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b/docs/assets/world_camera_image.png new file mode 100644 index 00000000..ea0d0a4e Binary files /dev/null and b/docs/assets/world_camera_image.png differ diff --git a/docs/batching.html b/docs/batching.html index d406f80d..6f1d7111 100644 --- a/docs/batching.html +++ b/docs/batching.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
\ No newline at end of file diff --git a/en/index.html b/en/index.html index f9f6f1b8..93ec3fbe 100644 --- a/en/index.html +++ b/en/index.html @@ -31,4 +31,4 @@ sample_sphere = sample_points_from_meshes(sphere_mesh, 5000) loss_chamfer, _ = chamfer_distance(sample_sphere, sample_test) - \ No newline at end of file + \ No newline at end of file diff --git a/en/users.html b/en/users.html index 15759df0..34569cb0 100644 --- a/en/users.html +++ b/en/users.html @@ -6,4 +6,4 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -

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\ No newline at end of file diff --git a/files/bundle_adjustment.ipynb b/files/bundle_adjustment.ipynb deleted file mode 100644 index 39320b6d..00000000 --- a/files/bundle_adjustment.ipynb +++ /dev/null @@ -1,439 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Absolute camera orientation given set of relative camera pairs\n", - "\n", - "This tutorial showcases the `cameras`, `transforms` and `so3` API.\n", - "\n", - "The problem we deal with is defined as follows:\n", - "\n", - "Given an optical system of $N$ cameras with extrinsics $\\{g_1, ..., g_N | g_i \\in SE(3)\\}$, and a set of relative camera positions $\\{g_{ij} | g_{ij}\\in SE(3)\\}$ that map between coordinate frames of randomly selected pairs of cameras $(i, j)$, we search for the absolute extrinsic parameters $\\{g_1, ..., g_N\\}$ that are consistent with the relative camera motions.\n", - "\n", - "More formally:\n", - "$$\n", - "g_1, ..., g_N = \n", - "{\\arg \\min}_{g_1, ..., g_N} \\sum_{g_{ij}} d(g_{ij}, g_i^{-1} g_j),\n", - "$$,\n", - "where $d(g_i, g_j)$ is a suitable metric that compares the extrinsics of cameras $g_i$ and $g_j$. \n", - "\n", - "Visually, the problem can be described as follows. The picture below depicts the situation at the beginning of our optimization. The ground truth cameras are plotted in green while the randomly initialized estimated cameras are plotted in blue:\n", - "![Initialization](data/bundle_adjustment_initialization.png)\n", - "\n", - "Our optimization seeks to align the estimated (blue) cameras with the ground truth (green) cameras, by minimizing the discrepancies between pairs of relative cameras. Thus, the solution to the problem should look as follows:\n", - "![Solution](data/bundle_adjustment_final.png)\n", - "\n", - "In practice, the camera extrinsics $g_{ij}$ and $g_i$ are represented using objects from the `SfMPerspectiveCameras` class initialized with the corresponding rotation and translation matrices `R_absolute` and `T_absolute` that define the extrinsic parameters $g = (R, T); R \\in SO(3); T \\in \\mathbb{R}^3$. In order to ensure that `R_absolute` is a valid rotation matrix, we represent it using an exponential map (implemented with `so3_exponential_map`) of the axis-angle representation of the rotation `log_R_absolute`.\n", - "\n", - "Note that the solution to this problem could only be recovered up to an unknown global rigid transformation $g_{glob} \\in SE(3)$. Thus, for simplicity, we assume knowledge of the absolute extrinsics of the first camera $g_0$. We set $g_0$ as a trivial camera $g_0 = (I, \\vec{0})$.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 0. Import Modules" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": { - "bento_obj_id": "139627658883376" - }, - "output_type": "execute_result" - } - ], - "source": [ - "# imports\n", - "import torch\n", - "from pytorch3d.transforms.so3 import (\n", - " so3_exponential_map,\n", - " so3_relative_angle,\n", - ")\n", - "from pytorch3d.renderer.cameras import (\n", - " SfMPerspectiveCameras,\n", - ")\n", - "\n", - "# add path for demo utils\n", - "import sys\n", - "import os\n", - "sys.path.append(os.path.abspath(''))\n", - "from utils import plot_camera_scene\n", - "\n", - "# set for reproducibility\n", - "torch.manual_seed(42)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Set up Cameras and load ground truth positions" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# load the SE3 graph of relative/absolute camera positions\n", - "camera_graph_file = './data/camera_graph.pth'\n", - "(R_absolute_gt, T_absolute_gt), \\\n", - " (R_relative, T_relative), \\\n", - " relative_edges = \\\n", - " torch.load(camera_graph_file)\n", - "\n", - "# create the relative cameras\n", - "cameras_relative = SfMPerspectiveCameras(\n", - " R = R_relative.cuda(),\n", - " T = T_relative.cuda(),\n", - " device = \"cuda\",\n", - ")\n", - "\n", - "# create the absolute ground truth cameras\n", - "cameras_absolute_gt = SfMPerspectiveCameras(\n", - " R = R_absolute_gt.cuda(),\n", - " T = T_absolute_gt.cuda(),\n", - " device = \"cuda\",\n", - ")\n", - "\n", - "# the number of absolute camera positions\n", - "N = R_absolute_gt.shape[0]" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Define optimization functions\n", - "\n", - "### Relative cameras and camera distance\n", - "We now define two functions crucial for the optimization.\n", - "\n", - "**`calc_camera_distance`** compares a pair of cameras. This function is important as it defines the loss that we are minimizing. The method utilizes the `so3_relative_angle` function from the SO3 API.\n", - "\n", - "**`get_relative_camera`** computes the parameters of a relative camera that maps between a pair of absolute cameras. Here we utilize the `compose` and `inverse` class methods from the PyTorch3d Transforms API." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "def calc_camera_distance(cam_1, cam_2):\n", - " \"\"\"\n", - " Calculates the divergence of a batch of pairs of cameras cam_1, cam_2.\n", - " The distance is composed of the cosine of the relative angle between \n", - " the rotation components of the camera extrinsics and the l2 distance\n", - " between the translation vectors.\n", - " \"\"\"\n", - " # rotation distance\n", - " R_distance = (1.-so3_relative_angle(cam_1.R, cam_2.R, cos_angle=True)).mean()\n", - " # translation distance\n", - " T_distance = ((cam_1.T - cam_2.T)**2).sum(1).mean()\n", - " # the final distance is the sum\n", - " return R_distance + T_distance\n", - "\n", - "def get_relative_camera(cams, edges):\n", - " \"\"\"\n", - " For each pair of indices (i,j) in \"edges\" generate a camera\n", - " that maps from the coordinates of the camera cams[i] to \n", - " the coordinates of the camera cams[j]\n", - " \"\"\"\n", - "\n", - " # first generate the world-to-view Transform3d objects of each \n", - " # camera pair (i, j) according to the edges argument\n", - " trans_i, trans_j = [\n", - " SfMPerspectiveCameras(\n", - " R = cams.R[edges[:, i]],\n", - " T = cams.T[edges[:, i]],\n", - " device = \"cuda\",\n", - " ).get_world_to_view_transform()\n", - " for i in (0, 1)\n", - " ]\n", - " \n", - " # compose the relative transformation as g_i^{-1} g_j\n", - " trans_rel = trans_i.inverse().compose(trans_j)\n", - " \n", - " # generate a camera from the relative transform\n", - " matrix_rel = trans_rel.get_matrix()\n", - " cams_relative = SfMPerspectiveCameras(\n", - " R = matrix_rel[:, :3, :3],\n", - " T = matrix_rel[:, 3, :3],\n", - " device = \"cuda\",\n", - " )\n", - " return cams_relative" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Optimization\n", - "Finally, we start the optimization of the absolute cameras.\n", - "\n", - "We use SGD with momentum and optimize over `log_R_absolute` and `T_absolute`. \n", - "\n", - "As mentioned earlier, `log_R_absolute` is the axis angle representation of the rotation part of our absolute cameras. We can obtain the 3x3 rotation matrix `R_absolute` that corresponds to `log_R_absolute` with:\n", - "\n", - "`R_absolute = so3_exponential_map(log_R_absolute)`\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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9PY1vfOMb89q+QLppIlY0XGrTYrFYEAgE4trh5AJSC3HlGG02G8xmM/R6PXp6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\nqIJnksff7wsAah6N5zvBNjmwc2c4ThPBYDCcck0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kS4SoHz2n9uzrxEOJjvxMP2JwMimU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higNJ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\nxD//+U+/PdJ99dVXK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lA5IkHXekO16MQaVSRb0/giCECczLXy6hMQCZjENLog8dOoSmpiaoVCoMDg7C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\neLBNIBD416xZk93d3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pQCAQwMMPPwyHw4FQKITLLrtsUvdNmnSTiMiCBkEQ0NHRgb6+PpSUlOCMM84Y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\ny4jLbvtjw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xwGKkeyFdYBgmbkn01q1b0dLSEpVNYbFYovQpEpFxZEbFyVj4kSXdDCAe2fb1\n9cFisciTbv78+cdlbNIroMfjQVtbG4LBYFJuDcRYyZFBlUxZbhzHxW18GVlyOzQ0hM7OToRCobhi\nNMmItU8lMpkhkek0vkQl0eFwOEpgXro+kQ9LiZBjS6LjFX54PB6YTCYolUo5CD2RAqFMI0u6U4jY\nggYiQk9PDzo7O5Gfn4+FCxdCoVDI6VXHA36/HwMDA/B4PKirqxulpjUW0u1eSBcSldxKN7vH4xll\neUlZFJHKYJmAKIonHemOF2NQKpVxrw/P81EC89KbS2QMQCLjyJLoQ4cOoaWlBUqlEoODgwgEAmhu\nbp7SY0wFWdKdAsQraOju7obVakVxcTGWLFkiW1iSfzfTcDqdaGtrQygUgsFgwOLFiye8jemmvZDo\nZpc6aET6JHmeh9/vx9GjR0dF69OJTLoXMmVVT9aNoVAo4r65xPr0e3p6ovQpfD4fnE4nRFGU32im\nAsFgEL/5zW/gdDoRDodx8cUXT+q+yZJuGhFb0MDzPDo7O9HX14cZM2bglFNOGTUh0nUTJHtDDQ8P\nywG7uro6sCyL9vb2Se3zZNHTVSqVyMvLGxW83Lx5MwoLC+HxeKKi9SqVapRlPFlfaSZJFxnKOxYE\nIa3El6gkWhAE+P1+DA8Pw+1246233kJHRwe0Wi2qq6tRUVGBNWvWxO1kPRls374ddXV1+K//+i8M\nDg7ivvvuy5Lu8UC8goZQKASLxQKbzYbKykosX7487QGMSMQjv1jY7Xa0tbVBoVCgoaFBtia8Xm9K\n2guJxjKVyBSxsyw7ioxjU6di81gjCz6kppdjIZPuhUxhKgJ28cBxHAwGA5RKJWpra7F+/XpZZU+l\nUqG7uzut5H/qqafK/x8aGpqQKy4SWdKdJCSy7ezshMFggNFojGqHU1VVhYaGhoxYMVJAK3ZfRISh\noSGYzWao1Wo0NTWNshbS3UhyOlq6E8FYqVORRQWxFV6RaW1SuS2mWalxssgU6SJO/EAQBGi1WsyY\nMQOVlZVTss8NGzZgaGgI3/ve9ya1fpZ0J4hY0XCpTYvFYoHf7x/VDicTkFqIR47RZrPBbDZDq9Wi\nubl5VCGChHRnG5zspJsIYxUVRJbbDg0Nwe/3g4ig0WigVCply3mqdSkydV0ySbqiKEbtSyrWmErc\nd999sFgsePTRR/Hwww9P+F7Pkm6SkMg2sqWK0+lEf38/AGD27NnIz8+fNNmmYvFI+gtEJAuZGwwG\nzJ07d1x/VirSjom291kk3UQYq9zW7/fDZrPB5XLBYrHIqmDxJBpTJeNMXpNMki7P81EuhHT7kyNh\nNpthMplQWFiI6upqCIIAl8uOLUCIAAAgAElEQVQ1ZmeWeMiS7jiIl2Nrt9thNpuhUChQVFQEnU4X\nZd1MFNIr/mQnKsMw6O/vR29vL3JyciYkZD4V7oUsxoekS5GTkwO/34/GxkYgjkRjpEhQPPHyZM/3\ndC/CSIR4pDtVlu6BAwdgs9lwzTXXwOFwIBAITKqYKUu6CRCPbAcGBmCxWKDVauV2OFardUIqXfHA\ncdykJqooiujr64PdbgfLsli4cKGcv5gs0kW6Wf3cySH2DSdVXQophzWWjDN5fY4n6cZ+TifOPfdc\nPPbYY/jhD3+IUCiEr33ta5M6p1nSjYGUiSCRLRHJ1WO5ubmjXtkVCgUCgUBK+4z1ySYzRqnIoqCg\nAEVFRaiqqpow4SIN7gBBELBz5054PB45yBQMBtHX1zcqaJTFaCRLhsnqUkTmsMYWe2SSdKeK+GKR\nSfeCSqXCt7/97ZS3kyXdY4gtaBBFEVarFV1dXSgsLMTixYvjdmfgOE72804WyWriSmPq7OxEUVGR\nXGRx8ODBSRdYTNYd4Ha70draikAggJaWFhgMBoiiiGAwiJ07dyIYDMJut8Pr9QJp1s89mfzGqWYv\njJXDGqlL4XK54Ha7sX379inXpeB5flIGwGT3JZGslFGUKSt7svjMk25sQYMgCOjq6oLVakVZWRmW\nLVs2po9Icg2kgvG2IVW0dXd3o6SkZNSY0u2XHQtutxttbW3geV7uFpGXl4dwOCxH8BUKBaqqquR1\nIv2Usa/GkalUJ7IwzVRhqvJ0Y3UpvF4vLBYLGhsb5VLoqdKlOF7uBZ7np0Wft88k6UpPxMHBQfj9\nfpSVlSEcDqOjowMDAwMoLy+X2+GMB4VCkbKlm4h0Ix8ApaWlcSvakCHSlcg2HA6jvr4+aelJxPgp\ni4uL5e+lV2OPxwO73R5FABIJS/9m6nU108hUgEtyYyQqtU2nLkWmSVeyqjPp1kgFJ/4I04jYDg3h\ncBgOhwNOpxPDw8OYOXMmVqxYMaGbYCosXal8uLe3N2H5cOz6U0W6Ho8Hra2tCIfDExbEGQ+JXo0l\nfVaPx4O+vj54PJ6oii+FQoFwOHxSBO8yVZE2HhGOpUsR2eFD0qWQhMvj6VIcL0s3S7onEGILGhiG\ngc/nQ1dXF5xOJ+bMmZOwHc54UCgUaSFdURRla7u/vx8VFRVJlw+n2ictHiZCtun2r8aTBJTKbyWr\n2Ov1YseOHSCiKem3limfcaYt3YkikTxjoi4SKpUKfr8fQ0NDEEVR7q82VYjnXjjRcVKTbmzaF8Mw\nUe1wSktLoVAoUFpaOul9pCOQBgBWqxVHjx5FZWXlhK3tdLoXInV16+vrx7VsMxXUiiy/VavVCIfD\nUc0vPR6PbBlHplJFuilORH9xpsqA0/1WEE+4XHow7tmzRw76xupSRJZCp4MgY0k3a+keJ8QjW0ld\nC4DcDkeqCEoFqRCe1Fm3p6cHhYWFEybbyDGkaulGkm1dXV3SxR7HK5MgXvPLSET6iyO1WaWAUeSr\ncTwf5XQlw0QQBGHK9yM9GFmWxcyZM2VSjdWl6OrqSkqXIhlk3QvHGfEKGmw2G9rb26FSqaLUtZCm\nINhkbszYzrr19fUp3Xwcx026QMPr9cLv92P//v2yZTuRYzoepJvM+MbzF8dq58ZaYpnqQpxJcs+k\nHkLkXE5Wl0JyG0W6jCLFy+PdH7GWbqbE51PBSUG6sQUNANDf3w+LxQKDwZBQ8CUdpDsRRHbWjWyr\n3tvbK5d6TgaTsXQje6GpVCosWbJkUjfldMuZHc9fLFliEhHs3bs3ykWRDn9xJDLZzeFE0+0dT5dC\nugY2my2hLgXP8/JxST7lEx3TmnRjc2wj2+Hk5eVhwYIFYyZpZ8q/J3XWdbvdqK2tHdVZN9UMiIm4\nOCLJVnIjbNmyZdL7TkbL90RHpL9YssR4nsfu3btRV1cnR+8lHQTJpZEOf3EmLd3p8OqNGJdRUVGR\n/H0iXYpt27Zh+/btUCgUaGxshMFgQHFxcdofMs899xwOHjwIURRxwQUX4JRTTpnUdqbHVYiBIAjo\n6emRa85FUZSLB2Lb4WQK8W4er9cLs9kMr9c7ZmfdVFO+kiFdn8+HtrY2+Hw+mWylsUhKY5OxdFMV\n6zmRkejmjyy9je1CHJtfPN7rbiZ9uvEqKqcT4ulSbNmyBYsXL0ZeXh52796Nnp4eWZjm/vvvT9u8\n3LdvH7q6unD//ffD7Xbjjjvu+OyQLs/z4HkeDocDPM+jv79/zHY4mYBkqUr7loJSgUBgFMHFQ6qB\nsLFIO5Jsa2trUVhYOGosqQQDx2pOOZ2t37HGn8hfLHUhlqxij8cDnufHbO9zsgXsMulqks4dy7Ko\nr6+HIAiYOXNmVAFOujBnzhzU19cDAPR6PYLB4KTP6bQjXZZlEQqF4HA40NPTg9ra2pTa4UhWXioT\nUsrV9fv9ctVWbW1t0kGpdLgXYteXXBpSl994ZBu5/mRvlkj3QmRGwclMuokQrwtxZHsfj8cDq9Uq\nt0jSarUIBoNyoGkqRcwzaVEfL4WxqXShsCwruyrfffddLFy4cNLnc9qRrtPpxK5du2AymVBcXIyZ\nM2emtD0pmJaKO0IURezZs0du9jiRElmk2acbS7aJXBqRSEXI/Hh0BM5kbnA6tpGovY/UbTgYDKK9\nvV0OpkZaxAaDAWq1OuWxZIoMj7es41RnL2zduhXvvvsuNmzYMOltTDvSNZlMWLFiBQYGBuB2u1Pe\nXiqk63A40NbWBq/Xi4aGBpSXl09qDOkg3XA4jH379sHj8YzpP060/nQi3UwgE801dTodNBoNSktL\nZetY0s31eDxwOp2wWq2yvzjSVyw1ZEwWnwVLd6rzdHft2oVXX30Vd911V0odhqcd6bIsC4Zh0pbu\nNZky3tjOularNaWLkEogze/3o7W1FQ6HA/PmzZsQ2UpIhXRZloXP50NHR4csjiKKYsZUz6YSx8PX\nmkg3N9JfPDg4iPb29lEaCNK/8UgvS7qpwefz4bnnnsMPfvCDUddmoph2pCtBqVSm3LEBE8jVJSKZ\nbFUqVVRn3b6+vpQeAJOxdP1+P8xms9x52O/3TzqAMFnL1O/3w+FwwOVyoaamBqIowuPxwO/3Y+fO\nnVHWmfQ3HZLXkWHthWTIPZ6/GMc0EKT84kh/sUajiSLjTFSkIcOluLFaulNJuh9//DHcbjceeeQR\n+btvfetbUfnFyWLaka40QdNp6Y5F3rGddefMmTPqSZeqe2AiPtVAIIC2tja4XC7U1dVhzpw5civ4\nyWKilm4wGITZbIbD4YBWq0VdXR2MRqO8DZfLhaamJigUirjWmRTNl/5OxO4S0yWrQKVSIT8/f5S/\nOBAIyGQ8ODiI4eFh7N27d5R+cbor746nwthUaumeffbZOPvss9OyrWlHujhGUlNt6U6ks26qD4Bk\nJkogEIDZbIbT6URtbW1Um/dUBW+SXT8UCqG9vR1DQ0Oora1FU1MTDh48OGo5aVyxQtqIqf6ShLSl\naqPYgoN0BJAmi0yR7lTsJ7LSS8ov3rFjB1paWuRzH9naR3ojiRWTnwwyTbrSvjK531QxLUkXabZ0\nI7dDROjv70d7eztMJlNSnXXToambCLFkG1vNhjT4Hscj3XA4DIvFgoGBAVRXV2PWrFlRhRXxAmmJ\nthev+gtjBJDiCZqfTMhkGbBCoZDfMiIh+Yslq1gSME/WXxyJ4yVgPl0UxjCdSTdd1oHUWJKI0Nvb\nC4vFgry8vAl11lUoFAiFQmkZj4RIsq2pqYlLtulCIp8uz/Po6OhAX19fQoH3eDm+kxlnogBSOByW\nX5Ml3dZwOAye52E2m+V10q2JMJ0t3XgYSyw9WX+xJNMoKYNJRBzpHsp0U0qJ4KeLli6mK+mmMyWJ\n4zjY7Xb09vYiPz8/YQPK8baRLuGcSAWyRJZtuhFr6Uptgrq7u8cVU09k1abr+iiVSuTl5UXlPvt8\nPhw5cgRGo1Gu/vL5fHKZaKwmwomMTArRTHQejeUvlnz1kWI0Op0OoVAIRqMRfr9/ypXaIvNyBUGY\nNkHaaUm6kZispSCJLLe3t0OhUKSk15AO94Ioijh48KBMtpPtZDEZSKQraVh0dXWhrKwMy5cvH9dq\nOV7FERzHoaioaJQmgkQGQ0ND6OjoQDgchkqlisqi0Ov14xLdyWbppmsfiZTBJPeQ2WxGIBDA0aNH\nZX9xPHGgdCDWp5t1L0whYjMYJvKEi+ysW1xcjLlz56K7uzuliZBKyx4pE8Dv98NkMmWUbCMxNDSE\n9vZ2lJSUTEjDIpJgJQI5XsUR8QJ3iHhN9ng8smwjEclkEC+SfyK89k8nSO4hjUaD4uJiWToz0YNQ\nqVSOEpOfKGlG3vtZn26GIGUwJEO6ka/Mka3V/X5/Wrr5TnQbUumn3W5HTU0NPB4PioqKUroBJ0oU\nRIS+vj50dHTAYDBg6dKlE374xNNZOJ4VaUQEZw/BOySifN7I9I73mizJBMaL5BsMBtlPn4mb+WQg\nXQmxvtWxHoQSGUf2WJtIJ4nIoN10ETDHdCXdieTqSp11e3p6UF5ePuqVeSpbqMdDJNlWV1ejsbER\nDMOgr68v5VzfZElXSoczm83Izc1FdXU1GIaZlLWfKJCWKdL1DIqwtYkQQgQwDPgg4ci7PFrf53He\nPRpwKsBQxKKkiQXDfnpuImUCS0pK5O95npd9lX6/H7t37x4VPJICd+nwxWbCos7kAzDZ7IVEPdaC\nwaAcvItMJ9RqtVEuCo1GE+UPFwQhparQTGJakq6EsXJ1w+EwOjs70dfXh/LycqxYsSLuZEhHECwZ\n4o7McY0kWwmpyjtKftmxiEAq9Ghra4PRaJQzNHp6ehAMBie133iBtKkm3XcfFODxF6AvPwBTGYOy\nFg66fBZEQMdmAQsuVuKUa1T45MkQ/ushLdz9Itr+M3J9lFoG5fM5KNSJI/m5ublgGAaCIKCxsXFU\n8GhwcDBKnCay0ONEDNxlUvEtFd9qZFufWH+x9FbidrvR29uLQCAAn8+HgwcPorW1FRzHYf78+VN2\nrJ2dnXj44YfxhS98AWvWrElpW9OadOORXSgUQkdHBwYGBlBZWTmu7GMqsoYSxrJ0Y8k2Msc12W0k\nO4axcm2HhobQ2toKnU6HefPmRVkFqZBkpgNpARdBV8ig8gwb5s2bASFMCPsBV6+Io+/xqDtNgaPv\nhzGjhUNuBYPnr/FixQ1qsAoGRIDfQdj4aBB8CDj3zuRSAhMFjyKbX8b6K5PNb50OVW8TwVTk6cYT\nLweAzZs3o7y8HBaLBUePHsWBAwfg9/tRWFiIO+64I237DwQCePrpp9HS0pKW7U1L0pUmaqSlK5Gb\nzWZDVVXVpDvrpjKeSESSbVVVFRoaGsYcz1Ro6uKYEtrRo0ehVCrR3NwcV6xjOqmM9R0QUNLEQHrU\nckoGfoeI4S4RK78+0jLHN0yo+5wC9acrsfXZEQu+duWnU73pXCXaPhz7zSQZiymRmHkiPQSp04lk\nFSebB54qMlmwkGlhHZPJhLVr16K6ulpuGJBKv8F4UCqV+P73v4+//vWvadnetCRdCQqFAn6/H4cO\nHYLdbk+K3KYaoVAIFotFJv9kx5PuPmkulwtHjx4FwzBR4jzJrDsRZJp0e/cJmLWGgdU+8tnRLWLI\nLKDx7PhBlKVXqfHGXX4Uz2JhKIq4DuMML9nX1K3PBeHoIih1QG4FC0MhA4ZjAZgAmKACoBrZIIKu\nIIYDAfQGAggEHAiFwujfWYgPv+3GpS85k27xM1GciE0pU0WsGyMyT3e8CtKJguO4tD60piXpMgyD\nQCCAvr4+WVwl1kc6UaTqCyIiHDlyBIODg3Jb9YlM9HT1SfN4PDh69CgEQUBDQ8OoKqNE60aS5DNX\nO9G7n8d5P9JDaxr7GGw2DgOHgVatHz4Xj7AHcDpywIgsTruBB8MBJI6QHNHIv6II+IYIrj4Rc9Yq\nYSxJ/jx5bAR9IQPYgaF2Ae5+Qt2qsUnqvHs0eOXbflzyqDYqmJYOOLoI53xfg5CX4LCK8AzSyPEC\nADNyvAoNkFvBwVisB8uNvGlYNvHY+39hiL5h1KwamXuRLX7UanWUiyIVUaBMk24mEA6HMy5gni5M\nS9INhULYtWsXioqKoNFoUFZWltL2JpPvGzkWi8UCr9ebklsj1UCaKIo4fPgwRFFEQ0PDhLpXxAbD\nTv2aFoYiFn+8ygkA+K+fGMApI1PCPl3X2c2h/d8swr4AWi4LouViDQYHPBjalQvPIEHgR5ZnmBES\nYhiAYQFjCYO8mQq4BwjGEkwIDMPA1alC3gxC9fLxpzCrYHDO9zX4530BrPlhclZQsg9hhgVEnqDS\nMyiexaF41uhlwv4RQrZsEtGxhce+18OoXMShtJlD7ul9COycEyWAHxnFTyQKFBm4G2+cmZJ1zCTi\nWbrZPN0phEqlwvLly+F2u9He3p7y9iZDupEiMFVVVTAajSgrK5v05J6se0HqyzY8PIzq6mo5/Wsi\niOdeKJ2twNwvqbFonQZ/vMqJ6lOUWPeoMWrbbR8G4RkKwTTbjxlzOex6PBe7nwXKz+GhNPajqLgH\nprzEBOG1i3D3TcwNwTBA334RxDOoXJT89M2tYFGzQoFdfwlhznlKKMfh3mRJt7SZQ99BETPmJn79\nVKhHAnhtG3kUzWLxzX8YoFAxaPsPD7tGQCBm+bGi+FLgbnh4GF1dXQiFQrIoUGShR+TrcKa6NWcy\nNS2elm5We2EKES+QlgomkqsbS7aSZdvb25vShec4bkLHEimIU1dXB4VCAaPROCkXSaIMDiKgtEmB\n724tQOvGEB5aaseCi9T4/J0GDA8P46OXHSg/w4HqfD0WnlaDM64Oo3OLgE9eyIOnQwHDag5qtTeK\nIKTIvsFgABsyQCQNgOTPmXWPgIqlLLTFIQg8gVOMPl5FAumMxnOUeP+XARx9n0f5vPTcoFXLOOx7\nPRyXdEWB0LlVQOc2HqYyFqetV0NjihzviCsi2Us2nihQvMaXBoNBJqWpTh3LpEUdSbqS+2Sq9m02\nm/HMM89gcHAQHMdh06ZNuO222ybdQWJaki6OEe9UyTvGQyTZxlPcSrXBJcdxCARibZ7RCIVCMJvN\nsNvtUYI4TqczaZ8wHyS4+kW4+kQ4ewQc/Q+Phq9+ui7RaKulfpUK391WgI/+4MBPlwyh4aJh5OUW\nIIfTw1TmkpevOkUBa1cQgptB73Ythv6iwIrri1C/gJPHLxGEzWqFozcMqy8AnU4Ho9E4br7rBQ9r\n4RkOov+QEl3bBIgxLwfSsEdlJxz7vnKRAv/3XT9ufH/sGyZZgjIWs/AMRp8rIUzo2CKgZy8PXT6D\neReqkFs+mhC0+QTXbh3yKlMji3iiQFLjS6/XK/cT3Lp1a5QoULq7eWRaYUza11RXDdbW1uJHP/pR\n2rY3bUkXadSxHYt0w+EwOjo60N/fn1DeMB1jGS+QJpG+FKiLDBwKYYLHqoR9L6HoQkLQPRKkcg+I\nIPFTIpI4hERguFuAPp9FQTUHVquAQJ/um2EBy+Ywqpd9ejP6fD60trZC1RzEf/+rHjueKsO2VwNg\n1AxyZseWAbOoOycM92EWs85S4Mg7PDZ1hHDaejVyZnxakpuvFeEtIBQ1MPJrs91ujxKqie0wkTOD\nhaaAhY0Ponr+5Kbvdz5OnMkxKRw7v+EAoWMzD7+TwLIMeveKKKxjsfnpIDglg7JmDhoTwHAMjMUM\nNDmAbWcOmq5Iv4UmNb7U6XQQRRF6vR7V1dVRWgjp7uaRaS1d6cE8nVwLmM6kKwmrpAPxSJfneVgs\nFvT396OysnLcAFkqojcYI5AWqWlbWTETTZVLMdxOeP8vPnhtIowlLFiOQZ9FDYYBCgrDUBsZmEpZ\nFNYqwR57/RYFQvcuHn6nCKWGwcJLNFBqRn5zvhMAH2HZKjUMdr0awBfvNSAYDKKtrQ1OpxMNDQ0o\nKCgAwzA461Yg5CX0HgjgwJV5+PJvwyg5ljvOMAwYjtB4lnIkr3Y2h+XXqfDh74LwDBBW3aiGoYgd\nebUe47U5FArB7XaPCiZptVr4/X7Y7fYpqwKbyKt42E84+n4YIEAIAzkzWFQu5tCzV8CZt4zk4gph\nQu8+AQEXQQwRHFYCqxJh26OHbw3JFXNgAGMRg9wKFip9euZ3pE93Mt08Ii3jsbp5ZJp0pQKf6SR2\ng+lMuulEJOlGkVwSZCsh1XLiWEvZPRTGgU960ddlR2FhIYqKFiPUwYIvY1C1VAF9/qfZBQCg1Cmx\n8JoQ6ldFE9DAUR7DXQIYlkHFfAV0eaNfJRlEZy8otUDAI6LVfBQ2my1xxwoOWPBlBqqKQbz/iAKa\nHOBz31SDVXxK4KVzOARchEP/4rHkKyqoDAw2PhpE0E1YfLkKzBinVqVSoaCgYFSHieHhYbS2tkZV\nganVapkcjEZjytoIEyHd5vOVCPsJRAC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uBU6Uz1cidwYLhYaBQjVCbI5uAZ07wuADhLNu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WsJk5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\ncgcFBTkPHTpUiZ8lW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SXnU84Pf7MTAwAI/Hg5qamlFqWmMh2e6FZCFeya18s3s8nlGWl5xFoVYGSwUk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\nLy8PZ86cg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62N1u9zjLS8qiUCqDpQKiKJ52pDtZjEGtVke9PzzPhwnMS18uyhiARMbKkuij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1YgoYzWdTrdkNb3MPe4UXc7/QPxcKV6JpMJlZWVtETPZrOhrq4ODofDb7Lbixcv4q233kJcXBxw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\nGo2ora1FU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Z1ZN1YyiVyqhvLpE+/Z6enjB9Cq/XC4fDAUEQpDeaqUAgEMCTTz4Jh8OBUCiE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\nIdgWIrpOp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D7JNkGAZerxctLS0jovWJRDLdC8myqifqxpBKpRHfXMJ9+r29vSH6FB6PB3a7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\nc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vKKvVKgXsKisrwbIsWltbxzXmyaKnq1KpkJmZOSx4uXXrVuTk5MDlcoVE69Vq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\nJYg7UKvVH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+cOAA5s+fD5VKhZGREYRCIcybN29a9zEd5Eh3GpCooKG/vx9WqxWlpaVYunSp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" - ] - }, - "metadata": { - "bento_obj_id": "139625435468368" - }, - "output_type": "display_data" - } - ], - "source": [ - "# initialize the absolute log-rotations/translations with random entries\n", - "log_R_absolute_init = torch.randn(N, 3).float().cuda()\n", - "T_absolute_init = torch.randn(N, 3).float().cuda()\n", - "\n", - "# futhermore, we know that the first camera is a trivial one \n", - "# (see the description above)\n", - "log_R_absolute_init[0, :] = 0.\n", - "T_absolute_init[0, :] = 0.\n", - "\n", - "# instantiate a copy of the initialization of log_R / T\n", - "log_R_absolute = log_R_absolute_init.clone().detach()\n", - "log_R_absolute.requires_grad = True\n", - "T_absolute = T_absolute_init.clone().detach()\n", - "T_absolute.requires_grad = True\n", - "\n", - "# the mask the specifies which cameras are going to be optimized\n", - "# (since we know the first camera is already correct, \n", - "# we only optimize over the 2nd-to-last cameras)\n", - "camera_mask = torch.ones(N, 1).float().cuda()\n", - "camera_mask[0] = 0.\n", - "\n", - "# init the optimizer\n", - "optimizer = torch.optim.SGD([log_R_absolute, T_absolute], lr=.1, momentum=0.9)\n", - "\n", - "# run the optimization\n", - "n_iter = 2000 # fix the number of iterations\n", - "for it in range(n_iter):\n", - " # re-init the optimizer gradients\n", - " optimizer.zero_grad()\n", - "\n", - " # compute the absolute camera rotations as \n", - " # an exponential map of the logarithms (=axis-angles)\n", - " # of the absolute rotations\n", - " R_absolute = so3_exponential_map(log_R_absolute * camera_mask)\n", - "\n", - " # get the current absolute cameras\n", - " cameras_absolute = SfMPerspectiveCameras(\n", - " R = R_absolute,\n", - " T = T_absolute * camera_mask,\n", - " device = \"cuda\",\n", - " )\n", - "\n", - " # compute the relative cameras as a compositon of the absolute cameras\n", - " cameras_relative_composed = \\\n", - " get_relative_camera(cameras_absolute, relative_edges)\n", - "\n", - " # compare the composed cameras with the ground truth relative cameras\n", - " # camera_distance corresponds to $d$ from the description\n", - " camera_distance = \\\n", - " calc_camera_distance(cameras_relative_composed, cameras_relative)\n", - "\n", - " # our loss function is the camera_distance\n", - " camera_distance.backward()\n", - " \n", - " # apply the gradients\n", - " optimizer.step()\n", - "\n", - " # plot and print status message\n", - " if it % 200==0 or it==n_iter-1:\n", - " status = 'iteration=%3d; camera_distance=%1.3e' % (it, camera_distance)\n", - " plot_camera_scene(cameras_absolute, cameras_absolute_gt, status)\n", - "\n", - "print('Optimization finished.')\n" - ] - } - ], - "metadata": { - "bento_stylesheets": { - "bento/extensions/flow/main.css": true, - "bento/extensions/kernel_selector/main.css": true, - "bento/extensions/kernel_ui/main.css": true, - "bento/extensions/new_kernel/main.css": true, - "bento/extensions/system_usage/main.css": true, - "bento/extensions/theme/main.css": true - }, - "file_extension": ".py", - "kernelspec": { - "display_name": "p3d_dev7", - "language": "python", - "name": "p3d_dev7" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.6" - }, - "mimetype": "text/x-python", - "name": "python", - "npconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": 3 - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/files/bundle_adjustment.py b/files/bundle_adjustment.py deleted file mode 100644 index 79ccba35..00000000 --- a/files/bundle_adjustment.py +++ /dev/null @@ -1,219 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. - - -# # Absolute camera orientation given set of relative camera pairs -# -# This tutorial showcases the `cameras`, `transforms` and `so3` API. -# -# The problem we deal with is defined as follows: -# -# Given an optical system of $N$ cameras with extrinsics $\{g_1, ..., g_N | g_i \in SE(3)\}$, and a set of relative camera positions $\{g_{ij} | g_{ij}\in SE(3)\}$ that map between coordinate frames of randomly selected pairs of cameras $(i, j)$, we search for the absolute extrinsic parameters $\{g_1, ..., g_N\}$ that are consistent with the relative camera motions. -# -# More formally: -# $$ -# g_1, ..., g_N = -# {\arg \min}_{g_1, ..., g_N} \sum_{g_{ij}} d(g_{ij}, g_i^{-1} g_j), -# $$, -# where $d(g_i, g_j)$ is a suitable metric that compares the extrinsics of cameras $g_i$ and $g_j$. -# -# Visually, the problem can be described as follows. The picture below depicts the situation at the beginning of our optimization. The ground truth cameras are plotted in green while the randomly initialized estimated cameras are plotted in blue: -# ![Initialization](data/bundle_adjustment_initialization.png) -# -# Our optimization seeks to align the estimated (blue) cameras with the ground truth (green) cameras, by minimizing the discrepancies between pairs of relative cameras. Thus, the solution to the problem should look as follows: -# ![Solution](data/bundle_adjustment_final.png) -# -# In practice, the camera extrinsics $g_{ij}$ and $g_i$ are represented using objects from the `SfMPerspectiveCameras` class initialized with the corresponding rotation and translation matrices `R_absolute` and `T_absolute` that define the extrinsic parameters $g = (R, T); R \in SO(3); T \in \mathbb{R}^3$. In order to ensure that `R_absolute` is a valid rotation matrix, we represent it using an exponential map (implemented with `so3_exponential_map`) of the axis-angle representation of the rotation `log_R_absolute`. -# -# Note that the solution to this problem could only be recovered up to an unknown global rigid transformation $g_{glob} \in SE(3)$. Thus, for simplicity, we assume knowledge of the absolute extrinsics of the first camera $g_0$. We set $g_0$ as a trivial camera $g_0 = (I, \vec{0})$. -# - -# ## 0. Import Modules - -# In[2]: - - -# imports -import torch -from pytorch3d.transforms.so3 import ( - so3_exponential_map, - so3_relative_angle, -) -from pytorch3d.renderer.cameras import ( - SfMPerspectiveCameras, -) - -# add path for demo utils -import sys -import os -sys.path.append(os.path.abspath('')) -from utils import plot_camera_scene - -# set for reproducibility -torch.manual_seed(42) - - -# ## 1. Set up Cameras and load ground truth positions - -# In[3]: - - -# load the SE3 graph of relative/absolute camera positions -camera_graph_file = './data/camera_graph.pth' -(R_absolute_gt, T_absolute_gt), (R_relative, T_relative), relative_edges = torch.load(camera_graph_file) - -# create the relative cameras -cameras_relative = SfMPerspectiveCameras( - R = R_relative.cuda(), - T = T_relative.cuda(), - device = "cuda", -) - -# create the absolute ground truth cameras -cameras_absolute_gt = SfMPerspectiveCameras( - R = R_absolute_gt.cuda(), - T = T_absolute_gt.cuda(), - device = "cuda", -) - -# the number of absolute camera positions -N = R_absolute_gt.shape[0] - - -# ## 2. Define optimization functions -# -# ### Relative cameras and camera distance -# We now define two functions crucial for the optimization. -# -# **`calc_camera_distance`** compares a pair of cameras. This function is important as it defines the loss that we are minimizing. The method utilizes the `so3_relative_angle` function from the SO3 API. -# -# **`get_relative_camera`** computes the parameters of a relative camera that maps between a pair of absolute cameras. Here we utilize the `compose` and `inverse` class methods from the PyTorch3d Transforms API. - -# In[ ]: - - -def calc_camera_distance(cam_1, cam_2): - """ - Calculates the divergence of a batch of pairs of cameras cam_1, cam_2. - The distance is composed of the cosine of the relative angle between - the rotation components of the camera extrinsics and the l2 distance - between the translation vectors. - """ - # rotation distance - R_distance = (1.-so3_relative_angle(cam_1.R, cam_2.R, cos_angle=True)).mean() - # translation distance - T_distance = ((cam_1.T - cam_2.T)**2).sum(1).mean() - # the final distance is the sum - return R_distance + T_distance - -def get_relative_camera(cams, edges): - """ - For each pair of indices (i,j) in "edges" generate a camera - that maps from the coordinates of the camera cams[i] to - the coordinates of the camera cams[j] - """ - - # first generate the world-to-view Transform3d objects of each - # camera pair (i, j) according to the edges argument - trans_i, trans_j = [ - SfMPerspectiveCameras( - R = cams.R[edges[:, i]], - T = cams.T[edges[:, i]], - device = "cuda", - ).get_world_to_view_transform() - for i in (0, 1) - ] - - # compose the relative transformation as g_i^{-1} g_j - trans_rel = trans_i.inverse().compose(trans_j) - - # generate a camera from the relative transform - matrix_rel = trans_rel.get_matrix() - cams_relative = SfMPerspectiveCameras( - R = matrix_rel[:, :3, :3], - T = matrix_rel[:, 3, :3], - device = "cuda", - ) - return cams_relative - - -# ## 3. Optimization -# Finally, we start the optimization of the absolute cameras. -# -# We use SGD with momentum and optimize over `log_R_absolute` and `T_absolute`. -# -# As mentioned earlier, `log_R_absolute` is the axis angle representation of the rotation part of our absolute cameras. We can obtain the 3x3 rotation matrix `R_absolute` that corresponds to `log_R_absolute` with: -# -# `R_absolute = so3_exponential_map(log_R_absolute)` -# - -# In[ ]: - - -# initialize the absolute log-rotations/translations with random entries -log_R_absolute_init = torch.randn(N, 3).float().cuda() -T_absolute_init = torch.randn(N, 3).float().cuda() - -# futhermore, we know that the first camera is a trivial one -# (see the description above) -log_R_absolute_init[0, :] = 0. -T_absolute_init[0, :] = 0. - -# instantiate a copy of the initialization of log_R / T -log_R_absolute = log_R_absolute_init.clone().detach() -log_R_absolute.requires_grad = True -T_absolute = T_absolute_init.clone().detach() -T_absolute.requires_grad = True - -# the mask the specifies which cameras are going to be optimized -# (since we know the first camera is already correct, -# we only optimize over the 2nd-to-last cameras) -camera_mask = torch.ones(N, 1).float().cuda() -camera_mask[0] = 0. - -# init the optimizer -optimizer = torch.optim.SGD([log_R_absolute, T_absolute], lr=.1, momentum=0.9) - -# run the optimization -n_iter = 2000 # fix the number of iterations -for it in range(n_iter): - # re-init the optimizer gradients - optimizer.zero_grad() - - # compute the absolute camera rotations as - # an exponential map of the logarithms (=axis-angles) - # of the absolute rotations - R_absolute = so3_exponential_map(log_R_absolute * camera_mask) - - # get the current absolute cameras - cameras_absolute = SfMPerspectiveCameras( - R = R_absolute, - T = T_absolute * camera_mask, - device = "cuda", - ) - - # compute the relative cameras as a compositon of the absolute cameras - cameras_relative_composed = get_relative_camera(cameras_absolute, relative_edges) - - # compare the composed cameras with the ground truth relative cameras - # camera_distance corresponds to $d$ from the description - camera_distance = calc_camera_distance(cameras_relative_composed, cameras_relative) - - # our loss function is the camera_distance - camera_distance.backward() - - # apply the gradients - optimizer.step() - - # plot and print status message - if it % 200==0 or it==n_iter-1: - status = 'iteration=%3d; camera_distance=%1.3e' % (it, camera_distance) - plot_camera_scene(cameras_absolute, cameras_absolute_gt, status) - -print('Optimization finished.') - diff --git a/files/camera_position_optimization_with_differentiable_rendering.ipynb b/files/camera_position_optimization_with_differentiable_rendering.ipynb deleted file mode 100644 index b1314da5..00000000 --- a/files/camera_position_optimization_with_differentiable_rendering.ipynb +++ /dev/null @@ -1,697 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Camera position optimization using differentiable rendering\n", - "\n", - "In this tutorial we will learn the [x, y, z] position of a camera given a reference image using differentiable rendering. \n", - "\n", - "We will first initialize a renderer with a starting position for the camera. We will then use this to generate an image, compute a loss with the reference image, and finally backpropagate through the entire pipeline to update the position of the camera. \n", - "\n", - "This tutorial shows how to:\n", - "- load a mesh from an `.obj` file\n", - "- initialize a `Camera`, `Shader` and `Renderer`,\n", - "- render a mesh\n", - "- set up an optimization loop with a loss function and optimizer\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Set up and imports" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import torch\n", - "import numpy as np\n", - "from tqdm import tqdm_notebook\n", - "import imageio\n", - "import torch.nn as nn\n", - "import torch.nn.functional as F\n", - "import matplotlib.pyplot as plt\n", - "from skimage import img_as_ubyte\n", - "\n", - "# io utils\n", - "from pytorch3d.io import load_obj\n", - "\n", - "# datastructures\n", - "from pytorch3d.structures import Meshes, Textures\n", - "\n", - "# 3D transformations functions\n", - "from pytorch3d.transforms import Rotate, Translate\n", - "\n", - "# rendering components\n", - "from pytorch3d.renderer import (\n", - " OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, \n", - " RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams,\n", - " SilhouetteShader, PhongShader, PointLights\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Load the Obj\n", - "\n", - "We will load an obj file and create a **Meshes** object. **Meshes** is a unique datastructure provided in PyTorch3d for working with **batches of meshes of different sizes**. It has several useful class methods which are used in the rendering pipeline. " - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Set the cuda device \n", - "device = torch.device(\"cuda:0\")\n", - "torch.cuda.set_device(device)\n", - "\n", - "# Load the obj and ignore the textures and materials.\n", - "verts, faces_idx, _ = load_obj(\"./data/teapot.obj\")\n", - "faces = faces_idx.verts_idx\n", - "\n", - "# Initialize each vertex to be white in color.\n", - "verts_rgb = torch.ones_like(verts)[None] # (1, V, 3)\n", - "textures = Textures(verts_rgb=verts_rgb.to(device))\n", - "\n", - "# Create a Meshes object for the teapot. Here we have only one mesh in the batch.\n", - "teapot_mesh = Meshes(\n", - " verts=[verts.to(device)], \n", - " faces=[faces.to(device)], \n", - " textures=textures\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n", - "\n", - "## Optimization setup" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create a renderer\n", - "\n", - "A **renderer** in PyTorch3d is composed of a **rasterizer** and a **shader** which each have a number of subcomponents such as a **camera** (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest. \n", - "\n", - "For optimizing the camera position we will use a renderer which produces a **silhouette** of the object only and does not apply any **lighting** or **shading**. We will also initialize another renderer which applies full **phong shading** and use this for visualizing the outputs. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Initialize an OpenGL perspective camera.\n", - "cameras = OpenGLPerspectiveCameras(device=device)\n", - "\n", - "# To blend the 100 faces we set a few parameters which control the opacity and the sharpness of \n", - "# edges. Refer to blending.py for more details. \n", - "blend_params = BlendParams(sigma=1e-4, gamma=1e-4)\n", - "\n", - "# Define the settings for rasterization and shading. Here we set the output image to be of size\n", - "# 256x256. To form the blended image we use 100 faces for each pixel. Refer to rasterize_meshes.py\n", - "# for an explanation of this parameter. \n", - "raster_settings = RasterizationSettings(\n", - " image_size=256, \n", - " blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, \n", - " faces_per_pixel=100, \n", - " bin_size=0\n", - ")\n", - "\n", - "# Create a silhouette mesh renderer by composing a rasterizer and a shader. \n", - "silhouette_renderer = MeshRenderer(\n", - " rasterizer=MeshRasterizer(\n", - " cameras=cameras, \n", - " raster_settings=raster_settings\n", - " ),\n", - " shader=SilhouetteShader(blend_params=blend_params)\n", - ")\n", - "\n", - "\n", - "# We will also create a phong renderer. This is simpler and only needs to render one face per pixel.\n", - "raster_settings = RasterizationSettings(\n", - " image_size=256, \n", - " blur_radius=0.0, \n", - " faces_per_pixel=1, \n", - " bin_size=0\n", - ")\n", - "# We can add a point light in front of the object. \n", - "lights = PointLights(device=device, location=((2.0, 2.0, -2.0),))\n", - "phong_renderer = MeshRenderer(\n", - " rasterizer=MeshRasterizer(\n", - " cameras=cameras, \n", - " raster_settings=raster_settings\n", - " ),\n", - " shader=PhongShader(device=device, lights=lights)\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Create a reference image\n", - "\n", - "We will first position the teapot and generate an image. We use helper functions to rotate the teapot to a desired viewpoint. Then we can use the renderers to produce an image. Here we will use both renderers and visualize the silhouette and full shaded image. " - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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JiQmCIEBrzebNm9m5cyee55HP5xMhM1Prz1Wh0r4mh7uvEfssnU+qWCzS399Pf39/4uNy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\n5mz/LUcpLFIKi42wld6lWPbnMh5HlN3M5sdpnVg2FA0HAaN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" - ] - }, - "metadata": { - "bento_obj_id": "140267769944592" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Select the viewpoint using spherical angles \n", - "distance = 3 # distance from camera to the object\n", - "elevation = 40.0 # angle of elevation in degrees\n", - "azimuth = 10.0 # angle of azimuth rotation in degrees\n", - "\n", - "# Get the position of the camera based on the spherical angles\n", - "R, T = look_at_view_transform(distance, elevation, azimuth, device=device)\n", - "\n", - "# Render the teapot providing the values of R and T. \n", - "silhouete = silhouette_renderer(meshes_world=teapot_mesh, R=R, T=T)\n", - "image_ref = phong_renderer(meshes_world=teapot_mesh, R=R, T=T)\n", - "\n", - "silhouete = silhouete.cpu().numpy()\n", - "image_ref = image_ref.cpu().numpy()\n", - "\n", - "plt.figure(figsize=(10, 10))\n", - "plt.subplot(1, 2, 1)\n", - "plt.imshow(silhouete.squeeze()[..., 3]) # only plot the alpha channel of the RGBA image\n", - "plt.grid(\"off\")\n", - "plt.subplot(1, 2, 2)\n", - "plt.imshow(image_ref.squeeze())\n", - "plt.grid(\"off\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Set up a basic model \n", - "\n", - "Here we create a simple model class and initialize a parameter for the camera position. " - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "class Model(nn.Module):\n", - " def __init__(self, meshes, renderer, image_ref):\n", - " super().__init__()\n", - " self.meshes = meshes\n", - " self.device = meshes.device\n", - " self.renderer = renderer\n", - " \n", - " # Get the silhouette of the reference RGB image by finding all the non zero values. \n", - " image_ref = torch.from_numpy((image_ref[..., :3].max(-1) != 0).astype(np.float32))\n", - " self.register_buffer('image_ref', image_ref)\n", - " \n", - " # Create an optimizable parameter for the x, y, z position of the camera. \n", - " self.camera_position = nn.Parameter(\n", - " torch.from_numpy(np.array([3.0, 6.9, -2.5], dtype=np.float32)).to(meshes.device))\n", - "\n", - " def forward(self):\n", - " \n", - " # Render the image using the updated camera position. Based on the new position of the \n", - " # camer we calculate the rotation and translation matrices\n", - " R = look_at_rotation(self.camera_position[None, :], device=self.device) # (1, 3, 3)\n", - " T = -torch.bmm(R.transpose(1, 2), self.camera_position[None, :, None])[:, :, 0] # (1, 3)\n", - " \n", - " image = self.renderer(meshes_world=self.meshes.clone(), R=R, T=T)\n", - " \n", - " # Calculate the silhouette loss\n", - " loss = torch.sum((image[..., 3] - self.image_ref) ** 2)\n", - " return loss, image\n", - " " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Initialize the model and optimizer\n", - "\n", - "Now we can create an instance of the **model** above and set up an **optimizer** for the camera position parameter. " - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# We will save images periodically and compose them into a GIF.\n", - "filename_output = \"./teapot_optimization_demo.gif\"\n", - "writer = imageio.get_writer(filename_output, mode='I', duration=0.3)\n", - "\n", - "# Initialize a model using the renderer, mesh and reference image\n", - "model = Model(meshes=teapot_mesh, renderer=silhouette_renderer, image_ref=image_ref).to(device)\n", - "\n", - "# Create an optimizer. Here we are using Adam and we pass in the parameters of the model\n", - "optimizer = torch.optim.Adam(model.parameters(), lr=0.05)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Visualise the starting position and the reference position" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5,1,'Reference silhouette')" - ] - }, - "execution_count": 12, - "metadata": { - "bento_obj_id": "140267760329488" - }, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140267802952144" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 10))\n", - "\n", - "_, image_init = model()\n", - "plt.subplot(1, 2, 1)\n", - "plt.imshow(image_init.detach().squeeze().cpu().numpy()[..., 3])\n", - "plt.grid(\"off\")\n", - "plt.title(\"Starting position\")\n", - "\n", - "plt.subplot(1, 2, 2)\n", - "plt.imshow(model.image_ref.cpu().numpy().squeeze())\n", - "plt.grid(\"off\")\n", - "plt.title(\"Reference silhouette\")\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Run the optimization \n", - "\n", - "We run several iterations of the forward and backward pass and save outputs every 10 iterations. When this has finished take a look at `./teapot_optimization_demo.gif` for a cool gif of the optimization process!" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "2d3e3feb01f74f29a767dea9f99e1315", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, max=200), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": { - "bento_obj_id": "140266489631952" - }, - "output_type": "display_data" - } - ], - "source": [ - "loop = tqdm_notebook(range(200))\n", - "for i in loop:\n", - " optimizer.zero_grad()\n", - " loss, _ = model()\n", - " loss.backward()\n", - " optimizer.step()\n", - " \n", - " loop.set_description('Optimizing (loss %.4f)' % loss.data)\n", - " \n", - " if loss.item() < 200:\n", - " break\n", - " \n", - " # Save outputs to create a GIF. \n", - " if i % 10 == 0:\n", - " R = look_at_rotation(model.camera_position[None, :], device=model.device)\n", - " T = -torch.bmm(R.transpose(1, 2), model.camera_position[None, :, None])[:, :, 0] # (1, 3)\n", - " image = phong_renderer(meshes_world=model.meshes.clone(), R=R, T=T)\n", - " image = image[0, ..., :3].detach().squeeze().cpu().numpy()\n", - " image = img_as_ubyte(image)\n", - " writer.append_data(image)\n", - " \n", - " plt.figure()\n", - " plt.imshow(image[..., :3])\n", - " plt.title(\"iter: %d, loss: %0.2f\" % (i, loss.data))\n", - " plt.grid(\"off\")\n", - " plt.axis(\"off\")\n", - " \n", - "writer.close()" - ] - } - ], - "metadata": { - "bento_stylesheets": { - "bento/extensions/flow/main.css": true, - "bento/extensions/kernel_selector/main.css": true, - "bento/extensions/kernel_ui/main.css": true, - "bento/extensions/new_kernel/main.css": true, - "bento/extensions/system_usage/main.css": true, - "bento/extensions/theme/main.css": true - }, - "kernelspec": { - "display_name": "pytorch3d (local)", - "language": "python", - "name": "pytorch3d_local" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.5+" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/files/camera_position_optimization_with_differentiable_rendering.py b/files/camera_position_optimization_with_differentiable_rendering.py deleted file mode 100644 index 6172fb4b..00000000 --- a/files/camera_position_optimization_with_differentiable_rendering.py +++ /dev/null @@ -1,280 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[5]: - - -# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. - - -# # Camera position optimization using differentiable rendering -# -# In this tutorial we will learn the [x, y, z] position of a camera given a reference image using differentiable rendering. -# -# We will first initialize a renderer with a starting position for the camera. We will then use this to generate an image, compute a loss with the reference image, and finally backpropagate through the entire pipeline to update the position of the camera. -# -# This tutorial shows how to: -# - load a mesh from an `.obj` file -# - initialize a `Camera`, `Shader` and `Renderer`, -# - render a mesh -# - set up an optimization loop with a loss function and optimizer -# - -# ## Set up and imports - -# In[5]: - - -import os -import torch -import numpy as np -from tqdm import tqdm_notebook -import imageio -import torch.nn as nn -import torch.nn.functional as F -import matplotlib.pyplot as plt -from skimage import img_as_ubyte - -# io utils -from pytorch3d.io import load_obj - -# datastructures -from pytorch3d.structures import Meshes, Textures - -# 3D transformations functions -from pytorch3d.transforms import Rotate, Translate - -# rendering components -from pytorch3d.renderer import ( - OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, - RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams, - SilhouetteShader, PhongShader, PointLights -) - - -# ### Load the Obj -# -# We will load an obj file and create a **Meshes** object. **Meshes** is a unique datastructure provided in PyTorch3d for working with **batches of meshes of different sizes**. It has several useful class methods which are used in the rendering pipeline. - -# In[6]: - - -# Set the cuda device -device = torch.device("cuda:0") -torch.cuda.set_device(device) - -# Load the obj and ignore the textures and materials. -verts, faces_idx, _ = load_obj("./data/teapot.obj") -faces = faces_idx.verts_idx - -# Initialize each vertex to be white in color. -verts_rgb = torch.ones_like(verts)[None] # (1, V, 3) -textures = Textures(verts_rgb=verts_rgb.to(device)) - -# Create a Meshes object for the teapot. Here we have only one mesh in the batch. -teapot_mesh = Meshes( - verts=[verts.to(device)], - faces=[faces.to(device)], - textures=textures -) - - -# -# -# ## Optimization setup - -# ### Create a renderer -# -# A **renderer** in PyTorch3d is composed of a **rasterizer** and a **shader** which each have a number of subcomponents such as a **camera** (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest. -# -# For optimizing the camera position we will use a renderer which produces a **silhouette** of the object only and does not apply any **lighting** or **shading**. We will also initialize another renderer which applies full **phong shading** and use this for visualizing the outputs. - -# In[7]: - - -# Initialize an OpenGL perspective camera. -cameras = OpenGLPerspectiveCameras(device=device) - -# To blend the 100 faces we set a few parameters which control the opacity and the sharpness of -# edges. Refer to blending.py for more details. -blend_params = BlendParams(sigma=1e-4, gamma=1e-4) - -# Define the settings for rasterization and shading. Here we set the output image to be of size -# 256x256. To form the blended image we use 100 faces for each pixel. Refer to rasterize_meshes.py -# for an explanation of this parameter. -raster_settings = RasterizationSettings( - image_size=256, - blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, - faces_per_pixel=100, - bin_size=0 -) - -# Create a silhouette mesh renderer by composing a rasterizer and a shader. -silhouette_renderer = MeshRenderer( - rasterizer=MeshRasterizer( - cameras=cameras, - raster_settings=raster_settings - ), - shader=SilhouetteShader(blend_params=blend_params) -) - - -# We will also create a phong renderer. This is simpler and only needs to render one face per pixel. -raster_settings = RasterizationSettings( - image_size=256, - blur_radius=0.0, - faces_per_pixel=1, - bin_size=0 -) -# We can add a point light in front of the object. -lights = PointLights(device=device, location=((2.0, 2.0, -2.0),)) -phong_renderer = MeshRenderer( - rasterizer=MeshRasterizer( - cameras=cameras, - raster_settings=raster_settings - ), - shader=PhongShader(device=device, lights=lights) -) - - -# ### Create a reference image -# -# We will first position the teapot and generate an image. We use helper functions to rotate the teapot to a desired viewpoint. Then we can use the renderers to produce an image. Here we will use both renderers and visualize the silhouette and full shaded image. - -# In[8]: - - -# Select the viewpoint using spherical angles -distance = 3 # distance from camera to the object -elevation = 40.0 # angle of elevation in degrees -azimuth = 10.0 # angle of azimuth rotation in degrees - -# Get the position of the camera based on the spherical angles -R, T = look_at_view_transform(distance, elevation, azimuth, device=device) - -# Render the teapot providing the values of R and T. -silhouete = silhouette_renderer(meshes_world=teapot_mesh, R=R, T=T) -image_ref = phong_renderer(meshes_world=teapot_mesh, R=R, T=T) - -silhouete = silhouete.cpu().numpy() -image_ref = image_ref.cpu().numpy() - -plt.figure(figsize=(10, 10)) -plt.subplot(1, 2, 1) -plt.imshow(silhouete.squeeze()[..., 3]) # only plot the alpha channel of the RGBA image -plt.grid("off") -plt.subplot(1, 2, 2) -plt.imshow(image_ref.squeeze()) -plt.grid("off") - - -# ### Set up a basic model -# -# Here we create a simple model class and initialize a parameter for the camera position. - -# In[10]: - - -class Model(nn.Module): - def __init__(self, meshes, renderer, image_ref): - super().__init__() - self.meshes = meshes - self.device = meshes.device - self.renderer = renderer - - # Get the silhouette of the reference RGB image by finding all the non zero values. - image_ref = torch.from_numpy((image_ref[..., :3].max(-1) != 0).astype(np.float32)) - self.register_buffer('image_ref', image_ref) - - # Create an optimizable parameter for the x, y, z position of the camera. - self.camera_position = nn.Parameter( - torch.from_numpy(np.array([3.0, 6.9, -2.5], dtype=np.float32)).to(meshes.device)) - - def forward(self): - - # Render the image using the updated camera position. Based on the new position of the - # camer we calculate the rotation and translation matrices - R = look_at_rotation(self.camera_position[None, :], device=self.device) # (1, 3, 3) - T = -torch.bmm(R.transpose(1, 2), self.camera_position[None, :, None])[:, :, 0] # (1, 3) - - image = self.renderer(meshes_world=self.meshes.clone(), R=R, T=T) - - # Calculate the silhouette loss - loss = torch.sum((image[..., 3] - self.image_ref) ** 2) - return loss, image - - - -# ## Initialize the model and optimizer -# -# Now we can create an instance of the **model** above and set up an **optimizer** for the camera position parameter. - -# In[11]: - - -# We will save images periodically and compose them into a GIF. -filename_output = "./teapot_optimization_demo.gif" -writer = imageio.get_writer(filename_output, mode='I', duration=0.3) - -# Initialize a model using the renderer, mesh and reference image -model = Model(meshes=teapot_mesh, renderer=silhouette_renderer, image_ref=image_ref).to(device) - -# Create an optimizer. Here we are using Adam and we pass in the parameters of the model -optimizer = torch.optim.Adam(model.parameters(), lr=0.05) - - -# ## Visualise the starting position and the reference position - -# In[12]: - - -plt.figure(figsize=(10, 10)) - -_, image_init = model() -plt.subplot(1, 2, 1) -plt.imshow(image_init.detach().squeeze().cpu().numpy()[..., 3]) -plt.grid("off") -plt.title("Starting position") - -plt.subplot(1, 2, 2) -plt.imshow(model.image_ref.cpu().numpy().squeeze()) -plt.grid("off") -plt.title("Reference silhouette") - - -# ## Run the optimization -# -# We run several iterations of the forward and backward pass and save outputs every 10 iterations. When this has finished take a look at `./teapot_optimization_demo.gif` for a cool gif of the optimization process! - -# In[13]: - - -loop = tqdm_notebook(range(200)) -for i in loop: - optimizer.zero_grad() - loss, _ = model() - loss.backward() - optimizer.step() - - loop.set_description('Optimizing (loss %.4f)' % loss.data) - - if loss.item() < 200: - break - - # Save outputs to create a GIF. - if i % 10 == 0: - R = look_at_rotation(model.camera_position[None, :], device=model.device) - T = -torch.bmm(R.transpose(1, 2), model.camera_position[None, :, None])[:, :, 0] # (1, 3) - image = phong_renderer(meshes_world=model.meshes.clone(), R=R, T=T) - image = image[0, ..., :3].detach().squeeze().cpu().numpy() - image = img_as_ubyte(image) - writer.append_data(image) - - plt.figure() - plt.imshow(image[..., :3]) - plt.title("iter: %d, loss: %0.2f" % (i, loss.data)) - plt.grid("off") - plt.axis("off") - -writer.close() - diff --git a/files/deform_source_mesh_to_target_mesh.ipynb b/files/deform_source_mesh_to_target_mesh.ipynb deleted file mode 100644 index c93a07c9..00000000 --- a/files/deform_source_mesh_to_target_mesh.ipynb +++ /dev/null @@ -1,2149 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Deform a source mesh to form a target mesh using 3D loss functions" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "colab_type": "text", - "collapsed": true, - "id": "HfwwW9HqtuvQ" - }, - "source": [ - "In this tutorial, we learn to deform an initial generic shape (e.g. sphere) to fit a target shape.\n", - "\n", - "We will cover: \n", - "\n", - "- How to **load a mesh** from an `.obj` file\n", - "- How to use the PyTorch3d **Meshes** datastructure\n", - "- How to use 4 different PyTorch3d **mesh loss functions**\n", - "- How to set up an **optimization loop**\n", - "\n", - "\n", - "Starting from a sphere mesh, we learn the offset to each vertex in the mesh such that\n", - "the predicted mesh is closer to the target mesh at each optimization step. To achieve this we minimize:\n", - "\n", - "+ `chamfer_distance`, the distance between the predicted (deformed) and target mesh, defined as the chamfer distance between the set of pointclouds resulting from **differentiably sampling points** from their surfaces. \n", - "\n", - "However, solely minimizing the chamfer distance between the predicted and the target mesh will lead to a non-smooth shape (verify this by setting `w_chamfer=1.0` and all other weights to `0.0`). \n", - "\n", - "We enforce smoothness by adding **shape regularizers** to the objective. Namely, we add:\n", - "\n", - "+ `mesh_edge_length`, which minimizes the length of the edges in the predicted mesh.\n", - "+ `mesh_normal_consistency`, which enforces consistency across the normals of neighboring faces.\n", - "+ `mesh_laplacian_smoothing`, which is the laplacian regularizer." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 0. Import modules" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "colab": {}, - "colab_type": "code", - "collapsed": true, - "id": "ylbZGXYBtuvB" - }, - "outputs": [], - "source": [ - "import os\n", - "import torch\n", - "from pytorch3d.io import load_obj, save_obj\n", - "from pytorch3d.structures import Meshes\n", - "from pytorch3d.utils import ico_sphere\n", - "from pytorch3d.ops import sample_points_from_meshes\n", - "from pytorch3d.loss import (\n", - " chamfer_distance, \n", - " mesh_edge_loss, \n", - " mesh_laplacian_smoothing, \n", - " mesh_normal_consistency,\n", - ")\n", - "import numpy as np\n", - "from tqdm import tqdm_notebook\n", - "%matplotlib notebook \n", - "from mpl_toolkits.mplot3d import Axes3D\n", - "import matplotlib.pyplot as plt\n", - "import matplotlib as mpl\n", - "mpl.rcParams['savefig.dpi'] = 80\n", - "mpl.rcParams['figure.dpi'] = 80\n", - "\n", - "# Set the device\n", - "device = torch.device(\"cuda:0\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load an obj file and create a Meshes object" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "colab": {}, - "colab_type": "code", - "collapsed": true, - "id": "dz0imH-ltuvS" - }, - "outputs": [], - "source": [ - "# The path to the target 3D model we wish to fit\n", - "# e.g. download https://free3d.com/3d-model/-dolphin-v1--12175.html and save in ./data/dolphin\n", - "trg_obj = os.path.join('./data/doplhin', '10014_dolphin_v2_max2011_it2.obj')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "colab": {}, - "colab_type": "code", - "id": "rbyRhI8ituvW" - }, - "outputs": [], - "source": [ - "# We read the target 3D model using load_obj\n", - "verts, faces, aux = load_obj(trg_obj)\n", - "\n", - "# verts is a FloatTensor of shape (V, 3) where V is the number of vertices in the mesh\n", - "# faces is an object which contains the following LongTensors: verts_idx, normals_idx and textures_idx\n", - "# For this tutorial, normals and textures are ignored.\n", - "faces_idx = faces.verts_idx.to(device)\n", - "verts = verts.to(device)\n", - "\n", - "# We scale normalize and center the target mesh to fit in a sphere of radius 1 centered at (0,0,0). \n", - "# (scale, center) will be used to bring the predicted mesh to its original center and scale\n", - "# Note that normalizing the target mesh, speeds up the optimization but is not necessary!\n", - "center = verts.mean(0)\n", - "verts = verts - center\n", - "scale = max(verts.abs().max(0)[0])\n", - "verts = verts / scale\n", - "\n", - "# We construct a Meshes structure for the target mesh\n", - "trg_mesh = Meshes(verts=[verts], faces=[faces_idx])" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# We initialize the source shape to be a sphere of radius 1\n", - "src_mesh = ico_sphere(4, device)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Visualize the source and target meshes" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "def plot_pointcloud(mesh, title=\"\"):\n", - " verts = mesh.verts_packed()\n", - " faces = mesh.faces_packed()\n", - " x, y, z = verts.clone().detach().cpu().unbind(1) \n", - " fig = plt.figure(figsize=(5, 5))\n", - " ax = Axes3D(fig)\n", - " ax.scatter3D(x, z, -y)\n", - " ax.set_xlabel('x')\n", - " ax.set_ylabel('z')\n", - " ax.set_zlabel('y')\n", - " ax.set_title(title)\n", - " plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "window.mpl = {};\n", - "\n", - "\n", - "mpl.get_websocket_type = function() {\n", - " if (typeof(WebSocket) !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof(MozWebSocket) !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert('Your browser does not have WebSocket support.' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.');\n", - " };\n", - "}\n", - "\n", - "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = (this.ws.binaryType != undefined);\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById(\"mpl-warnings\");\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent = (\n", - " \"This browser does not support binary websocket messages. \" +\n", - " \"Performance may be slow.\");\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = $('
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')\n", - " nav_element.attr('style', 'width: 100%');\n", - " this.root.append(nav_element);\n", - "\n", - " // Define a callback function for later on.\n", - " function toolbar_event(event) {\n", - " return fig.toolbar_button_onclick(event['data']);\n", - " }\n", - " function toolbar_mouse_event(event) {\n", - " return fig.toolbar_button_onmouseover(event['data']);\n", - " }\n", - "\n", - " for(var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " // put a spacer in here.\n", - " continue;\n", - " }\n", - " var button = $('');\n", - " button.click(method_name, toolbar_event);\n", - " button.mouseover(tooltip, toolbar_mouse_event);\n", - " nav_element.append(button);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = $('');\n", - " nav_element.append(status_bar);\n", - " this.message = status_bar[0];\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = $('
');\n", - " var button = $('');\n", - " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", - " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", - " buttongrp.append(button);\n", - " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", - " titlebar.prepend(buttongrp);\n", - "}\n", - "\n", - "mpl.figure.prototype._root_extra_style = function(el){\n", - " var fig = this\n", - " el.on(\"remove\", function(){\n", - "\tfig.close_ws(fig, {});\n", - " });\n", - "}\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function(el){\n", - " // this is important to make the div 'focusable\n", - " el.attr('tabindex', 0)\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " }\n", - " else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "\n", - "}\n", - "\n", - "mpl.figure.prototype._key_event_extra = function(event, name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager)\n", - " manager = IPython.keyboard_manager;\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which == 13) {\n", - " this.canvas_div.blur();\n", - " event.shiftKey = false;\n", - " // Send a \"J\" for go to next cell\n", - " event.which = 74;\n", - " event.keyCode = 74;\n", - " manager.command_mode();\n", - " manager.handle_keydown(event);\n", - " }\n", - "}\n", - "\n", - "mpl.figure.prototype.handle_save = function(fig, msg) {\n", - " fig.ondownload(fig, null);\n", - "}\n", - "\n", - "\n", - "mpl.find_output_cell = function(html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] == html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "}\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel != null) {\n", - " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": { - "bento_obj_id": "139741805306320" - }, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": { - "bento_obj_id": "139740023070416" - }, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib notebook\n", - "plot_pointcloud(trg_mesh, \"Target mesh\")\n", - "plot_pointcloud(src_mesh, \"Source mesh\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Optimization loop " - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "colab": {}, - "colab_type": "code", - "collapsed": true, - "id": "Sc-3M17Ltuvh" - }, - "outputs": [], - "source": [ - "# We will learn to deform the source mesh by offsetting its vertices\n", - "# The shape of the derform parameters is equal to the total number of vertices in src_mesh\n", - "deform_verts = torch.full(src_mesh.verts_packed().shape, 0.0, device=device, requires_grad=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "colab": {}, - "colab_type": "code", - "collapsed": true, - "id": "0BtSUfMYtuvl" - }, - "outputs": [], - "source": [ - "# The optimizer\n", - "optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "colab": {}, - "colab_type": "code", - "id": "9DAjqI9Atuvp", - "scrolled": false - }, - "outputs": [ - { - "data": { - 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xe3XiwWCQo0ePNnWMtY7Z6HZet9+dh3mWcgYn97SRKhj8/J9cZSqto8jw2ddm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\n7Naaj4yMYHBwEHfddRcWLFiA7u5u5Ofno6WlxeWF3dp06MDAAF555RX89re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vVkzn5+e5ceMGJ06coL29HdM0a4tfi9vNPQ/1VCq15l2Il0ezfL1vhr97fZKy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lpUdZtkWOXV0SKqLKAJ/j1wr6Tz0WO9lJs2YU1i4uZs55j5msmFqTKu55GvmSQWKBgKCB05AoCy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\nTebDR7oQBT9It02m3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bs65/rmeIlPnOrnvfvTnBsp4HrQE1V5cm+CumlzN1snEVYQENiR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FahbJlQ003cKyTKz0PB/40jJzSYemqUgCuulkokZ8MqIIqZKGapj4ZKkazBHhT+8b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\nComow8+YgD/+8Y/Yvn07cnNz8fzzz2N0dNT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IdM0NxVpC1LNlajTuasmEimnzH75xmy9eGOeFH9/LM0/0rftYbmUgcSsuKNFo\nlBMnTvDss8+yf/9+crncmm6ZTCbDgQMH6o9jsRiZTOY+Yf/Wt77FRz/60frjoaEhXnzxRRzH4Rd+\n4RfYv39/W/v82Ap7LVI+OzvLrl27WvrBtDuyTgjBK6+8Qm9vL0eOHGl6zY2wVGrB2eXuEDar4KjW\nr72/v59yubzqdkutpKVzTUOhUF3oQ6HQhp/gN2eL/N537lAwbIbnCpTM6vFYsowCRPwKbzuQYDJr\nMpEpk6tYOMK1ygOawsEdEd6YyHG0N8JUzmA2Z5KM+LEdQdEUmLZCX8zHUzsjDM+XCWhgOHCgO4ym\nwvBciaLpEPFpGLYkoGvoioKJq/ruJcQNpioKhHQoW26QdSlONfg6X3b4998a4/1T4+yMB+vHsp1Y\nx1b52LeSxhz6WGz1HvksE9dZ7hy+efMmu3btqov9oUOHiMVinD59mhs3bvCf/tN/4rd+67fa2t/H\nUthrVqNhGMzNzTU17LkRTdMwDKOJV77JzMwMpVKJ8+fPL5oHuhatTjdaSi0vPpvNrniHsNFZLlJK\nRkdHmZ+f58yZM5TLZUqlUkv73dhOV0pZn2s6PDxcT1ertdNd712PlJLf/PptprJlpFTIV2wq9ptV\noDVqWSrRoI/eeIjeeIh8xUJX3cT0eFCnUCyRq9js7QozmTEYSASZyhgIIejqCNApJAe7wwR8GtmK\nYCZvIhUF0xZ0BHWe2hklGQ5w4U4Gv08jGlJJhHQmsxX2d4XJGw6W7aZG6pqCX5WYjvud6IpEU99s\nRVD7hhwJ2bJASIXvZDv50PGd+OzSomKextbEawn9o9S+dqNo9RxMJpNkMpn643Q6fd95f/HiRU6c\nOFF/XBvvCHDkyBGy2Wzbd0ePnbA3jqzTdb0ty7sVi702yNowDCKRSEuizjqF3TAMLl++TCKRWDU4\nu5HC3tg07OzZs6iqSrlcbnnfl64XDocJh8MMDAzc12WxNu4umUwSj8dbPlZ//sYMowtF8oZDxXwz\n62TpN1yrGD28I4ymKtxNl0mXLUxbYjsSwxKEVdeVEtAV9iYDXBjPYjsOQkgO9UYYSITQVYULYxlS\nJcvNb1cUdFXh9myB/niQzrCGIyWpoklAV3EcgSMk01kDR0iEdF1B8YCKEA6mA2rVXeM49wdha58l\nW3H46tVZJjNl/sWPHuDUkzsXFfM0XjRXy/F+1HK6N4JaA7JmOXnyJF/84hd517vexejo6LKFUbdv\n3+Ztb3tb/fFf/uVf0tXVxdvf/nbGx8fXNdHrsRH25XLT2yk0ogVhLxaLXL58mV27dnHs2DG+//3v\nb9paS6l1gzxy5Ei9kdJqa7TRZuoPAAAgAElEQVRyHFYS9nw+z+DgIPv372fnzp1rvr5dlnZZrHUC\nnJ+f5/bt2+i6XnfrNLPu1ak8Eb/O7Aq9WWr4NQVdhYWiTbFiMzJfQlNVHOmgqAqZsk0w6FrNRcNh\ndKFEpmSjKJAumUQCFfZ1ubfd/YkAM3kDW7jFS5rm+sxfG89wJ1WpX1RsU1A2TXqiPjJld/98uoJp\nS6IhH+miwHIEPk1Zc5iHghtwHZ4t8etfG+YL/9tpNHVxMU/tolnrvb9cUPtxFPZW0x2PHDnCgQMH\neOGFF1AUhQ9+8IO89NJLhMNhzp8/D1UrvtGt8/a3v51PfepTfP3rX0cIwS/+4i+2vb+PhbCvlJve\nTnZLs9tNT08zOjrKk08+STz+Zpl3q7exrQY2pZQYhsHw8DBnzpxpKtq+ERb71NQUY2NjPP3003R0\ndKzr/VtlaSdAwzBIpVJ1V8O1a9fo6uoikUgQDAbvG1RhCYGqKCjLVHYqDZa6rio8u6+TvOlgCUmh\nYuPTFDpDOhVLoCmSvoggHnLFL1u2UVV3Lb+uMl8w3SwZR9IZ8rOjw8/IQgkV0DSVfT0RxlLluqjX\n9lKpNhRzhMQWbk8avepy8WuKm0dfzZSR8s1GY2KFzyOQLBRNLoylecuB5KLnGy+a+/btW5T6NzY2\nVj92iqLQ1dX1wAR+qwvc2rlrfu655xY93rdv36LHv/3bv73ocVdXFx/72MfWsZdvsu2FfbXc9Hat\n4dW2cxyHoaEhbNu+r5KzJnCtCHsrgc3aIA4pZd0N0uwa7Qq7EILr169jmuaKlasPuvI0EAiwc+dO\ndu7cycWLFxkYGOD/uTDBGxNjCCk4PxDhJ5/ayVRF499/4w4zeQPTFstau/VGXQo8uSuKLSRCSOIh\nnR1RPzdmSyTDOroGtlCIBVUUFMZSFUzboaa4QV1DV2AiXWZ3MkSx4nB+X4LeWJDb80VUVeHIjgij\n86VFPWGo+sgXShaW4/rVowGdsuXgCMmeuA9LmJRtBSFdZddU3P9GEvFrlCwHW7z5fgVDUDAEv/63\nw3z8p49wevfK/WWWBrUty2JoaIhsNsvFixfx+XyL2uduZpvkrfTre5WnDwnN5Ka3+0NZqQlYoVBg\ncHCQgYEBBgbuH0BcuyC0YuU0e/GpzUA9dOgQhmG0vEY7wl6pVHjjjTfo7e3l2LFjG+bD3ygcIfnr\nEZPRq2NMZA32JjtQpOQL14p8a2yE2ykbu2rhqopCUHfzxpemN2pA2K8xMl9kZzzIsd4OfJrKW/Yn\nyFZMKpYrpk/tjBJV8gCc2BXFEYLJjIHlOIDk1O44+7oi3MsZXJvOkzecempjPKjj11Uifp1ixaax\nw0DN+laqn0kCnSEfqqKQNwSxoI8f3tPJ5ck8hbLFQskm7NfedNGsMEN9Il3hcy9PcLS3g7C/OdHy\n+XyEQiG6u7tJJBL1u6OJiQny+Xy9q+JGZy9ttfvHE/aHgHZy01thOZ/05OQkd+7cWbWJ1mb0mJFS\nMj4+zvT0dH0G6vDwcEtrtJPuaBgGFy9e5NixY3VrbrXXbwX//Y0ZhjOCgnSDl2MLbmaOqqpkTNff\nXMsDt4VEVSGggy5AUVTs6jFxBVejYDioEkzb/XumZNEZDnB+byfzeYM76QrVTERMW7C/K8yhHRFK\npoMjBAMJ178e8mtMZAyiQR0FSJVMgj6Va9MFchULUQ2+1vqzF0zpVrRqoKkKybDG8Z1RRubK7Ao7\nXJ23+daNBRQUbCFIhHRCAY1M0SJXtrHk8sM9HAk37xXIlq2mhZ0l6Y6Nd0fLBWJr1cXNNttaia0W\n1q1ev1W2nbDXrPTNvHVrFFvbthkaGkJKuWYTrY0Wdtu2uXLlCn6/n/Pnzy+yaFr5/K1Y1LULSalU\n4m1ve1vTFXO192/HHdUOFcvh1fEspiPoCKpkym6JvqK44qgqSr0jo10VPkXCnkSIuYKB7Qgc4T7v\nCEHJdPBpCk8PxBicyjOZqVC2BGf3xlEViIV9BPIGuYqkaNrMF0z6E0H8mko0KHllNE1/p2vBlk2b\nkE/FsAUg8WsqliMpGhYhv4blSCJ+lYotMaouIqfW2lFKiqbgymSBnfEAQV1QshwcqRANalRMScWW\nBP3gIFFVBbWaSXP/d+IWZSXCvpaO7Up9lJbrqljLXmoMxNZcN61UFzfmkW8FW33H0CrbRtiXBkg3\nUzhqwdNaFsiePXvo7+9fc82NFPZcLseVK1fuy0ChjRTJZoXdsiwGBwcJBAJEo9GmRX3p+2/EdyOk\nZCpbQQh49U6G6ZzBnkSQnz7RS8l0+L++Nsy16TyzOYmvVKFiOTgCIgGNXbEAU5lKvRS/moZOIqzT\n1RGgaAo3FVFxlV1TQMOhN6iQzaRJ5W0Cfh1Hwg9G065YWwLTFvQHHToCOvmKjb9awu9TFQYSIUqm\nu2LYr6NpKj4kKCrZssXBnghjqRJutxkABaeaMaM2tAn2+zR+8vgOhueKzOVNtKBDh0/jXtGmYppI\nJNGgTkegNqhD4NdVDOv+GIIESqbDR758g//wD443f+yb7O6oKEq92dbSQOz4+DhAvdnWWmmqWy2s\nnsW+BTiOw61bt9i3b19botFOQLNUKnHlypVls0BWYqMGTU9MTHD37t0V127Vp93MftUuYgcOHKC7\nu7ulASAb7WO3HMF//J+jjC6UGU+VkVKyryvEt4dTXJrIsS8ZomA47O8OM58vV7NTQFdVKrZgPF0m\noClE/QpWNb75dH+MjoDG9ZkCkYCOlCa66vq/K7ZE1RR++NhOXh5NUTRtdCw0FcYyEA3qBP06hiOY\nKLhumNm8gQT640G3ZkJTCOiuZV4ybd5xoJPLUwUcIQnpKtGgRsSvY9iuW8SyHQK6StmyiQQ0grpK\n2XYI6W7Ky75kiPmCSdEUFEynOphDxbQl+YqNE3UzZkoWiOXM9SqqAm9M5CgYNh2B5uSg3crT5QKx\ny6WpLheI9YS9NR5pYW8MkE5NTbXVV6FV14Bt2/Xbyre97W0tfdntTF5q9H87jsO1a9fqbp+V1m71\nArKW8C5NZawVeLXy/hvF391O8YVXpxhZKLG/K4xhCwzL4fJUDr+m8Z3bKe6kQ0T9GrmKQ8WdZogU\nrmtCSImUEPH5SIT9zBYsbCG4ca+AkHCoJ0zIp5EtW5QsgS3cdEJFgVfv5rCFQnc0RCLiRwjBTDGP\n4zgYFRtdUXAkFCsmJ3bFmMiUMWy3aZdfU9E1lZJlc3u+RNl06IsFeaI7jOWI+kQmZ1ZQNKCnw89b\n9nfy11dnyZQs19qXEA3obiGUX2NXPEAmb+HTqimRKvg0FSEFuYqF4bguGHsVYXefkm7coEkX+Ea5\n0nw+Hz09PfT09EBDmurExASFQqHeRiKRSGypK0YIseVZOa3ySAu74zj1rJf1ZLg0+6OpuT/27t1L\nqVRq+Qq+nslLtYyb3bt3MzAw0NQ2zbKSsK+UyriZTcMAchWb74+kCegKJwdifGVwlootSIZ1vnUz\nxb28QcVyuDFbBCkpW67/21ElpiWYzRk4HQEm0+Xq+tUJRNWMEseB2aJFT4ffNQ4EGLZrVc8XLTpD\n7klsOwKfT3MDrIprbe+IBRhPlSlbDrYQ+HSNSEBDVRXSRZOoLqnk0yzMmZhqgJLu4Kh+Sqbr80+X\nTMqW4wq9qjBXNDjdH0dR3DuKguFQthw6gjqKquLXFIzqT0bFHeJxczZPUNdRFdgT96FoPnIzJXyq\nSjygkqvY5CrOfQ3ClsORsDMWaMnPvlnW89JAbK2NxMjICPl8HlVVmZ6e3tQ2z8tRs9Y9YX+ArPd2\nrSbsPt/KP2wpJXfv3mVycpKTJ08SiUS4c+dOy/varitmYWGB27dv89RTTzXVgGgjXDG1TpDLpTK2\n2499Le4slLgyneer12ZRFRXLEXzyW6M80RNBCMGFO1l8moqm4gYby4Y7PUhA2ZYohqAj4IpjT4cg\nEtDwo5AxIGe604w0xXU/WBIM2/UVR/wKuqbSGdQpWQ6JkE7Er5GvWDhSoikQ0BRCPpWjvR0oimv1\nW7bgxLEocwWLuYKBAuz0V0h276CcqbC/Q8WsVCjlcnxnwsKvq9iOgopbXGQ4Ak1VSZVM9iTD/M+b\nKRwpMWxJtmzz8kiae4U3cxVr31Ch4nBod5RX72YJRBwO90SZLzrkDYdI0M2vn8wa1TiBgsrywdMa\nBdNhrmCyI9qcWD4I63VpG4n5+XlmZ2cxTfO+QGxnZ+eq5+962Wo3UDs88sJeo+bmaPULWEtsa71P\napkn6/GztSrsQghmZ2ebyrhZzzpLhbrWlXG1XvEbYbGPLpS4dDdHf2eAdNHk8y9PMpWtYAnBoZ4O\ngj6V+aJJrmyTN2wcIdFUh0TYT9GwMIU7M1SrWeRAxRIkq9bnzngQ1bBIJBL8z5spDNvBr7v53Zpw\nc8819c1B0kXLwXEktnAzVfYmQqTKFh0+lVBApyfqJ+TXCOg6jiMIBlWEhGcG3IvtWKpEOW3h1zV8\nmkpHJAyRMMmuJFezMxQqNkLYWLZEKiBsC7/fz3i6THeHH0sINFXBrys4UjBfqOA49x+3gE9DUSBf\ntrhasnlrh+DZAwlmsgYBXWWhUCEe9pEquSm/q4m6qsBUtsIPxjK850RvU9/nVgidlJJQKMTevXvr\nbZ5zuVy9wlhKWXfbtNMvaDU8YX/ALNceoNUBDau1B8hms1y5coUDBw7cl3nSDq2Orbt8+TLBYJBk\nMtnS52q3klRKycjICAsLC6uO6WvVWmvcn69eneHVsTQLRYtM2SSgadyaLbBQttBV1e05bkuGZvL0\nRf0UKg6q6rwpThKyFRNTVF0sSw6nxM1uuZsxSYYFY/M2nfksXRGddNnN8/ZpKtGAQtinU7EsDEsg\npI0QGj5Vci9nEAv5KJkOhi0oGg5q0eLJvih3UmVSRZMjvR0kwj5eHk3TEdCQUiFVsNjhd4OkedNm\nPF1mTyKEkJJY0EfBFHQE/fXmXpqqElFNTNNi8p6JJiWGg9v4S0gs5/7ccxXYFQ/wvZE0jpAUTMG3\nR7I80R3miR0RTAeG54r0RP3M+FTyxtq/NyHdgqdm2Qp/81Jx1TStLuRUY1/pdHpRILaxn/969tcT\n9i1kPX1floqtlJI7d+4wMzNTL/rZCJoV9tp0pSeffJJCobDhRU1LURQFx3G4dOkS4XC4pXYEqyGl\n5PWJLPcyJSbvmfzeH73G0EzezfYwbFCo+qrBFqAprq+81nZ2LO22RlaqIi6rrpSKVXv/JZ+72s/l\nTqpCZ8hHpmzT4XOnGOVtgV4ttbccQV88goJ0+577VWJBnemcid+nUzQcRNkiX3EI+d0xd2G/xrdv\npzjcE2ZfV4jemHvR2xnzU7EEPlXhQHeIQiqHlJJjOzqYTJcoGO7Q6r64n6LlkClZxEI6h7rDHN8V\nI+zXKZk2ijApiRx3FspUTOgI6uQc6c49FZLa1xnQFb4znEJVFQKaSkB30yNvz5fpi4eIhXSCPo25\nvIEjwAesUHgKVVHfGQvwQwean+K1FUK31pq6rt8XiK3NMC0UCnUDKZFIEA6HWxL6Ry0jBk/Y7w9o\nmqbJlStXCIVC9xX9rJdmxtbdunWLQqFQ751eLBbbyqRpxWIvlUosLCzw1FNP0de3/vmYN2dyXLyT\n4dZckclMhWvTeVIlEynLaKpCWYWS9eb+1Y6wkFBZZlyRAyRDPkqmjWnLerOrpXQEVPriATJlh7It\nyZQtAorEEQ4Rv5tO2N8Z5NZcEb+mMDJfQUgJUiVXcatDbaHi9u1yM2j0ahMvwxboqkJn2M9MzmCg\nM8RcwWQ6Z/JDByKYjuC18RxhR/D6lXvkKzY+TeVHDulkKw6358p0Rfx0hf2YjsCnq9iOwLBsdE1F\nqgF0fwihu0VLfTE/mdkSQU1iSrCUWjFVtTWvDdIHQVVBqRZc3U2XeToS4+iOCF+/MUfFcrNtlmtu\nVkMBfuRgAk1tXugeBot9LQKBAH19ffT19d0XiC2VSvXWxM0EYre6OKodHmlh3+hOjbVWpQcPHqxP\nCl+Ndjo1riTSlUqlPtj69OnTi8bWbabFPjk5ydjYGLFYbF2iPpEqcWO2wCujaf7HlRkMR5ArO/Xq\nzlpJu+O4gyEaEdVpQEKsLEC6Cp1Bnbzptqk1G3zPfs1N89udDJOv2JQMm4otkBJsoCPgHktNVVgo\nmgR1DVDo6vAjhKRoOMwXTIQEy7Hwa65lr6mudR/2aVhC0hcLcrg3wtBMkdEFd8rSMwMxfJpr1ffF\n/HxvWBAMuIMwggoMThU52tdBrmKRjPhQUOo91X2aikRhKlPGEe4UJwX3LuZOxqQj6KdiO/h9MFdw\ne7cLV/dRFLCFoCQkPUE/R3d2MJmpkC/bTOUq1cHabuxhNTQF/vuVOX7xnQeabiuwVcLe7hzcpYHY\nWkVsOp1maGgI0zQXtSZeGoj1LPYtZD3Cbts2IyMjzM3Ncfr06fsa4i9HOwMwVkp3nJ+f58aNG8v2\nXWl3vupaFrsQgqGhISzL4uTJk9y4caOlNQBsRzA6X+TPL03xt1dnmS+ZdYt7aYfCte4fpMRNWVxm\nxqimwPG+Dn74YJL/+NIYhi0X9T7pCOi844kkIZ/Gd0dS9TF1AteFEQtoFEzBbK6CKSSqopIqmjy1\ns4P5kkWuYqGqChGfSqXqGkpGfPRGAyyULCqmze5EkLfsT1A0HdIlk96OAAqSdMkiXvVPZ8s2Uiyu\njTAdt3dLdySA7Ugk7rDqnmiAjqCOlLhVsMJtRAYQDbgXkr1JP3nDYTproCtVl5l0+72HfdAVVCgZ\ngicTAk1a7E8GKZo2V6bylBoGhqyGkGDbYtVc96VsRdrfRrp/Giti9+7d67ZYbqiIbQzExmKxtiz2\nz3/+89y6dQtFUfjABz7AwYMH6899+MMfXtTy+Jd/+ZdJJpOrbtMqj72wCyEYGRmhu7ubc+fONf0F\n1tZrVdhrLYSpWj63b98mnU6vGKzcDIu9XC7zxhtv0NfXx969e+utGJqlYjlcX7D4jd97mZGFklu9\nuYT7ZWL5rOra0Q7q0BWEmF/lysKb+6IAT+2K0tUR4OJEnkTY5zbjqjbISoR1Xvxfj/LsvgQf++ub\nrktBAZ+qIpHoUtAZ8ZPsgFuzJQK66gYyDYcr0wXiIfcUCPrczophv07BsOmJBshWbHYnQvg1qFgS\n2xF8/3aaguGwuzPE/p4wr4xmSITdgGg0oBHxK9S8GiXLqfvio0EN03HTJA1L0B932zEoCuxOhLiX\nNzAdUc/S0RQFTVW5my661rdS68uuoCAJ+v30JUKoVpGKEiSTqZD0FbieEtULSHNIIBHxEQ083Bbp\nZvr1a4PTGwOxtYrYz372s2SzWQ4dOkQkEuHAgQNrnvPXrl1jZmaGF198kYmJCT7zmc/w4osvLnrN\nRz7ykUUtOZrZphUea2GvVbnVhku3wnoF1zRNLl++TDwe5+zZsytaQRvVhqBG7e6gMZWxWZ+8YTn8\nzeA9PvmtYWby1hphuaUo9f9tXEnXFAYSQTJlm7IEw4Rz/QEWChUCqkRTVXZFFIRwCGgqQZ9GXzxA\noeJmrBg2FE23SK3Dr9MfD5Av29hSoikqqhT0Rv1kyo7r37cEUroDMnyayo5YwE1xlG7DrVrpv5QS\nR0j8GgR0jVgAvnL1HmXTTae8MJ7BEjH8PrfSE6A/EUItqYybPvy6gq6qPNETRgKndscJ+jQ382i+\nxFiqzMGeMEJIgrpKybCR1buVoK5yvK+DiXTF7Rkj3f4yZcshqCuULMlcwSRTMukLK/zEniiXJiEl\nA+h+E80wkI5Eq8Yn1uJf/mh7rTgeJA8yYNs4uOVf/at/xdDQECMjI3zjG99gZGSEf/gP/2F9CtJy\nDA4Ocu7cOQAGBgYoFouUSqVVkzDa2WbVz9DWVg8J7frYG9P62mlDQJvtAWrb1Hz5hw8frkfxV6Kd\nYqDl2vCulsq41hqm7fDFixN85tujzBfslvalRuNgaAU3f/zojjAnB+KMzpdZKJiUbHeS0ZxP41f+\nl+P0dwb49EujCGGRTmcwbAdhqUhHwbAFfk0hGtD48uVZuiMB3v+WAf7g78YpGA7Zis0TXWGmFjIk\nI350zebSuIMDCOmg29DdEcCnqIT8KpNZNwPHr6mE/Sq5skXEryOlgqbAXNFGCnfIRd50c+lfHc9y\nZEcH3RE/AV3l8mSeAZ/Ku57o4Y2JLP2dQZIRP7fmCsQCbraKoijsTYYwHUHRsAnoGt8dSSOlJOhT\nqVg2O6JBntwZ5W66QtCnYtpusNWvQa7yZuqn4cBEwQ3yRvyaK/YVm2I1MO0scyFdiq7CH/5gkr93\nZEdLAdQHzVamHMZiMU6dOsWRI0fcuoA1zvtMJsOBAwcWbZ/JZBaJ9H/+z/+Zubk5jh49ys///M83\ntU0rPNLC3kizwl4b8NzZ2cnZs2eZnZ2lVCq1vF477QEURSGVSpFKpVr25be6b41CbVkWly9fpqOj\nY9lUxpXWcIRkcDLLr/zZIBMZoymfbSOaAj4VUFR0BBXHLYiJh32cHIijKTCyUOb6vQKaSrV9rYNl\nC5IRH3uSYd71ZC/fG8kQCkfY3Rng5ZEFZmZL2I7rP98RVlCkw+sTWd7/lt386rueoGDYxIMaqqry\nu195hXuGzZXpAj5dIaAqCAHxkI6iSK7fy2NUh1EHdJUDPWEKFZt4yIeUkrBfpVTNLgn5NXyaQqUk\nKFUsdF11i5MUhWjQx55EiGIqS9lw2xX0VCs5D3RFuDyRo7vDfZwqmfh1Db+mMjSTJ1+xiQbdUzGg\na8zlLRwhOdwT5gdjWfy6gu1IeuNB5oqFxd9RNePlSG8HqWKKfNleJOaq8ma+/7JDriXcTZUZmc1z\nqG/tquatYisDmEKIekBVUZQ192OpkbQ02PyP/tE/4plnnqGjo4Pf/M3f5Ac/+MGa27TKthJ20zRX\nfU3NDdE44HmzB1rXsCyL27dvY9s2b33rW5u2PtoNnta2qfW3OXDgwIpZL8vOMM2U+Xd/e4tvDs1i\ntT49ELU6dch0BB0BDdN0p/mE/Drn9sZxHMn1mSLHd0UxHYEjJB0BDUu4Qvp/vzTGQCLEr77rCd7+\nRJKvXptjeK5INBzgmd1+hmYK6JqCBLL5IqXZPJ/7+jwX5ySa7mdnZ4h/8aP7+OEBP/lwF6OpCmXT\nJuzX0TUFXVWoWIKAT8MUDn7FrSItVGwc6fZDt4XkXt5EUxRO9ncQ0DUGJ3M4QhCOBOnp8HEvZ9AT\nC3AvW2F4rsguXcEQ7ii7/oR74fbrKs8MuJ9zOmeQr1js644Q9mt0RfxYjqyfyBKF/d0h0iWLaNDH\njx1N8tp4DsMW5ErL/74rtiCfN7GqprymgFTcxme1yUuqcn+GjFL9Z9qCmzevk5vU6OzsJJlMEo/H\nH6oUv6202FvNyEkmk2QymfrjdDpNZ2dn/fE73/nO+n+fOnWK8fHxNbdplW0l7CsJtBCC27dvk8lk\n7hvwvJkDrWvUKlh37txJqVTalNF4y21Tm+q0VmvhpcOd//gHd/nc9+8wmTGaWs+ncp/4+3SFeMiH\nrri9SCq2+7eQT2WhYLEj6uep/ihBXaMvFmSuYCClW3UZ9GlEgzpzeZO/Gpzh2nSRgmFRNB1uzZZ4\nZiDK7mSI6ayBpmtYmsaYCDJ4M8tAVENUclzPZvj03+b54V6HvqifouFgOTCTc3u6JMI+EmEfuqpU\nqzxFdaiFmxM+X7SJhXSiAY0jvRFu3CtyaEeYVNFkVyzA4d4O/LrKtek8t+dLzBcMOoI6U0XJ0bCP\nsYUS8wWTRNhHpmRhWDY350rcTVcomTbX75X40cNdDCRC7E0GWSiaOBK6wz4OdEdIhN1T88uD98iU\nLEzbnVO6lA4dRuaKXLybR0hXvJUlxVu1/17qlpFVi70r6uddP3QWRTpkMpl6gVwgEKjnekcikS2f\nObqVwt7K2idPnuSLX/wi73rXuxgdHSWRSNTvzkulEp/85Cf5tV/7NXRd59q1a7zlLW8hmUyuuE07\nPNLC3oyPvZYfnkwmlw1SbsZA6xqNzcNOnTqF4ziMjo5u+DrLrTs5OUkwGGypx0zRsPnfv/AGF+6k\nl810WYmAT8UxRD29sXaIn9oVY2yhiE/XsCwLv1/Hp6ncni9xL2+CIjnQFeZgT5hs2SJfsbCFK0Bl\n0yHg07h5r8Drd3MUq8nvPhXGUmV0VaG/M4CuKgx0BimYAtOB+YrCEz0JtyOmI/nS9TxD3x+kbLuZ\nMraqoKoKb3siweh8uVr05GDYbopkserGiQU1wj6NgO7msjvCddfsjAU4uTuOqigYlsN8NS/ep6tk\nSiapgsC8NsuZ3XF2dwYxHUFPh590WWEqa+DXVUxHpWw5vDGR4+0HE7z9iSS5io0lJGrV/VP7nRYq\nDnZ1DquygsP8ykwRIV2Rboxl3Pe7WEHcTUtwbTrHM7s7F1Vvlstl0uk0Y2NjFIvFelFPO+fLetlq\nYW/FYj9y5AgHDhzghRdeQFEUPvjBD/LSSy8RDoc5f/48p06d4qMf/Sh+v599+/bx7LPPoqrqfdus\nh0da2GlwIywn7HNzc9y8eZOjR4/S1dW17PbrqVhd7Qdu2zZXr15F07R687B2qkhbbZFbLpcZHx8n\nGo3y9NNPN2VlSSm5MGPzf37mZSazlZZcLz7VzYPWFfD7FLcHeDWX+3sjCxzoijCVK6MAnWEf2bLl\nFioJyWzeYC5vEgvqgCQe8pOrWJQth6vTeU7v7iTo00iX3c6IABVHElehu8OPrqpcmcrhCNidCBLQ\nVQzbYTZvYFgOab+GammoPh9IB8Wx6QyCYzuU8jmkcB3UYb+Gogj2JoMEfRoaCgXDJlqdQnThTgZQ\niFSHTl+fybO3K8LQdI7OkA9bSPJli5m8ha7AbN7ga0NzvOdELwFdZXiuuKgtbsinoWsqjpQMxIOM\npsoMVN0246kyw3Mlntrlzs0N+TWElFgreBkLNgSrufE1C5yq62XZcXi82TSNahC7ZAs+9e07/Jfn\nFt/6h0IhQqEQu3btWobvpVAAACAASURBVDTmrlKpcOHChfr0o87OzraLh5plq4W91bWfe+65RY/3\n7dtX/+93v/vdvPvd715zm/XwyAt7jUaBrpXm5/P5VZtZLd2u3fWWUps2tG/fPnbt2lX/+3r95WtR\niyHs3LkTn8/X9K3zZ793hz+7YTJXWbuQiCVWny1AUeHpPXFKhsPofAlbERiWwLLdWZ3n9ia4cHsW\ngHzZpiOgUrEd4mEfmqLQF/Nze65EPKyS1PwUTTfz45d+ZC/furlAxK9RqQ6QViQIoRDU3T7pfl0j\nVbLY3x3mcE+YKzPucObOkI+prEFfUNIZ0inZAqRG3nKwHIXvThgIIdgVhqhfJY1CvmwxVzARQkFV\nJNNZA6oCGQtqDM+V+HuHu4gGNA73hnEcgaIqvH43i+mAX1OqFwo3NVGvpmc+0R3m2kyBZMTPXMFE\nCgdHSE7u6mBotkjJcOrTi2oj9PLVCSHH+yJ86+YCtiNXrCKtBUcbfyXaCsKuLOOacRzJQsGiaNhE\nVpiiVCvqCYfDpFIpTp48STabJZVKMTY2Vs8FrzXd2mgR3upBG5t94dpoHq29XYWa0Nb6iPf09HDm\nzJk1xa2dtEVWEenV/Nqb1R6glsqYSqU4e/YsqVSKcrm85ntLKfn3X7vJFy9OUlg97gzLVJMquNWi\nUsJPHuvh9ck8U9kKjvnm/g5N50kVTMoWRIWboiikOyBaV1UCfrd/uiPdtD1NVYj4NXo6/NzNVLhx\nz3UzJMM+Qn6NiF+r74EC7O9ye7boqkJ31M85fxwUhRv3CmTKFqWK4Ow+H5qmMrZQqpf029X+BfOm\nzkAogGKblE2TTAX8KhhCcYOREkJ+dyiGAK7N5OmNBpCKws25Aod3dHBqd5zJdJmCCSHV7StjO6J+\nlxHy65zbEycc0Lk2nWdkocyRHRH64kEcIXllLs3uRBCl6t450humUHEvDLmyTciv4zjuQBFzGXUv\nN/Tdqf3a7RV+Mo1lYtXZ2FiOWFHQl/vN1DJDGsfcmaZJKpViamqKfD5fn36UTCYJhULr9s///+y9\naXAc+Xnm+cu77gs3QIDgAd5Hs9lk363Da+u0LMuWZUszOwpJa8sR3plZeydGEfKE7d2VxnLEaFbh\nidCOZhySJVmSZXnGlnXZlltSd0t9Nw+AJ0DivoG6Kysrr/9+yKoiQAIkADab3e1+voAgKiuzqrKe\nfPP9P+/zvNYq9ruN1xWxm6bJSy+9dFMf8etxO6qYldt5nseFCxfwPG/dvvadIPaVUsbjx48jy/KG\n2jc1x+NPHx/hK89Obrj1IoCIpmC7XtDzJQi8kIAfnF/g3//8Hi7Pl5ktgCz72E7QMC9YDhUXtKqL\noSl4vo8QwYSm4/k4nqAjblC0XNIRjYgmc2xbgu+fWyRqKHQmdOZKNjtbwvzS0U6Klsv3zi3geoKI\nrvJ/v3svA+1Rzs2W+Prz0wzNBguJcUMhV/F5abLIztYI92xLcGXJZLFkAwLL9anYLlezPoYCMgqq\nAj4Cz/eb/WrX88mWayQjOhFdZn9nDEmSONqdYHjRZHdbhGO9iSA7tBq4SKbiBtWaixpSyVcdHNcn\nYvhkogam7dFZnzxVZInD3XGiemAjEIqo5Koe8bpNwfn5CrbjoamBH419i3NVkUCWA4fMRhD29Vuo\nctCK8URA7K4PlZqDc70H8hpYj+R0XV9lumWaJrlcjpGRESzLIh6PN90VdV3f2Am3Anczmu6Niv0u\noGE52ziBHn300U2dOFut2BVFadoDVCoVzp49S09PD729veuegFvZ182IvVgsMjg4eINp2a3aN77v\n83vfGuQnw0sbJvUGydme11zEEyskc1eXTP7smQned6yL//bUOLgSjhT0cO36FKTvC8JhFdeTeNNA\nC+dmS1iOT0tUoz1uUKg6vHlPC73pMMMLZUq1oB2xvSVCZyLEuw618+DODI7ns7M1gmV7bG+N1nv0\nsKc9SjKsBTF3cuAUmTIgGdXY3RZlvL7o6vrBxcTzg/aJocgkwiqdcYOryyam7dUzRCXCihyQvCQ4\nmHRwqgWWl30i0SjhUIiuhE5fJozleCRCKo+fn0EQLMI6QpCOaE0jtIYXTM3zyZsOqYhG1fbwfMhV\ng3OpYLrEwyoly2UsW6Vqu1Qdger6de07N5iorYQnIKbJuJ6HrtBcBJfrhO7WHdl8n2ZfXpElSjWX\nz/7TKJ98xwCGun51uhGClSSJaDRKNBpl27Zt+L7f7M9PT0/j+/4qWeVG9el3k9jfqNhfYZimyenT\np+no6CAUCm26GrhdHfvc3BxXr17l4MGDJJPJm26zmX75ym3WwtTUFJOTk9xzzz1Eo9E1j20t+L7g\n//zWIE+NLN+UIFYdwwqlhSwFPeRS1UWWr/VxzZrL4xcXOT9bJKYrGFGd5XINRZYJ6woLhcCy16+P\n6t/fn+LKYgWAeCioTjNRnffdEwSaFKoO52bL6Grw+j0h6EgYnJrI8+3BBVxfEAupfOyha5IwTZH5\nnTf3M7xQwfY8fF/guh4xQ2n2uhMhhYlste6uGChkIoaCKgeRe4GuvEbN9QmrgQNkoerypt0pDnQn\neW40S8EBt1DgheEZQrpKpVzi8dEqy6aD70OaIG/0Hy4s8e6D7UwXLAbaoiDBbMFidKnKYtFmZ1uE\ne/tSTGWrhLXgq/jDiSUWyzaaIlOyXGKGiiS52G7g5nhvb5Jzs2XKNW/N9RBR183LshdU5Y3P/ToJ\npFy3PpYbUYGe4MXJAlcXK+zviq97Lmw1pSyZTJJMJtmxY8cqL5ZGKEajrROLxV519gZvuDveBUxM\nTLBv3z5SqRSzs7Ob3n6rJ5EkSczPzxMKhThx4sSGMhdfjhN2ZcvnxIkTa94irh9OLfjU9y/x/fOL\nN41Laz5PnShWDrd4PpQsF0OBTDzQnwe94aCqnS/aSATRcsmwRmfSACRkt0pvewLL8WiNaTw9mkNX\nJWYKNvOlGvs6Y/yL+3qa+37LnlbGs1WuLgVTwff3p3hiOMv/OD2LJEl0JUPoqsy3Ts3yW49sb24X\n1hT+/S/s4msvzJCv5tGQ2dMWYbZgUbBcMhGN9x7tYGi2TM506hOsQW9/oeTQmwnT3xIhrMmcnSkR\nMxT6W8Ls7wou2vf1Z1gq2+xtjyLCJVrDMt8Zmsd3bfx6Tz5v2rREg0pdliVSYY2L82X6WyL8aHgZ\ny/Eo1QIbg+WKw6HuYOJzsVQjW3GQpWDdItDVQzyk14lYMFOwgkEvLRjkWguNu5HrP2KnLocMKRKm\nH2TASiJQKDX858dz1ZsS+8vRElnpxUJdktxwViyXy0Sj0SbRr5w5uVt4g9jvAvbt2/eK62qr1Soj\nIyPous4999zzilUYDVfGrq4u+vr6NmUc5rgev/ONs/xkeHnDzn+NQIuV63WKHLC94wUTi4jgyy5L\nQaXoeCKosiWJY31JDFXh5/e38Z+/X2ChZNGVDPGuA6185/wSHYkQqYhOpeZyqDvB/TvSK/Yj8ZEH\nezFtD1mWeGoky0+v5qBuXzudr5KOqMTWcCXc1RblP7xjgMGpPJ/9wXlenCpRqXk8NtBCuebxk+Ec\niiyoWD41z8NQZTIxjaimIUvQUbcC2N0aYU9HjJl8tanNz5sOharDXDEIi+5IxFBUnXBYQXMs7LoP\nfNVyUHGpFvOk41HS4Qg50wEh6ncHMrIkmM5ZWI7HAzsyzVzXkKYgEMQNmaojkBD4QmJXa7R5lxPW\nFTxfUFtjMTVXXd/PR5KC4O+QGgyV1bygnC/XfNpiCl2Jm4dO3Im2RCgUoquri66uLoQQVCoVstks\nFy9ebHqlO46D67p3pde9WRfXVwNe88T+St+2NbTxfX19VCqVV2z/jf1uZGH4+oq9XHP5+FdP8cJE\nYcOkzgpNdESTsJygwvP9gOhloGQ5hHUVTRaUal4wTyAH+5YRTOctshWblybzpDXo605gOz6j2Wu6\nSkOV0RSt2ScHWCzX+N7QIp4QPLQjxb7OOHPFGlFdQVeCMGqBRLHqcGL7Ne31fLHGX5+epeb6dCdD\nZCIaUV1CCAVFlriyaBI1ZKqO21wzaInqJEIaYVXGEz79LWHCWqBeaY0F06mz+SpT2SqJiMbIYpl7\ne1OoikQ6onJ+rkw6ojJXsIgZKmVhI8syuq7yc/taCKke0ws5zGoVV1ap2j6yrKDIgqzpUJBcslWH\nrOnyloEWDE3B9TyEJKMpCumIQncqRFvcYEdLhK6Ezk+Gs2RN55YhGutBiED1oysyNc+rt9QEyxUH\n5xZPeqcXMSVJIhaLEYvF6Ovra3qlLy4ucvr0aSRJaqptEonEHe99N0y/3uixv07h+z4jIyMUi0VO\nnDhBtVqlWCze8f0KIajVaoyNjd1Sk9/AKntgx+Ujf/4SZ6eLmyL1lXA90VwwVeRrC2+OL5A8D11V\n0ZSgshRI+EKiOxlitmAR0hRqjs+ULejxBboWBDX3ZcJM5YJKOKwpvP1AMO1Yrrl8/olxbNdnPGfx\n9+cW+M2H+9jXGWNotsTejiijyyY1x+fBnWl++Wjgf+P5gi8/N4XvB8QzslhhrlgjosnIikrVdZgt\n1nA8H9eHmK6QCakULQfH90lFDBTg4lyZnqRBOqIy0B7IVfd0xPCFoDsZwvcFqhIQW08qTEvYpXeg\nhc/lRynVXDIhiV87uT34d0QjrCk4cogdYRXXdcjbSwzNV7HqksR4RENRgoGoq8sm9/cn+adLyziu\nQ1hXiIVUDnbF0RSZQtUhHdWJ6QrlenVvb/JmVVNk3PpisON5Tb17Y8H0z56eoDsVoju5dgvklSY5\nWZZJpVIYhsF9992H4zjkcjnm5ua4fPkyhmE02zabzTLdCBoXsjeI/S5jqxXFzbZrOEKm0+mmNr5W\nq93xFlBDyiiEaEoZN4JGxW7ZLh/7yinOTG/tAtTosbsCjEaosggCo31foCjBz6rtoSoSmqKQCqu8\n/UA7z4zlqfkCTZEpWi6IIPJNU2R2t0V5aFeGs9NFKjWXg13xZgrRpfkKFdvj4nwZ4YNA8IWfTfCp\n9+zjrXtaOD1V5N7eJG8/0MaRnmtuhCXLxbQ9wlpwy6wpMqbtEZIFnXGdbMWjUquhyhKKJCjWnGAh\nV0DcULm6aFK0HAQSs/kah7clmou9L04U6E2HcX3Bxfky9/UlURWZuYLFUsXmBxeXKFkuYU3GsWF4\nsUJPKhx45cgyshQsIiu6wVsP9rCv16Roevz0ShbP83HdIPZuellQcgTxkNpU0CyXHQ52xtBVhQtz\nJSQkrHo0YMPga6MXbF2pSx19UOtyJscL/k+RJaquT9FyOTNVXJfY74bscOU+NU2jvb2d9vZ2qLcn\nr88ybRD9VmSV1+O1WK3zeiD2lSfZVuLqWEGEa52wy8vLXLx48QZbgq1OrG4UK6WMtVpt08Zhnufx\nu381yIsThU3tdy2ikAC73peRCSSCviTwhABJxhcCyxaoIYmq7TO6XCUT0ZgtWE3lRdUNKvPjfSke\n3Z1BkiQc1+fxy8v848VlupIGH32wl5ih1HXfQWUsBIRUhZ9eyfKvHujlbQfa1zzuqKFgKNfeI88X\nHO9Lcnnc5Px8hVLNpz2mU6jaVLyg9ZAzHVpjGlFdZjLrBn1vWSKkK1xeKDPQHiVfdWiN6XSnAqLb\n1x5lOl+jO2mwVHbob4kwOFMmEdYoVl1U4MqSSdxQKYdVJElidLkKAtJRHSEEqZDGvvY4FxcqFKoO\nsqThC8FAa5iXpktUqjaWH5iRGarMj4eXiRkqL04W0BWZuaK9qbsvRQoSqgIbg0b0Hij4yAQXCMvx\nSUfVuvx0fUK8G0R3s32Gw2F6enro6elZZXswNDSE53lNWWUqldpSn/wNYn8VYCtxdSu3W/kBrgym\nuN4RktswD2MDVc/1UsYrV65sqlKSJInHR6s8ecXctIf6yoGWZl5pvUqXJXD9QK5I/fY9rKsslm0M\nVSaiq0jAVK7K9pYoEV3FcjwimkKHLvEn7ztEzba5PDpFKBrlO0MLGKqMosBcweLbg/P8yj2d7O2I\nMbpUbQ5EdSdDhNcJWhZC8LOrOabzFns7Y3Wpo09rVOdDJ3r4zNw8USMMksw/XVrC9YLBI4FEW1xj\nWzqMripN3XoipCJJQTRdWJMJqfqqyc54SENTZHpSQeqTUd9WQiJuyISR6EmG6EwYzc/r6LYE07kq\n8bAa3Em5gkLV5c27M3zv3CLpiMqBrjjb0mGWbZnnxnJAYCvseD757AJPLsuUbJ+qc2Ps3Xq2vA14\nAmwXKk4g4VQ0Bct1cQTNuy7PF5g1j3RY53jf+r7sdyvIeiPkujLLtL+/H88L3CobFf3Kadl4PL6h\n1/EGsb8KcLu+Lw3Jom3bDA4OrhtMwcvgCrnWxachZfR9f5WU8WZ3FGvBR+Jvh80N69RXHcOazxdU\nwF7dQiAZ0dFwqDgSluNBPcezaAUeLf0tEWquG8geVZn2uEHIdljMFfiPf3sKS9IpV23yVY/+TAgj\nZGAYBjnTQZIk/u2b+5GBC3MlDDXoM7/7UMcaRwbfOjXH+bkyIVWm6no81J/irfvaUGWJ5UoQrt2V\n1pgu2NiuX69UQZYDSaDt+kghQSqiUfN8FEnCdDySIaUuhfQ5P1fmnm0JZAlOTRU50BllqeIwnbcQ\nCA50xoO2ku1hIzgUUZkt1tjZEqTfSELwyK4M9/QmeX48x0w+kIimIjpvO9CK6fgkwxoly2W5Etgj\n2PVefkSTGa8auCIItF6LuyXWJ/UGGtemqiuwyk6g4ZckNDkwVqMuzUQIvn9ukXcfXvv99n3/VUvs\n10NRFFpaWpp32rVajVwux9TUFKVSiUgk0iT69SxyX4tSR94g9gArSTqfz3Pu3DkGBgaafbw7sa/r\nTxbTNDl79izd3d03TK82ttnoyb1YdpjffCjUTSEE6KpEzFAxbQ9DDrJGNVUhrMnYno/jCvZ3xLl/\nZ4a/OztHpT5EM7ZU4c0dHv/170+hxzPENZV0wmduIo+k6di2QzZfogON8XFBJpPhoR1pJvOBfDCq\ny6yV2uYLwaX5gNQBwqrC0GyZX6i3a0KqjERwnKenik3/FK+ux7c9v97LlnjbgTaeGc0H/W3gQGes\n7vUiM9AWoSWq4QvY0RomVh+ouqc3wULJ5uGdadpjGo7j4FUK9LfFODNdZNl00OpB1JcXK1xaqDCd\nr9IWN0jWnyOsKfzCvjY6kiGeGMkSM1SihkpMkjBtF0mSUBUJWZJRVRnJdlZnxko+YVWmtIn4WUEw\nDZwIBQvZDatlXZVxheCbL83y9oPtqGu86UKIV1UrZjMwDOMG24NsNsvly5ep1WokEomm7UGjyNuK\n+diXvvQlhoeHkSSJD3/4w+zevbv5t6GhIb7+9a8jyzJdXV18/OMf58KFC3z2s5+lt7cXgL6+Pj7y\nkY/c1mt9zRP7VnNPV0JRFFzXZWxsjLm5OY4dO3bLrMGtVuxr2Qo0pIwHDx5cMzVls/saWaps+rhu\nBgmI6DJqncyjukK55lPzQFOD23nZD8yy3nm4g1REIx3WyPSlMGsuvl2l6tToaO/i7FgBy3bRVYXe\ndIhkNExYV9jdGuFte1PkcjkuXhnjz14qEDZ0oiGDxZLF/zw9x2+cCAaYnhpZZmi2jCJBxXZJha/1\nhFcWkxFdYU9G5ak5E3sNH5SIJtMa14moCqmwxuGuGAMdcZYqNmH12hMVLDfQoAPVmgexa+9Ld1Kn\nNx0K7jaExpxVRJIkdrdFeWx3hmRY4wfnF9Dr/f8dmTBnZ8rs7YjRaKoMzpY4N1dmsWxzYnuKuWKN\niu2hyjI7WsK8aXeGrz4/g+v5aHVLAUUKFogPpGWmqwo1z9m0Qsb1RPMYwpqC6/rkqw5RXSFvBmsL\n1+PV1mPfKlbaHvT29uL7PsVikWw2y+TkJEIIcrkcuq6va/m9Fs6fP8/c3Byf+tSnmJqa4vOf/zyf\n+tSnmn//whe+wB/8wR/Q0tLCZz/7WU6fPo1hGBw4cIDf+73fe9le32ue2Fdiq8QuSRIXL14kFotx\n8uTJDffztoKVFgZCCK5cuUIul+PEiRPrruJvltgT4VtPwW4Goh6/pisSqbCOJEHNBk0iUHXUpXua\nIvPdoQWO9yXxBYQViYpVQiDTktCZKtjBAqMMph3I9f7fX921ypukq6sLEUmTHB1Fl3ysmkWlUuG8\nledqS43JmsHjV8pE9KBfXahnfBp1G9+3HQhaCMWqw1eem2Ys54KkE9ZkSpbXfD16vY/eEdfpz0SY\nK1hczVbpSIbwPJ+Lyxb9LRGKVYdS1UPNBMeYr7oYBYtERGOhWCNmqFhOidFlE0n4hOufq1pX1MwW\nLEzbQw8H22uqwuGeOA/uSFOwXF4cz1Nzg8nP6VyVVETjl450cnWpgiJJ/Ju37iCiyWRNl/FcFVkK\n2l+TuSqHu+OYhSwXcu6mSV0C4iGFquOD8DEdL5holRR2tAaTt2ueC3epx36n2yENWWWjsHJdlxdf\nfJFnn32W2dlZHn/8cY4cOcLJkydX+TJdj8HBQU6cOAHAtm3bqFQqmKbZLBT/+I//uPnvRCJBuVze\nkIR5s/hnT+zFYpHFxUV6e3sZGBi4Y8fWQIOkG338eDy+ZrLTWttsFEe3pTAkqG1VuL4GPB8ULdBS\nt8R0VEUmqkB7IsRcsUZIDSRzwwsl5opV3rk/w+ODk0SiUQ70tHBfeJEfLgVV+nIlyBHtSxuBh/l1\naInqRHQFkInrcfRQlPu2J4jFVJ4bmiSbs6hoCuFwmGRI4x0H2tA1hR0tEdrrU6N/c3Ye2/PRFZnO\nuM6lBfNawHM9uq8lprNcdmiJekzkLPa2xzBUGUMN1DGP7kpzZaFCNh5Mcrq+4GB3nFRYRQA/vLCI\nIgetmj3tUS7NFpElMLRgIOqnV3IoisTwosm+9gjxkIbl+pydKnBqskjF8TjYGW/cALCrLYrjCxIh\nlV2tEaqOx1+fmkVVgnbO0Z4Eni/QVJlHdqU5PVnkJ5Me68+Zro+4oWC7Atv1UWUJVYDwBZbj0xYz\n6u//jXgt9dhvB6qqcv/997Nr1y6KxSI9PT0MDg6yuLh4U2LP5/Ps3Lmz+XsikSCfzzfJvPEzl8tx\n9uxZPvCBDzAxMcHU1BSf+cxnKJfLvP/97+fIkSO3d/y3tfWrDJshdiEEU1NTTE1N0d7eflvBsZuB\nLMsUi0VGR0dvcGVcD+t5v6wHQ1X4wH6ZL59/eXX2jWOQJAldBrsuRfRFvWdb78UvlSwWZ6b5f375\nMJFYgnRE47nnloiHNLalgyg7XwgMVWa5EizkJVfcZRiqzEcf6uWvT89huz6HuuL84tFO5ks2Vypz\nzFV9lBr0SS62U6E6V6azM43qtOB5KoqiUHU85Lqk8vRciartryJ2Q1PoSBgc7I7TEtGI6km0FXLJ\nSs3j4nyFhXKNsuUxW6xh2h6O57O7NcQzY0WKlkNYU3luokBYV+nLhLknatO7O8P/PD1LrD5Ne8+2\nODN5i3TM4NxEnvNzZWRJwvZ8JpZMPnhyG4os4Xo+D+3MsKcjypeeniRZbzH5QnBmushc8Vou7C8e\nbuepK9ktkTqA8IMMWOGDrNRHy6RA635xrsR3hxbWXEBtpJW9kng1eLG3trbylre85ZaPv/57utYd\nTqFQ4DOf+Qwf/ehHicfjdHV18f73v58HH3yQ+fl5/uiP/og//dM/vS37hNc8sW+lx+66LufPn0eS\nJE6ePMnY2Ngd1aSvhGma5PN57r333htcGdfDZit2SZJ4S28IL5riL56fuY2jvQZRr9oPdMUwNIVa\n1WfZEixWbGRJwvM9cqZDXJdIaoJQyza2dbSuOqYPnujmK8/PkK/UCKkKnhB87sejyMC9fUl+6Uhn\n8/G96TD/9i07Vh3Dt16aYXsmTKnmYdoek2X4zUd283N7Wsjn8ywvL3PlyhVmqjIvjfkUHYlCxcV0\nQJZB8uuqn3p/ujNhcHqyQCKkkopoyJJEa0wnZ9oULZeq4xHTFX46kkVTgkreE4KnR4tUHQ/fE5R8\nl5gexN/9ypEWLs+7zI3ngm3rxK4pMkd6krztQBvfHZpHVYJM07AiU6jazJcskuEgTerSfJlL82XK\ntktGDQi0YnvM1C0LClWXatXme+cWKW22/7ICJSe4wMU0EL6P6wWtNd8PrCCeG8uvS+z/HCr2BjzP\n2xTBZjIZ8vl88/dcLreqaDRNk09/+tP8+q//OkePHm1u89BDDwHQ2dlJKpUim83eVLxxK7z2BJo3\nwUaIvVwu8/zzz5PJZDh8+DCKotyWJn2j8DyPoaEhbNtm3759GyZ1bmOh9t/93A5+97jBvlYDfZ1P\nejNf0Z5UiHLNC/raQjBTtMmZDk79PXc9j46ozJEdHXSnV78+SZLIRDT+3c8P8B/esYcDXbG64kUh\nrCs8P15gMnfz1Keq46MqMkd74hzvS3LPtji/sL+9KWsbGBhg14GjDJWjbEvpaL5NyfLxXB9phX+8\nLAVZrfMlG0WWGGiP0psOkwyr3NOTYEdLlIH2aPO42+IG21vC3NuXJKwqRPSA4GNhDV2RUBWFIz1x\n5ksOowWPbMVhbLlK3rQD9UXN40BXjLzpoNWdGxtIGBq/dqyL+7en8HxBxfYo11yuLFYDkzUgW7GR\ngKiuIEsQ1lSqjs8aXaxNwQeKDphufTBNCuSsnmNzZWaBCxcusLCw0Mwd4HW0eHqn9n306FGeeeYZ\nAEZHR0mn06uklF/+8pd517vexbFjx5r/9+STT/Ltb38b6q2cQqHQTKbaKl7zFftKKIpCrVZb9+8z\nMzOMjY1x+PBh4vH4qu22WrFvpIJZKWVUVXXTFc9WiN11XV566SV+7dFD/NZ70iyVa/zO189wbraI\nEI350uCnu4bFawNSXWmiSNCTDlOoOgzPlzAbgzJenWAEaKrMzs4MBculVHO5ulhhZ9s1gmzcpiqy\nRNFy0ZQg6Wkqb7Fcdvj7C4t85MHe5jj99WiP68wWrPqkpMe2NcbeJ7JVVFUlHDa4L54gMj7LxWUP\ny6vb1AKGGiycCl81qQAAIABJREFUuq7H8e1BYDb1yjqkBeHRVdtrxsXFDAXX85kt1ChaDumwRjKs\nMZGroikyD+xI8bYD7fz90CyaLKHIMsf7kpRrLj2pMD1Jg6euZKnaHq1xnblScI7KwMldKXrSYYZm\nF5t9bUmS2NMeRVGCCEHT9pCQmC9auJ5AVRR2t4awXY+F8iZ0juugYeomSWB5QX/5fYe76O5OrVKJ\nZDIZLMu6pWLs5cbdzjvdjDXB3r172blzJ7//+7+PJEl89KMf5cc//jGRSISjR4/yxBNPMDc3x+OP\nPw7AI488wsMPP8znPvc5XnjhBVzX5WMf+9htu1i+5ol9I60Yz/O4ePEijuOsGVu3Mg1pM9iIhcH1\nUsbh4eE7GmgthGB8fJxarcajjz7anJhtjRl87aMn+O9PjfG9c/PkTYdYSOF4X5qoIfOln06uOZyk\nyEHyTzKs0hYzeHE8h+2tnn706p4l7z7SSVhXCbk+E1mTL86X+VcP9LG7I9Yk9poTBGAc7UlweaHC\nVK7KQqmGLElcnC/zF8/P8C9P9qxxJPAb9/XwuR9d5cxkEU2SCGsKk7kqvelrFVF7wqDm+nUCl/F8\nyMRC1Pwapt3QxAuE77CwlGVcMenMJJH1EAtll6f8LJIQDC+Y9LeEURWZve0xBmdK5KvBom/OcmiP\n6TywPcXP729FCHhhPMdSxSZaPx1lSWKgLcojuzJ8/9wCEhAzVA53xdFkmT3tUeIhBYHEX74ww3jO\nJBPRm6HWmizxnsOd/PjyMns6omQiOs+N5ylYDttTYY71JgkpEhdn8ixUgzWOtWLwNgof8LzgTkap\n++onEolmOEbDfGtpaYl8Ps/c3Nyq4Z472Z652xX7ZtcUPvShD636vb+/v/nvr33ta2tu84lPfGKL\nR7g2XvPEvhJrEXujWr6Zh/mtKv31cDNiF0IwMjJCPp9fJWXcau7pRhZPG+0eVVWJRCJr2CBI/OZj\nO/jNx3bg+yKYNKxnej59aZbzS6uX4uT6SP+u9hjvOtTBk8NLWHW/8RteLzBQJ8BGb9nQZH42mmV3\nRwzPF3zhqQkm8jYIn8cGMrzncAf/6YdXiBkqvekwEV1hZKGy7l1QoKCRmla9Qgi+MzjPbz927Ytz\naa7McsVhth5IgSu4f3uCJ64WkCU7eF5JQtM0BrYnqbkuwncpL81Ss3wqIkY0FuVAZ5TWeIiT/Sme\nHs1xqDu4w3tuPM/QTBHbEeSqHtHRPMmQil5fCM7aLq3tPj6Ce/uCcA7H9Zt3IZIk0ZcJ8+7DHTxX\nn0LVFJmeZJgz00UG2gKHwkxMZ7EU3CHIskR7Qufdh9up2h5vGmjh24NzpCMqx7t0LhUVxrPVVdYH\nW4EsQ0iTiRkqz4zmmchV2Z4JqvOG+VaxWGy2F7LZbDOSMpFI0NLSQiqV2lDozGZwNzNH35g8vYto\nVIPXE/v8/DwjIyPrDv40sNV4vPUyTG8mZbwTgdbUL2Bnzpyht7eXbdu28bOf/ewWz3ntmFRF5v96\nawf/+/fnWaq4gc5bkfi9nx/g3Yc7SUV0XM9nbLkCV9YfX39pIo+qXvsSiHr8HMAzszZXqyZhXcP3\nJb754ixHt8UJaYHfeGPKUZbWnxFwfYHr+SiyQqHqkDMdMpFrJLJcsXl2LM/utii72iIUTIfL0xYx\nQyEdDkKlq07DAVJiT1sMARzqihMxVJ4aXkK4FsVCEdM0cZNhijGLqiUAFU8Iri6Z6IpCMqKiyBJP\nXcnxvnuCRd9j2+JcmTI50hNnV1uUC3NlhhfLTOUshBBsz0TwfUHEUIgaCtlK0I6aL1o8O57Hcjw6\nEwbtcZ1cxeaJkSxXlirsaIkQ1oMWUdRQierB8Y9lLUYWbJDkwAd/y8bMAQxVwRNQqLokwyqnJotN\nYm+gQXSRSIRIJNLMNG0M94yPjwcXphWeLLdbbb/WKvZXA14XxN5Ag9h93+fy5ctUKpWbDv6s3G6r\nvi/XXxAKhQJDQ0PrWhLcCWJfWlri0qVLHDp06Ja5q+shpKt85YN7eXLKpVJz+eV7ummNXxucUBWZ\nT7x9L39zepbyGmoMQ4FUVKcvE+HCbBnL8SjbLo/uzgRTfFbQXrAcj7GlCotlm1RYJRFWGZopsast\ngibL/NKR9eWfmiLTlQxxeqrAeNZqOjR+b2iedx7qoFxzm9QmIREP1YOkhWC5Pjka1RQURUJT6iHO\nlsuLkwXiIZXpos2OlijRaAzL8TnQpvO3FxaYy5aZLrkc6oxQs10ihooiQdlyMWsuNcfD0BQkoDWi\ncrgnwchihaGZIhFdZXsmwuWFMq4vaIvpHOiK8aPLS4xnTWKGyo+Hs7h+IMd8bixPR9zggZ1BmMpA\nW5RiLUiRGlsyGWiP8qPLSzx5eZlizaFQEyiSh/oycE/Z9pClwIphX2dsTS37WpYCK4d7du7cieM4\nZLNZZmZmKBaLG/JkuRneIPbN43VH7LZt8/zzz9PW1sbevXs31Pu73UDrBiYnJ5mamlozYHrlMb5c\nxC6EYHR0lOXl5Q2HcKwHSQoSdT54snfdx1QrZfR1/CJbYgb7OxO871gXP7q4yDdfmqYlqvGD84uM\nZ6v0JxR+MmczkauRrzq4vmChZHO4J4GuyLzzUDuHuuJrjrELESQ0qbLEh0708MxojqiuENUVelIh\nnh0v8PaD7XTEDcKa3Gzl2K7HkXaV0eUqQgjiuorr+1Qdj4rtky3bzJZs9ndEEQJ6kiEqtseBjhj7\nu2J879wiHa0tdLS2sMOskSuZ7M/4jGcrjFVMXBT6WiI8PZrjcHccRfgcaA3uIGbyFhH92terPxPh\nSE+cnlSIvzkzT0ST6Yjr/OxqjnLNrTtlyji+IGvaze00VeZYW4TJXI2B9iiyLDG6ZFKwXCp2PbBa\nBJ75Lwd8EaiPhIA3Ddw4Sr+RASVN0+jo6KCjo2NNT5ZkMtn0ZNlIi+UNYt88XlfEXigUyGazHD9+\nfFNyodt1hfQ8j/PnzyOE4OTJkzc9EWRZ3vRC7VrE7roug4ODhEKhdUM4NqM5vlUff25ujqtXr7K/\nJ8HTY8VVYdgRFX7lWDfvOdoZ2DPMl+lMhJr7vjBX5h1dKj9bDFozSt0CeKZoMdARJazL3NOTIBW5\nsTfr+oIvPzPJVN6Cut59Z2ukPoYPthsMD/3jxUUe3dXCh0728Den51gq11g2HaaWXJatMhU70MSE\nNYVkWCUWUoiGFHboYZT6YFLUUJAlhYd2Zag6Hq4vaFwqExGDdCzE775tP98enOcHQ/N0xyQSsk2h\nUsIs2Lxjfwu2KfHcWI7LC2Wm80FId2MYqSNucG62TEQLdOyGqnCsN0mh6mA6PhXbx/MEviewnCCL\ntVrz2N0W5eJ8pVlBJ0IqihxkljawkXDyjUIAz47lmFg2GeiIrf7bJnXsa3myNL6n4+PjyLJ8Syvd\nN4h983jdEPvw8DC5XK6ZoLIZ3I5To2manD9/np6enhtcGdfb5nZVMZVKhTNnztDf3093d/e622zW\nw329u4Lh4WHK5TInT55k72GXj371FFcXKwgBj+1u4b98cHWgt1jDS0eWZXa0GLgisMUt1zxKlsuZ\nySIfe6R3TVIH+NGlJaYLNYy6JPH5sTwHu2Kcni4hCcHQXJmOmMGZqSLnZsq8eU8L+apLqeZzcb6C\nZXkkIwamHfTXBeAJib0dIWquj3KdB7+hqQwvVBhfNpkvWGzPBMRvuz696eBidWxbgplCjZZoMNTU\n5fsYuOBU+enVHAWvQjIexfckzk4XOdAV576+JImwRs3xsVx/RdKTxKO7Wvj+hUU0WaIjbvDQzjQ1\n16NoOWiKwveGFpjOW01tfSqsEdFVsqZL3WkXUV+fUKTVhL9VOD58+h+G+eK/PLbq/2+XZGVZJp1O\nN3N7bdsmm802rXSj0WiT6BuL/28Q++bxuiD2s2fPNivX5557btPbb3UAyLIsLl++zNGjRzdsSbDV\nHnvjwrOwsMDIyAiHDh0ikVg/EGGzVr9r2RY0ovkSiQTHjh1DkiRa4ir/47ce4MKVcUKqxK4d2294\nrjfvaeWrz02iyzKO77OrLUrCcHmwP8mPR/KBN4kM+BKlmkvedNe9CGVNp26fe+04B9pjHOxO8Nen\nZhloiwYxbhLUXJ+/PjVLdzJEseaiyhJVV5CRJXQFfKEQ1WX6M2EmchayLNObCrFUsmlPGIQ0mdao\nys9Gs0Q0lZa4zvCSyf6OGD2pEA/uzPDSRIEz0wVGFytcXRTcsy2J6wvecqiLMDa1kQr93e1UKhVa\nbJNCpcCRsItdcvmL8Ry+kLgwV6I3HSYe0miPG+xqDaOrMmFdQW7EGjoSITVQFgGENZnFko1pB1O3\nD+xI8oPzDjXHQ1NlKrZPwlBwfIFzGxOpKzFWX8dYOVfwck+e6rq+ykq3UqmQzWab8uRkMolpmpuy\n1Hg58Qax30UcPHiw2UrYygmw2Yq9IWUslUoMDAxsymdmq8Ru2zbDw8MUCgXuu+++Wy4Ib1Qiud7j\ny+UyZ8+eZefOnXR2dl732EDXvt57drA7wW8/toMXx/O0xgwe3pXh3Lkhjm2Lc3RbgtOTeRxXENJk\nVEXizFSBfR1R7u278X082BXnwlyZsK4EyidZYmdLmGREZ65g8cJkoTk+u/L4W6M6IU1BkcD1fSRZ\nJqT62K7P8EKFZFjjaE+CsKZQsV1+6UgH8ZDK352dJ6IFX4uEoaGmgv6/ocpUai5npovEDI3jfSmm\n8lVKNZdfP95NKqLzzPAyo3mXsmKxqzVOIpGkxfPp357gy0+PYdUJakc0jOfZPLa7jTNTJZ4eLTA0\nW2R3W4xMRMN0PFpjOuXatfe3PW6QCKnMFWv0pkNMZKvYjofrg2sHE2aeD+bLROoA2bLD//a1s3z2\nfQeaXj53snqWJIlYLEYsFqOvrw/P85ptm0uXLqHrerOaj8Vir4i1wRvEfhehaRqe5235g97MgqZt\n25w9e5ZkMklPT8+mT/KtELvv+0xPT9PR0dEM074VNjPUdP3jG0NVR44cWTWhe/3jb3bh6MtE6Fsh\nlWs8/4ntSX5wbg7Hg5oX9L1DmsJ4zuJYrwhG5WWpaeV7qDtOxXY5NVlEkuDtB9pIRoKL2oM7M5yd\nKWE5PgJB3NA40Zfi7HSRkKZwtCdBWqmRTkYZWaySrbokDY181Uaruzg2oMoSTmPSagV84fPnT09y\nebFCzfWJ6Qr3bU8jyxJ9mQjxkEIqonNqssDgjElnTGHRtMmO29yzLcGjAy3E4xESqQztra34vodp\nmhRLZf7hmUEsoRKPxzjYEWG8YBE3FDzf58pChWXT5kBnHCQJzw+MyRoEO7JkIssSYVmgqmrQfrK9\nTVlE3AoCODNV5ONfH+RL/+s9GKr8iro7NqLsotEou3fvRpZlstksExMTlMtlYrFYk+jvhPUtd3nq\ntYFPfOITvPe97+WBBx4A4IUXXuCb3/wmf/Inf7LuNq8LYr9dbFQVc72UcWxs7I5o0leiVCpx5coV\nEokEe/bs2dR+NlOxS5KE53lcuXKFbDZ7S5noZh0nhRD88T+O8cPhHLYbTDoqIgjKmClU+bV7u/jq\n89OMLwd+Mcf7krzjYCAXvb8/zf396RueM6IrfPzR7ZyZKiIB9/Qm0ZXAyGs8W+V43CDaYxFv6+GT\n3xulIx5MosYNlZLlYXs+miyjKxLfGZqn6vhYtofjCeIhFR8wax5DsyWyFYea51MwXdIRlV1tcUzb\n5VB3sLg4mbMI6TIxXWZHR5ps2eZdhztIhjWeHcuxULCgPpykhyIc6cyQqzhUrBpPDi8xkVvG9gQj\nMxo/tydDVzJKzfWZLdZwPEFLRGMyb9GTDKEqMpWahyRDSJbIWytknvWe+8sBAdRcwdBsmd/+2ln+\n64eO3NUEJcMw6OrqCjz7haBcLpPNZjl//jyu6952cPV6+77bFfsjjzzCU0891ST2559/vmkath7e\nIPYNhGastPhdma60FZnkZoi9oUTZuXMnprm5rLvNVuwA09PTZDKZdVU21z//Zoj90rLDC1OVVSM0\nPuB4AkWSuLJk8qPLS4RUhd50mOfG8hzoirM9E+ieTdujUHVIhrVV+uqwpvDAjtWkf6w3SXcqxEKx\nxui0w/DMIo7nM1es4fqCdDjw61ko1jjWl6RgOtieT0RXiOgKlZrLW/e2kAhpfP2FGQqWiycEmiIT\nDylcWapyoCvBwa4U+zuDO5pC1eHqkons+nRKEhFDIW6o/OOFRXKmQ29LmIuzZeaLVY73pUhFNEYW\nK4wuVZmp+BihEJLrk635XJor0aZn0WQZE4O2VIyooZDxNM5MFclENaKGjCwEJftanikvszpmJV6Y\nLPJffjLGY8lXh7ujJEnE43Hi8Tjbt2+/IbhaVVVaWlqaFf9WjlkI8aoIs37ooYf4xje+gWmahEIh\nXnzxxVWpTGvhdUnsL+cCz82kjHeK2IUQqwasisUi5XL5Zd9PA6ZpcvXqVRKJBPv379/QNpsl9vmK\nh4RAFl5TCd+wITNkl2++OEPF9hC4LFUcDnRGWSjV2J4Jc2XJ5JsvzlBzfTRF5r1HOzjYdWOLyHZ9\nsqbNhdkyL0wUUGSJl65a7OkyiIdUJnLBYmCp5nGyP0V73OCte1r5q5dmV50vkiTRlQyhKTJ7OqL8\n8NJi8++aInO4O85b9rQSr1snnJ4qULFdsqZLvuRAqMR7j3YhSbBUtgnXL0QHuuMocrDI+8J4gbih\nMpGt4ro+sqZgqAqFqkdVMti+vZty1cZcLlAp5skt2hghA8sCJa7RHg8xlatSLV+zgWhYu90JCOAr\nz03Td0Ll3lehu+P1wdWWZZHNZhkbG6NSqTTVcplMZsOmXg0eudvEnslk2L17N88++ywdHR20tbXd\nMsfhdUHs138pXy5ib4zpb9u2jW3btt3wnFsxD7sV4dq2zZkzZ0in000lymbbKmyCeJeXl7l48SI9\nPWsbb62HzR7TvhYV37VJhDRKKwKZZQlOT1fYHgOzKqFrKmVXIm8a7GoN7oy+MziPIgc6c4Dvn1vg\nYFecpXKNH15cwhNwqCvG45eXKdc8hmaK7GoNrHh1RWJ02ULXAwVKzfHob4kgSxIT2So/uryELAW9\nfV2V8YUgZqiULJfHLwXeOG1RvanOOdQVo/W6hKELc2UyUZ2j3TGWci6tyRCHu+PUXI/lik3YUchE\nNCRJwvUE47kq0frw0kO7Mnzv3ELQPpGCsf6q7ZE3bSQkVCNCKq4T1hQW82XKdh6vlGUy65HUIHcd\nm99Jcnc8wX8fdPjlt27O7vl2sZWqORQK0d3dTXd3dzDgViqRzWYZGhrC9/1VbZv1nvvVUK038PDD\nD/PMM8/Q0dFxyzYMrxdiX4mGwuV2P5CFhQWGh4dvOqb/clfsxWKRwcHBG+wI7oQNgRCCiYkJ5ubm\nOH78OIVCgVKptKl9bJTYc7kcVLL8m0d7+OKpAkum24x4kwFFVWhtSRC2XWZzJp7rskvPsTB5Fa+l\nBdtxkVZ8no7nUzBt/ttPJ5seM98/t8De9iixkIoqy4xlq3QlDTpjMpMVgVdzKVkOjueTrdTIVRxO\n9hsslmyKNZekEUgNY7rCYwMt/O3Z+WZg9MO70mRNh65ECEOVedNABqW+30Ca6CPL1L3SZXRVpub6\n/O3Z+aBvPl0koisc6k7w5oEMPxpebr6W9rjB7tYoS5Vg2vS+vgQ9qTDLFZttqRCKLHFqssBAWwTT\nl9nVkaYtaTBiZhmeLa+aOJUAXZVwXbHlZKVbYaoC//qb5/jPv3pgVeLUncbtFGqSJJFIJEgkEvT3\n9+O6Lvl8nqWlJUZGRjAMo1nNRyKR5r62Quxf+tKXGB4eRpIkPvzhD7N79+7m386ePcvXv/51ZFnm\n2LFj/Oqv/uott2ngwQcf5Ktf/Sqjo6N8+tOfvuVxvG6JfSsOcw2iGhkZoVAo3HIBcSuEu54CZ2Zm\nhvHx8TXtCF5uR0jf9zl37hySJHHixAlkWaZUKm16sXUjj2+sTXR0dNDV1U5XVyf/8fuXKFtu3e5X\nkAprCAKr2Jwl0FQFJdVBR0eabDaLVFliqiyIR8MousHOtgRnpksULZdESEVTZGQJ5ko1BsIaqbDK\nQjnopyPgXfszfPPsEroiEVZVshWH3e1R+ur9+4ShEg2pvLO+WGvaHrV6CAiAripsS6n8yrGu1e+j\nEPz9+UVmChZTeYu4Bi2q4JHOOKcmCwgBO1sjdCcNchWb+/qSTOUtshWHyZzFrpYIti94bCBDueY2\nLQiGFypENRlZkoiHVO7tSzK6XKUzYTA4k+XpsRy5io3t1/3yAVUOYu3iqmDhTrF6HU9eyfL5J8b5\n19clXL1WoKoqra2ttLYGCV/VarXZmzdNk0QigSzLJBKJTS2cnj9/nrm5OT71qU8xNTXF5z//+VW9\n8C9+8Yt88pOfJJPJ8Id/+Ic88MADFIvFm27TQCwWY//+/VQqleZx3/Q1bvioXyPY6hSpJEnUajWG\nhoZIJpMbkhVuZV/XV/m+73Pp0iVqtRonTpxY0zvj5ZhWbcCyLM6cOUNnZ+cqG+PNLrbeqhUjhODS\npUtYlsWJEycYGRlBCMHx3hQn+1P85QszWPURyZzpsLM1GCoK6zJhTea755a4ty/FA7t28X/s2Mn3\nBme4OpdH96tESgX+bAhmyoKwobK/I07cUBF+ELQxnbeoeYKpnMXD3Tol16+nLynEQ4HHTHXFeKYQ\nAkUKevSlmktYk5uulACeL0ivMRl7eb7CQslmoC1KW9xgaqlIb1LlWF+SJ0ey1BwPxxdEdZVUVOf5\n8TyGJrM9E2YmV6XqeKSjKsWqy9BMibCusD0TRpMlPCHwRDBJemXJJB5SsT2fkuUiRKB+kesL0NQn\nRcOaQmsqzJJVvmOLqNQXaL/4zCS/cV83bfE7IzN8JREOh+np6aGnpwff9ymVSjz99NM89dRTCCGY\nnJzkyJEj7Nmz56beNoODg5w4cQKAbdu2UalUME2TSCTC/Pw8sVisScrHjh1jcHCQYrG47jbXo7W1\ndVXy0s3wuiD2reSeXg8hBC+88AJ79uzZcNbg7bZIarUaZ86coa2tjX379q17IdlKj32tbfL5POfO\nnWPfvn3NRaYGNrsYSv2itBYaE6upVKppxNZ4flmWSIU0wlpgeOX7AtPx+e7QEiFdoT2uI0sSku/z\n9NU8D+wI2h6/eLQHjgbrAH/03cuU3Bw118G0LV6sWrx1V5xd7Sm+NZglEdbYlg7heYKXZmo8N18l\nX3URksRyBVIhlZaYRrHmotX92ftbwnzjhRkc30eRJFJhle8OLeIKwdGe+A3VuucLFss2av0CkAqp\nyOkQYTnwtHE8n2fHC2hy8Fkc7IqhKjJXFisMTpfxEcQNhf9lbxuJkMYDO9LMFi0qNZfWqMr5+QqT\neYv9HVF8X9CVDHFupghS4JlueyqWu7o011WJt+xpYWShjHuHI3xdHz75d5f4wgeP3NkdvcKQZZlk\nMsnb3/52Hn74YUZGRgiFQvz0pz/l6tWrvPvd715323w+z86dO5u/JxIJ8vk8kUiEfD6/alI8mUwy\nNzdHqVRad5uVmJ2d5dSpU3zwgx/c0Ot4XRD7SmxlinRychLTNDl+/HjTw+JO7IsVF6EGye7du/eW\nt1ZbkS5ev83U1BSTk5Pce++9a1qn3u6kagMNH5vrJ1ZXXjiWKjauH6Qz+QJkEfSnHdejbLkkQhqS\nBDtabjxOzxecmipScyViIR3b88lEVP7Fve28cHWBqDCJyTq5ko+qaVyZc1AVBYGg5ggkCcKa4KGd\nafa2RehKhuhJh/nu0AKGJmMgU665/Pmz0/RlAq+S4UWTkcVKU4kzka3yo+FlilWb4QWT431JwppC\nzfXpbVepOh4TuSontwetFxloi+nMFCyeHcs3/WkmshaX5ssc3ZasB4ILHNcnkQ5zsl9jYtlkMmeR\nCKv84/nFZvCGqsr0pULkzIDYZQkUIF91eWmiQDqqM1u0b3jvXm48P17g/3tynI8/eqOtxOsBnucR\niUS47777OHny5C0ff/33YaWIY72/3WybBv7yL/+SJ554go985CMbjiX8Z03snuc1e81bmV7bqseM\nbdtcuHBhlSb+5d5Pg3hXtnpu5jy5lUnV69HwhT98+PANPjYrH7+3I4pUl280zuuQLhPR1CDkQ5U4\n2pni7QdvvHPKmU7gbOgF8XeKLKFrCn3beohn2vnZ0mVGlypYtoVllxECbMfHUBUkPCQJuhI6maiB\noijsbg8GjBzvWsrRVM7CFX7zuFVZ8OxojoNdcYQQ/Hh4CUNRaIuF0GSZ8eUq9/WnONqWRK4VgwlW\nARFDZU/9+WcLFqNLVXKVukWvJpEKK1xZMjnYFUdVZCzHpzUWfCV9AXMlm0xUozcV5vFLyxQtB4TA\ndn3ylocuBRp2SYAnBT+jIZVK7Q6X63W4vuCrz03xsYd6UV/BhdRXCpsdTspkMuTz+ebvuVyuaTdy\n/d+y2SzpdBpFUdbdpoEPfOADfOADH9jUsb8uiH0rrZjrpYyDg4N3dNiI+oly/vx5PM+7pb3v7eyH\n+nti2zYvvvgiLS0tN231sIVWzMoLwUqFzXq+8Cuf/z1HOpnOVfnGi7O4voehCPrSEfozYd66p4VU\nVOdIT6I58i+EIGsGhleB3a2MZXu4QqAqEo+1Z5gtBtJH0/ZxfIlkJMTOdp2pxTxFO7DBdV2IGZA0\noGDazCgSf3UqGONvjxlMFaqEVIWQJqPJcvP9cj3IRIMeu+sH4d8NtWMqopOO6rzzYDvZbJb/n703\nD5Izv8s8P7/3zLuqMutQ6b7VOltSq9vudh/QDT7AgAdzrjFBLI6dwQNBeI9gBzAmYGciWDwxYQYb\nZoJdYgfMAMHMGmzDGh80drvtPqTWfatKqlKpzryP935/+8ebmV1VqlJVpkottdxPREeXqt4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/N5ZN2bpihpU0UN1NtG6ydLNhNlh7ihsC0e5/ytN6NuVRUEgURRFVRVoDgBAURGJCEEgCklM1WX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\nd3d34/V6KSoqwu12Z8V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hhz/8YZ555hleeuklnn32Wd7znve0/TqWEgj7EtZrWbfRuS9++mP37t3s3r17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\n4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NAd1yk0ArVNw3I5OtDTtBQOBpXqtsv4cJI/fnOO83crmI4XyCnXec0SUFSFwVSEmZJF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\nqUR1m5awV45pCavEAxIl885zDQJoDmu0RHQ+8uyeTZP6aqxue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jRVyyWqK/ybdx4lPDdB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\niv0DqKys1ET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OllDLU3vSJY+SLTB0SEQ0LMejZ9IkqkHR9fPpqahKydNwXI+StzAnU/lPIWA4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\nEwwG6ejoQJZl80RSVla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xPDA0QTKmY7sSy5U4fhDBxwyoOPVovX79E0DB8hmaqTFbcfnIqT56OtY+Metu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o8st2oJABJ1y2exanJ1TiaqSXQnNA52RQkCj2w2w+fPTK35GfrN89Y8HyFCHfyy4W4cjQdha6S0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4uWdHC6/cdWqKdixR4OM/GCeWrxDL1WgOqEQWzMQGTubxqhK6abH/hIIie1BcJqokUNM0KrUa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\nHS5fvoyuri6kpaUhMzMTQqHQKSb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sq1yo2GiAs5xS6XqSXNXh+nSJhbJNdzLMRx7vfmDXcaeDnSuD3fURgnWhv379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\nbpXrpRCFmkvUUEmFNYbnK5z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dhZ5UlFN9CVRFYbHi0JkIoSp+58SSJXh6ufdL0XSYzpv0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dNw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\nKpUKWVlZowaLh4uJKLEoioJOp8PDDz8MPp+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SHzrU1dJnsNvKJ9ezWmQ36lGod8WuthCszxHarBktiNjvQzaqTd9OrpybpEik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cuXOH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\nVqvR1dXFDHVFRUV5/HDw10CQL9B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- "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "139741807862096" - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], - "source": [ - "# Number of optimization steps\n", - "Niter = 2000\n", - "# Weight for the chamfer loss\n", - "w_chamfer = 1.0 \n", - "# Weight for mesh edge loss\n", - "w_edge = 1.0 \n", - "# Weight for mesh normal consistency\n", - "w_normal = 0.01 \n", - "# Weight for mesh laplacian smoothing\n", - "w_laplacian = 0.1 \n", - "# Plot period for the losses\n", - "plot_period = 250\n", - "loop = tqdm_notebook(range(Niter))\n", - "\n", - "chamfer_losses = []\n", - "laplacian_losses = []\n", - "edge_losses = []\n", - "normal_losses = []\n", - "\n", - "%matplotlib inline\n", - "\n", - "for i in loop:\n", - " # Initialize optimizer\n", - " optimizer.zero_grad()\n", - " \n", - " # Deform the mesh\n", - " new_src_mesh = src_mesh.offset_verts(deform_verts)\n", - " \n", - " # We sample 5k points from the surface of each mesh \n", - " sample_trg = sample_points_from_meshes(trg_mesh, 5000)\n", - " sample_src = sample_points_from_meshes(new_src_mesh, 5000)\n", - " \n", - " # We compare the two sets of pointclouds by computing (a) the chamfer loss\n", - " loss_chamfer, _ = chamfer_distance(sample_trg, sample_src)\n", - " \n", - " # and (b) the edge length of the predicted mesh\n", - " loss_edge = mesh_edge_loss(new_src_mesh)\n", - " \n", - " # mesh normal consistency\n", - " loss_normal = mesh_normal_consistency(new_src_mesh)\n", - " \n", - " # mesh laplacian smoothing\n", - " loss_laplacian = mesh_laplacian_smoothing(new_src_mesh, method=\"uniform\")\n", - " \n", - " # Weighted sum of the losses\n", - " loss = loss_chamfer * w_chamfer + loss_edge * w_edge + loss_normal * w_normal + loss_laplacian * w_laplacian\n", - " \n", - " # Print the losses\n", - " loop.set_description('total_loss = %.6f' % loss)\n", - " \n", - " # Save the losses for plotting\n", - " chamfer_losses.append(loss_chamfer)\n", - " edge_losses.append(loss_edge)\n", - " normal_losses.append(loss_normal)\n", - " laplacian_losses.append(loss_laplacian)\n", - " \n", - " # Plot mesh\n", - " if i % plot_period == 0:\n", - " plot_pointcloud(new_src_mesh, title=\"iter: %d\" % i)\n", - " \n", - " # Optimization step\n", - " loss.backward()\n", - " optimizer.step()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Visualize the loss" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5,1,'Loss vs iterations')" - ] - }, - "execution_count": 17, - "metadata": { - "bento_obj_id": "139740794754384" - }, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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s3ryZd999l5kzZzJlyhTef/99zj//fEpKSpg/fz7jxo1jwoQJZGVlgXtBfuON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\nC6BzBXScAdmFkGiFZCvEEuEKggACHyp5GD8IpQkoT9R9joe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- "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "139741777095760" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(13, 5))\n", - "ax = fig.gca()\n", - "ax.plot(chamfer_losses, label=\"chamfer loss\")\n", - "ax.plot(edge_losses, label=\"edge loss\")\n", - "ax.plot(normal_losses, label=\"normal loss\")\n", - "ax.plot(laplacian_losses, label=\"laplacian loss\")\n", - "ax.legend(fontsize=\"16\")\n", - "ax.set_xlabel(\"Iteration\", fontsize=\"16\")\n", - "ax.set_ylabel(\"Loss\", fontsize=\"16\")\n", - "ax.set_title(\"Loss vs iterations\", fontsize=\"16\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 5. Save the predicted mesh" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": {}, - "colab_type": "code", - "collapsed": true, - "id": "krikJzrLtuvw" - }, - "outputs": [], - "source": [ - "# Fetch the verts and faces of the final predicted mesh\n", - "final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)\n", - "\n", - "# Scale normalize back to the original target size\n", - "final_verts = final_verts * scale + center\n", - "\n", - "# Store the predicted mesh using save_obj\n", - "final_obj = os.path.join('./', 'final_model.obj')\n", - "save_obj(final_obj, final_verts, final_faces)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 6. Conclusion \n", - "\n", - "In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3d datastructure called **Meshes**, set up an optimization loop and use four different PyTorch3d mesh loss functions. " - ] - } - ], - "metadata": { - "bento_stylesheets": { - "bento/extensions/flow/main.css": true, - "bento/extensions/kernel_selector/main.css": true, - "bento/extensions/kernel_ui/main.css": true, - "bento/extensions/new_kernel/main.css": true, - "bento/extensions/system_usage/main.css": true, - "bento/extensions/theme/main.css": true - }, - "colab": { - "name": "FitMesh.ipynb", - "provenance": [] - }, - "kernelspec": { - "display_name": "pytorch3d (local)", - "language": "python", - "name": "pytorch3d_local" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.5+" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/files/deform_source_mesh_to_target_mesh.py b/files/deform_source_mesh_to_target_mesh.py deleted file mode 100644 index 72909bc6..00000000 --- a/files/deform_source_mesh_to_target_mesh.py +++ /dev/null @@ -1,253 +0,0 @@ -#!/usr/bin/env python -# coding: utf-8 - -# In[1]: - - -# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. - - -# # Deform a source mesh to form a target mesh using 3D loss functions - -# In this tutorial, we learn to deform an initial generic shape (e.g. sphere) to fit a target shape. -# -# We will cover: -# -# - How to **load a mesh** from an `.obj` file -# - How to use the PyTorch3d **Meshes** datastructure -# - How to use 4 different PyTorch3d **mesh loss functions** -# - How to set up an **optimization loop** -# -# -# Starting from a sphere mesh, we learn the offset to each vertex in the mesh such that -# the predicted mesh is closer to the target mesh at each optimization step. To achieve this we minimize: -# -# + `chamfer_distance`, the distance between the predicted (deformed) and target mesh, defined as the chamfer distance between the set of pointclouds resulting from **differentiably sampling points** from their surfaces. -# -# However, solely minimizing the chamfer distance between the predicted and the target mesh will lead to a non-smooth shape (verify this by setting `w_chamfer=1.0` and all other weights to `0.0`). -# -# We enforce smoothness by adding **shape regularizers** to the objective. Namely, we add: -# -# + `mesh_edge_length`, which minimizes the length of the edges in the predicted mesh. -# + `mesh_normal_consistency`, which enforces consistency across the normals of neighboring faces. -# + `mesh_laplacian_smoothing`, which is the laplacian regularizer. - -# ## 0. Import modules - -# In[2]: - - -import os -import torch -from pytorch3d.io import load_obj, save_obj -from pytorch3d.structures import Meshes -from pytorch3d.utils import ico_sphere -from pytorch3d.ops import sample_points_from_meshes -from pytorch3d.loss import ( - chamfer_distance, - mesh_edge_loss, - mesh_laplacian_smoothing, - mesh_normal_consistency, -) -import numpy as np -from tqdm import tqdm_notebook -get_ipython().run_line_magic('matplotlib', 'notebook') -from mpl_toolkits.mplot3d import Axes3D -import matplotlib.pyplot as plt -import matplotlib as mpl -mpl.rcParams['savefig.dpi'] = 80 -mpl.rcParams['figure.dpi'] = 80 - -# Set the device -device = torch.device("cuda:0") - - -# ## 1. Load an obj file and create a Meshes object - -# In[4]: - - -# The path to the target 3D model we wish to fit -# e.g. download https://free3d.com/3d-model/-dolphin-v1--12175.html and save in ./data/dolphin -trg_obj = os.path.join('./data/doplhin', '10014_dolphin_v2_max2011_it2.obj') - - -# In[6]: - - -# We read the target 3D model using load_obj -verts, faces, aux = load_obj(trg_obj) - -# verts is a FloatTensor of shape (V, 3) where V is the number of vertices in the mesh -# faces is an object which contains the following LongTensors: verts_idx, normals_idx and textures_idx -# For this tutorial, normals and textures are ignored. -faces_idx = faces.verts_idx.to(device) -verts = verts.to(device) - -# We scale normalize and center the target mesh to fit in a sphere of radius 1 centered at (0,0,0). -# (scale, center) will be used to bring the predicted mesh to its original center and scale -# Note that normalizing the target mesh, speeds up the optimization but is not necessary! -center = verts.mean(0) -verts = verts - center -scale = max(verts.abs().max(0)[0]) -verts = verts / scale - -# We construct a Meshes structure for the target mesh -trg_mesh = Meshes(verts=[verts], faces=[faces_idx]) - - -# In[11]: - - -# We initialize the source shape to be a sphere of radius 1 -src_mesh = ico_sphere(4, device) - - -# ### Visualize the source and target meshes - -# In[12]: - - -def plot_pointcloud(mesh, title=""): - verts = mesh.verts_packed() - faces = mesh.faces_packed() - x, y, z = verts.clone().detach().cpu().unbind(1) - fig = plt.figure(figsize=(5, 5)) - ax = Axes3D(fig) - ax.scatter3D(x, z, -y) - ax.set_xlabel('x') - ax.set_ylabel('z') - ax.set_zlabel('y') - ax.set_title(title) - plt.show() - - -# In[13]: - - -get_ipython().run_line_magic('matplotlib', 'notebook') -plot_pointcloud(trg_mesh, "Target mesh") -plot_pointcloud(src_mesh, "Source mesh") - - -# ## 3. Optimization loop - -# In[14]: - - -# We will learn to deform the source mesh by offsetting its vertices -# The shape of the derform parameters is equal to the total number of vertices in src_mesh -deform_verts = torch.full(src_mesh.verts_packed().shape, 0.0, device=device, requires_grad=True) - - -# In[15]: - - -# The optimizer -optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9) - - -# In[16]: - - -# Number of optimization steps -Niter = 2000 -# Weight for the chamfer loss -w_chamfer = 1.0 -# Weight for mesh edge loss -w_edge = 1.0 -# Weight for mesh normal consistency -w_normal = 0.01 -# Weight for mesh laplacian smoothing -w_laplacian = 0.1 -# Plot period for the losses -plot_period = 250 -loop = tqdm_notebook(range(Niter)) - -chamfer_losses = [] -laplacian_losses = [] -edge_losses = [] -normal_losses = [] - -get_ipython().run_line_magic('matplotlib', 'inline') - -for i in loop: - # Initialize optimizer - optimizer.zero_grad() - - # Deform the mesh - new_src_mesh = src_mesh.offset_verts(deform_verts) - - # We sample 5k points from the surface of each mesh - sample_trg = sample_points_from_meshes(trg_mesh, 5000) - sample_src = sample_points_from_meshes(new_src_mesh, 5000) - - # We compare the two sets of pointclouds by computing (a) the chamfer loss - loss_chamfer, _ = chamfer_distance(sample_trg, sample_src) - - # and (b) the edge length of the predicted mesh - loss_edge = mesh_edge_loss(new_src_mesh) - - # mesh normal consistency - loss_normal = mesh_normal_consistency(new_src_mesh) - - # mesh laplacian smoothing - loss_laplacian = mesh_laplacian_smoothing(new_src_mesh, method="uniform") - - # Weighted sum of the losses - loss = loss_chamfer * w_chamfer + loss_edge * w_edge + loss_normal * w_normal + loss_laplacian * w_laplacian - - # Print the losses - loop.set_description('total_loss = %.6f' % loss) - - # Save the losses for plotting - chamfer_losses.append(loss_chamfer) - edge_losses.append(loss_edge) - normal_losses.append(loss_normal) - laplacian_losses.append(loss_laplacian) - - # Plot mesh - if i % plot_period == 0: - plot_pointcloud(new_src_mesh, title="iter: %d" % i) - - # Optimization step - loss.backward() - optimizer.step() - - -# ## 4. Visualize the loss - -# In[17]: - - -fig = plt.figure(figsize=(13, 5)) -ax = fig.gca() -ax.plot(chamfer_losses, label="chamfer loss") -ax.plot(edge_losses, label="edge loss") -ax.plot(normal_losses, label="normal loss") -ax.plot(laplacian_losses, label="laplacian loss") -ax.legend(fontsize="16") -ax.set_xlabel("Iteration", fontsize="16") -ax.set_ylabel("Loss", fontsize="16") -ax.set_title("Loss vs iterations", fontsize="16") - - -# ## 5. Save the predicted mesh - -# In[ ]: - - -# Fetch the verts and faces of the final predicted mesh -final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0) - -# Scale normalize back to the original target size -final_verts = final_verts * scale + center - -# Store the predicted mesh using save_obj -final_obj = os.path.join('./', 'final_model.obj') -save_obj(final_obj, final_verts, final_faces) - - -# ## 6. Conclusion -# -# In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3d datastructure called **Meshes**, set up an optimization loop and use four different PyTorch3d mesh loss functions. diff --git a/files/render_textured_meshes.ipynb b/files/render_textured_meshes.ipynb deleted file mode 100644 index 93b16c0b..00000000 --- a/files/render_textured_meshes.ipynb +++ /dev/null @@ -1,494 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Render a textured mesh\n", - "\n", - "This tutorial shows how to:\n", - "- load a mesh and textures from an `.obj` file. \n", - "- set up a renderer \n", - "- render the mesh \n", - "- vary the rendering settings such as lighting and camera position\n", - "- use the batching features of the pytorch3d API to render the mesh from different viewpoints" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Import modules" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import os\n", - "import torch\n", - "import matplotlib.pyplot as plt\n", - "from skimage.io import imread\n", - "\n", - "# Util function for loading meshes\n", - "from pytorch3d.io import load_obj\n", - "\n", - "# Data structures and functions for rendering\n", - "from pytorch3d.structures import Meshes, Textures\n", - "from pytorch3d.renderer import (\n", - " look_at_view_transform,\n", - " OpenGLPerspectiveCameras, \n", - " PointLights, \n", - " DirectionalLights, \n", - " Materials, \n", - " RasterizationSettings, \n", - " MeshRenderer, \n", - " MeshRasterizer, \n", - " TexturedPhongShader\n", - ")\n", - "\n", - "# add path for demo utils\n", - "import sys\n", - "import os\n", - "sys.path.append(os.path.abspath(''))\n", - "from utils import image_grid" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "### Load a mesh and texture file\n", - "\n", - "Load an `.obj` file and it's associated `.mtl` file and create a **Textures** and **Meshes** object. \n", - "\n", - "**Meshes** is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes. \n", - "\n", - "**Textures** is an auxillary datastructure for storing texture information about meshes. \n", - "\n", - "**Meshes** has several class methods which are used throughout the rendering pipeline." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [], - "source": [ - "# Setup\n", - "device = torch.device(\"cuda:0\")\n", - "torch.cuda.set_device(device)\n", - "\n", - "# Set paths\n", - "DATA_DIR = \"./data\"\n", - "obj_filename = os.path.join(DATA_DIR, \"cow_mesh/cow.obj\")\n", - "\n", - "# Load obj file\n", - "verts, faces, aux = load_obj(obj_filename)\n", - "faces_idx = faces.verts_idx.to(device)\n", - "verts = verts.to(device)\n", - "\n", - "# Get textures from the outputs of the load_obj function\n", - "# the `aux` variable contains the texture maps and vertex uv coordinates. \n", - "# Refer to the `obj_io.load_obj` function for full API reference. \n", - "# Here we only have one texture map for the whole mesh. \n", - "verts_uvs = aux.verts_uvs[None, ...].to(device) # (N, V, 2)\n", - "faces_uvs = faces.textures_idx[None, ...].to(device) # (N, F, 3)\n", - "tex_maps = aux.texture_images\n", - "texture_image = list(tex_maps.values())[0]\n", - "texture_image = texture_image[None, ...].to(device) # (N, H, W, 3)\n", - "\n", - "# Create a textures object\n", - "tex = Textures(verts_uvs=verts_uvs, faces_uvs=faces_uvs, maps=texture_image)\n", - "\n", - "# Create a meshes object with textures\n", - "mesh = Meshes(verts=[verts], faces=[faces_idx], textures=tex)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "#### Let's visualize the texture map" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-0.5, 1023.5, 1023.5, -0.5)" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(7,7))\n", - "plt.imshow(texture_image.squeeze().cpu().numpy())\n", - "plt.grid(\"off\")\n", - "plt.axis('off')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Create a renderer\n", - "\n", - "A renderer in PyTorch3d is composed of a **rasterizer** and a **shader** which each have a number of subcomponents such as a **camera** (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest.\n", - "\n", - "In this example we will first create a **renderer** which uses a **perspective camera**, a **point light** and applies **phong shading**. Then we learn how to vary different components using the modular API. " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "# Initialize an OpenGL perspective camera.\n", - "R, T = look_at_view_transform(2.7, 10, 20)\n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", - "\n", - "# Define the settings for rasterization and shading. Here we set the output image to be of size\n", - "# 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1\n", - "# and blur_radius=0.0. Refer to rasterize_meshes.py for explanations of these parameters. \n", - "raster_settings = RasterizationSettings(\n", - " image_size=512, \n", - " blur_radius=0.0, \n", - " faces_per_pixel=1, \n", - " bin_size=0\n", - ")\n", - "\n", - "# Place a point light in front of the object\n", - "lights = PointLights(device=device, location=[[1.0, 1.0, -2.0]])\n", - "\n", - "# Create a phong renderer by composing a rasterizer and a shader. The textured phong shader will \n", - "# interpolate the texture uv coordinates for each vertex, sample from a texture image and \n", - "# apply the Phong lighting model\n", - "renderer = MeshRenderer(\n", - " rasterizer=MeshRasterizer(\n", - " cameras=cameras, \n", - " raster_settings=raster_settings\n", - " ),\n", - " shader=TexturedPhongShader(\n", - " device=device, \n", - " cameras=cameras,\n", - " lights=lights\n", - " )\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Render the mesh" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The light is in front of the object so it is bright and the image has specular highlights." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-0.5, 511.5, 511.5, -0.5)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "images = renderer(mesh)\n", - "plt.figure(figsize=(10, 10))\n", - "plt.imshow(images[0, ..., :3].cpu().numpy())\n", - "plt.grid(\"off\")\n", - "plt.axis(\"off\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Move the light behind the object and re-render\n", - "\n", - "We can pass arbirary keyword arguments to the `rasterizer`/`shader` via the call to the `renderer` so the renderer does not need to be reinitialized if any of the settings change/\n", - "\n", - "In this case, we can simply update the location of the lights and pass them into the call to the renderer. \n", - "\n", - "The image is now dark as there is only ambient lighting, and there are no specular highlights." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "lights.location = torch.tensor([0.0, 0.0, +1.0], device=device)[None]\n", - "images = renderer(mesh, lights=lights)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-0.5, 511.5, 511.5, -0.5)" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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gmomi9pd7e30sjhkH889mKMQZcjCETaDw7/7dfwAAvPDiRa/J33zhAm5eu44ja6vGImaHE4yxS+892KJKAwgDvPrKJfz1M8/izJkzePe7340kSfDXf/3XuHhRtjOOY/zVM88CAL7/vX8HgTMRxc7LcdiZCz9J9BX9pSQSJYR2zF+iQjl3yZE7UylNV5VhRLtduMKQxVgue5jcQkgdFC3kcOP8Bm9ihQ+ESEWlT7FGmh4Xc4xy+8uvv4G/+KsvAADW1tZw9uxZfP3rX8fW1lbFOg3g0muvYW1tNVvLmngKLBubrH8KQBDgz//yc1heWcEHPvABnDx5EkmSYHV1Fb/927+Nfr8vdr106VUAwJ2NTawsLFiDwu0EKcSA6Y0RXC1if6GdPUZFABjHSk/MdoxnXcZ0cIm17D8apaz7QQhxQdFC5pfSmuVYNG3sdbbBOhNrjd/7g/8Pjz76KADgAx/4AFqtFj7/+c/jj//4jzG09j9JkgTXr16DyvdJ8RqUGVV4KvLm1rd4qbtSeP3ya3jhxZfwfe9/P06ePAkACIIA9913Hx555BE888wz4oy379wBAKyvr1uiZWSSaG/u+Sgt0EoQEtarc7dbyMfy+2F6yirJr4bAqphr2TlNUVG6NFPQOBKICSEFFC3kUFLeg8UMiWhhoRBCC5U9TGD0EbrA8RnA177+DaggxA//8A8DAKIo/bM7e/YsXNV7F156Gd/R7yMqckZqFrLKaYdnyCSK8IVn/gara2t4+OGHS6e01jh9+jSeffZZJKV9WVLu3FlPX2/dBu46BcTVNulA9tymwPKoQvv+V7wzhhAp2hiipOJVsQVLdUrnQSkvpnJdxn8gGihXFTl+F5X7kr6LWvxnmRAXTMQlh5LzTz7lSMJU5WRHPVosyquJla0rhjp0ujiZ45ldASRa499/4k/xIz/yI4iiqBAsAHDs2DGsra3JF6A1tgYD3yVWr0v6WIgr63oAbG1u4mvPfxMPP/wwFgRvyeLiIjqdjjhbnCSIkwRXrl5zJONKZpn5J+N6E2zvTH4M5dCPryRHG2/sUm07AVeY3vm5+O9MCQ2UPKx9LBdyCviff/lJtx2EzDkULeTwoqyVoZTbYCzilYUdGIUOHB6XoomxmCpD4CCd58WLL0FD4Z577qmYt76+7qzSGcYxFhcX5esSyROFNeRV0lhEgwAIAlx44QJu376DM2fOVFsrJXpYbF7+1iUgMefTwoJs2yCZb41h2t20oEYUqcZwJa9L/t+ALV4MQZN/dtppj2tO5jrvOKYUOu02Ou220JgQkkM/JDnE+EIkQhhCSgy1wxKlb9hCjoQZDQhDfPLP/hxve9vboIR8iMFggCtXroiWX71+A/2NjYaLmKvExU5OTYmz1+e/eQFhFOHUqVPiqFtbW7XC5bU3rmCw3UcrCqum5PetiVOltP1/g9CWGHYxQjLm70bwkKV6RGcfR69aJ9AAAjUSk0F2DSqzU5WenG2HEhter8DP/9KvTNaRkDmCnhZCCCGEzAT0tJD5oggV1FTjlD462tV8o7525SpeufQqvu/7f0A83+/3nYm43U4bW/2B5WmpqZhxGWh5PvLKn0uvvSZ6gHK2t7eLxwu4uH3nDra3t9BqLVW9DlIys/eeSd6LujIu6ZgycmDLFUWJ1hgMhhjEMYbDGIlOkGThrTiJkSTpzsSBUlBKIQgChEGAMAoRmp/DMNtoWWURR1/oq+66gYVe19+AEAKAooUcYs4/+RTOP/GzkBZ6bSVeqrH3ynCsRPmhIMCnPvPnWF1dxenTp8URvvnNbzpHX1leRtQxBItZuluayFrofeZn566+/gYA4Nat29je3sb29jaWlpZKTZMkwc2bN2tFi9Yat9c3sLS8LOd7FLYbJtet4s7ddMeMu6ji/wCtEScJ1je3cOvOOrb7AwziGDrR0Nk9TZJU1JgiJBUuuVhRaEUttKIQrShCFIWj99kjDYIggLJDRKWInfTfmMbP/eIvj3dthMwpFC3kkGMmcuqi6mWYLVgqSPdzDYL0m3UYBOm35+wbtFvEVHNF0ikyb8b6Or747HN48MEHxd4bGxv4yle+4rQ6CBQWe11gGBfTWW9G85nJwLZ3YXQQ0ApaAa++ehkAsLW9jVarhVu3buHYsWMV+771rW85PUE5YRAg0QkqCahejVEnPuwcHV9FkFmR5G4TJ6m4unLjFja2tlLvita+kcvWZsMHahtBECAIAkRhgHarhU47/QGATruNdhQhDIMsF8b8vQh2ao3zv/rRBlYQQgCKFnLIOf/kUzj/kXTPlkRrXL91G/3BEP3BEIlOoKAQRSECpYpvzO12C1EYIgwDtCLPn4gZwcg/ZwvVixcuAoCzAujixYu4dOmSc+g4Ttx7n5RskKplzG/65aTiJEnw6muvA0CRZPv666/j3LlzpRDHK6+8gmvXrjWYXmFru4+KuFBGMuzYiamC4LLfiyJAFmsawPrmJq7euIX1zfrkYhvTKRfrVPQCQF8pbPX7iDZDtLK9VTrtFha7XSwu9NBuRWnSoO0BywdUioKFkDGhaCGHH2PN29jcxs0762mlSFaeqwKFQAUIglS4tKMInXYLdx0/VvQTF15XVVEY4rmvfg0AcPz48Uq3OI7xp3/6p16Tj66tucMtuU3FvFa1U4nygf5ggFu3bxefB4MBLl26hPX19SJEtL6+ji984QvY3Nz02ghk4RBlCZZ83rGjPNJJR5xFHMM4WOwIrDEcxrhxe30iweJDa4041kjiBINs5+L+YIDhMAYUEKgFtFqR41eSevUIIePBvxpy6Dn/5FM4/+RTUCr91j2MY8RJUuQwxNmis90fYGMrFTU37qx7S2bT43aIKD2+vrWFl15+BQBw5cqVyjb9zzzzDF577TWnvUEQ4OjRI/7QRcmDYX2Nd23VEgS4s76Oq9eu4+q169mlaLz00ku4ePEi4jjG1tYWPvvZz+KFF17wzV5QbJjXdC8VL6boEE5r4aT0ZOQ8/yfbt2W738f65mbhIZk2GqkXL9Eag2GMze0+1je30B8O0/BaRXxqtKII/8uv/NNdsYeQwww9LWRu+N9+9aP4b//hT3nb5N/Et7ezBwX6PAOOyMXz33gem9mDEK9cuYLr16/j2LFjuHDhAgDgE5/4RG2uyOJCDyoIgGKh9RhSnNIer1D6MhwOC9tybty4gU9/+tO4cOECbty4gZdeeqkitFy0Wy202u3ywuxKaPbub2LdTKWEU3ZGrxbvf3Gx2Rhb/T4GQ39C8bRIvS8xBsOh4NVJjey0O9yThZAJoWghc8Wpo2t49Y2rtaLhnW9+KH1jL4Rm0mslcqGAIMDLL71cHH7ttdfwR3/0R1hbWyu8F7eN8IyIAtZWVqoHbTvMj4Vt7jGhFGKHGLl8+TKuXLmCOI5r741Jq91CK0tCHc1lJ5tidH9cbUrtXdU3UugoFyhWiMzwyiSJnmpYqI50k7qRKXnVl1IBuu02Thw/5ulNCPHB8BCZK87/6kfx9ofO1TcUExEaZJSGYRF6AdL8lRdffBHPPPMMbty4gRs3btQPEYQ4csTOaSll+5ZDQIWe8YkNXTTJq6Nshnk4YwyWFxfR6zTcY8R7+0wPjHFYG6/OPBb7d2OKSlWUI+8ZKq2qisKwKKUPwxC9bhenTp7Af/0//Mze2kPIIYKihcwdv/zUP8M9J8b8tivmJlQZxHFJtABpyKluvxOT5eUlLC0uyvPlYkUh9S6U1mqfKkgXT62TomR3GiwtLRaVM76p3c8jsttaiqWUV5R1aiDOzHyjditq9LubFkopLHQ76LbbgFJotVqFYPkv/9H/uGd2EHIYYXiIzCX/56//3/jQj/94UfVh8m2PPJy+ycVBltBZwc7L0MDrl18rdpydlNN3343Q9g7ozBD7OTe1jFwUWmtsbGz6d28dk2NHjqAVhkbujcMGe05TyOTvldVHSswtypxtNxMcn9O8m72SLEopLC30sLa8hKgVoRVF6HTa+JlfOL9HFhByuKGnhcwtH/v4x/0NFEbhCik6VNpqPm13++bNHdnUbrVw9sy9gi1S4mr1rdDRaKfRHwwQhmFVFI1JPsbxY0eNGayypWKDEyWfVxqjJ2MLJdO6/LEsEBUqT+C2ybwzYRjuWXlxp93CqaNHsLy0iG6ng163S8FCyBShp4XMNU8//TQ++MEPVk949xOxyb75BwHW76zvyJ6VlWWcOWNs+68B+TlJRiJuQzuVUkgchT3jsrDQAwCsrq5moRfBkIrdPq+Inbzrqy6CHHISUQiDtDQ77vebdJiIfEfcs3efwvEja2i1IooVQnYBelrI3PP0008X74vQUJFLYX3jL3Ij7L1B0oqXy6+/viNbTh4/juOnTo4O5FU3WjdcpD0bnCgFFQSI4yTdcXcHLC8tYXlpCd2lxbJtdjWTy+a6a6koK6FayuF4Kh9Mxc7Swu48kDDNX+nigTP34oEz9+Leu05idWWZgoWQXYKeFkLg8bgAcjmtkKOh4wSvZg8jnJQH7z+HQHKdmPubmJ8r6R2SG2WUD7O00MNgMNiRjQBwMivb7eQPdZTKwF3mAFUvjJk/VJNPXOkjHi//ztaWl3D1xi3PwM3Jn/6slMJCr4vveOzt6HY6AICfYmUQIbsKRQshGU8//TTOP/FhVJM8rTCGnTCaeVlUGO6ovDYMQ9x/7iwwHMK5ekuxHecib5dJa6ytrCAMUwfrpN6WQCncnXmD2oHreg37aza8K+UL5VVC9l4tdXOYCOJtoddFGAQT74qbV1wFQVDk89xz6gTe+sA5/Ff/PSuCCNkrGB4ihBBCyExATwshFXxf8YXk0iysoYMA/R0kez784ANYXVnJQkDlqp/84X/u3WEF02xvhdZYWl5K5wBw7Xr9RncSS0tLuOuuuwAY33pEp0d2UDk8J87b3MTLYvf3lEgDiMIQq8tLuHazWYgoLwvPPSutVqv4icIQ73j4fvyjDz/RaCxCyPSgaCEkIw0Nmbiqduwy3nSR7W9s4Iq1sVxTup0O3vH2tyIIQyCJy/MW+SJCDoh5oMh7QbVEOis/jpXCXSfT0M6kouXkiWNYPbJWPljJR/GF1OzzhdHCbKbgMd5X8oqqOUY2dx8/ihu3biPxbDSXb7oXhiGiKEKn00Gn00Gr1YLWGr/2a7/m7EsI2X0oWgixsZNdKxhJsUabdqeDtZUVvHH16thTnj19L+47czrbpK2Bm8EnAko5HWUvR6QUjqylgiMIgrGfyRMGAU7fey8Wez23Td5kWlvw5R2Vo5+q6J8Gk4i0WxFOHj2Cy1evjYYzHmmglEq32+/1sLi4iE6nA6UUhoMB/o9//s/HmosQsjtQtBCSU2yPb3ksXIujJWoGcTzWdv05vW4X73z07Vjo9SbYbj6zz66+KcwuL/rtKMLakVUAaeXP5uYWxmFlZQXn7juLKN+sLS939gmW4j4CDgUy+piHxsRbLnifxkEpnDq2htsbm9jY2iqqgPKN9trtNpaWltDr9aCUQhQo/NOnPjr+PISQXYOihZAc30Lp2jXeIAImqk556P5zeOjhh6ByweKaS9yjxCw1Njw/ktjSGgjDIjwUReP9+SulcN+Ze3Hy5ImRuGri8LCreaTQVr4XTSmkJeyEVyckC9Em76IXhCHO3n0Sb1y7gVgnWFxYRDfzGi0vLWK518HK4gL+4T+2Q4WEkIMARQshTahbmDWgOh0cPbKGm7ea7weyuLiA/+Q734O2+fyeXIA0yNNwb1YilBsrBcQx7rorFS0njh3D7dvNn5O0sryEt731rei125ZHyFBZYtKt5Q2qXJ9kP2RvSmW7f8EMs69wG7udNu675xTanTbWVlbQ66Ybz/3kf/eP3WMTQg4EFC2ESOSVOlp5vtmXF2Pd748d3nn82x7DXXedAuLYk8hqz2mcz5+/o6wmrs8aiNrpRmjveOsjuHT5Mra2tmvtVErhoQfuT5+LZF6j7UURTc/jVeZJJRxq4EHxqUffPbBOBEGATquN/+ZnPuIejxBy4OA+LYRAqBxSmUtAGcIkq8AxGpVegijCI29+uPGcZ+69B48//i7Lw2IiCSBVbqi0f7FWsLwTOt28bjjE6dP34t6772701Ocja2t4z7vfhXYUycKsuDee5GXT+9Rzuv8AACAASURBVCFcSvVCbHEkTuogT6YW7EBaHfRPfuEXPf0JIQcRihZCXGigUYVKvnYmMY4cPYpWq96Bubqygh94//uw0O14RIDyr8sw7fM1tBJYtU53x11dwZsffhDLS4veGcIwxA++/704cfw4xn7iojbf5ELCZastCOuuzed1Ec4Zw/z8L/2Kuy8h5MBC0UKIi5LHQjuSW41DicZDDz+Et775Td5hFxcW8Pe+/33pVviuxF0lLfC+fI4sBFO010Lz8oEoivDIW96Ctz3yCJaXlmRbFxfwwR/6ATz00INpCKuulNmes9AdpgjxhIDE8NokIglOWyaoOyKEHBCY00JICUcli7PsGWXhEsd49NF34PkLL2J9faPU9NjRIwCA97/37+LBB86NqoWsqUvzlaplPHk1JWOy9xWRZfVPEiwtLeA9j387lpcW8eLFl/DG1avoDwbotNs4c++9eNe3P4a77747ex6Si/xeZa9SCbSUmGtjP1HbbNqkSqmywZ48XZNwGCHkYELRQkiJ/Ou44FHJT7u0gAaQJHjgwQfw93/4h/AXn/srvHHlCqIowsMP3I/HHn0HAOD48WOpizPPA5EW62JsQQQAlpAxBVYDoWUyjLG6soy/9dijOHPmNG7dugUkGktLi1g9dhTLvR4CX3KxRnVul0CpK1cu9c3aNUnSLbrYVUuuOShaCJlVKFrI3FPdvl/ADhVJX+PzQ4MBHnzoQZy9526sb2wiCEN0el108n1RspySUjWMwytQtcNQT469SCrjSNVE+ZxKAUmCTruN0/fcjeSuk4BOn+Rc5L/4UMYEku2e0mMnvutqaotLVDbUNYSQgwlFCyEmlcVVl70JJc8C7MZZGw0MBmi121gz9zQplQob/ewIj02x6FqLuehdkQ7Z3o6KwUU+SWCu6ra4cgoPW3gJYRozt8WlGvJ+omAR7pf4AMl6L44ee9dhQshBgYm4hLhKa/MKnpJQGGOsfNG3y3ft9r4N00zEuXX51d5VFzAExARVOKUQlGd684PvfuXhNdGUhj6QQp/ktjV24QAa3gcmEkIONhQtZK5JQ0N2wkiGqh6q3xrE8DBUdk8z2hXjZIuudyHNO7g8EEa2arGNv9S0QWzEVf0jVQaZ5zVQbHRXN7BLZ5Q8PD6jJqRpzgsh5MBC0UIIIYSQmYCihZACweOSJ3eWnB2OzUCU3c+R+2LvYltUEAkehfypxxUvhu2NMOZweW3qHBZmebFEXRjL68UYw8VR8gjZRhlhsIo5jt+LvTsuo0OEzCwULYTYVASCskIaVlKo2a5RvoSdOGOFdqSmlVNKtkfMPdHVZr7zUqWRJyWnlBhbCac1VAjO8W2jjNeKiDJ/L2aYTjmbEUJmC1YPkbllVOps5Yt4E17NKprcQ2L08Zb4WjkuldJeIYlWPuDGdEoU6S4OMWVWH5W8SKZ92XlliCuzgkpJ4xlj5JvO1eWT5KKnNBfcfRTKY2rrd2Gm+tC1QsihgaKFkErcQAjFiEJDWlh1WSiIgiExPBjJqF/x4sp4tY5r441dhp0v6lKpsCuMZAutUojL9HAI5hVjCJ4eM8LjFS55sm9DV4gkmMSIHF0rhBwWKFrIXJJ6WcxV1Leiml4Yq40Y/tDpgwXzV61RESp5KXTxmtsg5WpYY4tzW+GiYr8T4X3JC4LyOdOLUip1ViMbc++JfW/MMSveltFw5XwV8YQxhB4JGdFzZc1nCkXJljrhRAg50FC0kDlG/FpeJV8883alzeIM8VH8JEASZ+Ik/9HVfqVXWGO67JG8LXokPPK+RVjHEikqKIuSICgfVwGAAAhU+loSPNb1m/ZU8nEsz1R+D5073ZrCxgoTSWJFK1S8S6Ydrg0AKVgImWlUze6QDAaTQ8n5j3wY/ufZWGGe4u8kSZ/MrI1XHafvk+x9SaRoq382NuDw0kxCbdyl9FIWMaY3JhiJlyAAVFg+HgTlNsVwyprD9n7AHx6SjkuektLuvD4BZA0o5esAOP/kU47+hJADgPgHTk8LmTvOP/FhY3G1F1bL65HE2U/2lOP8fRIbokXwpowGkY2YVpiicADp8jElNHKaJggQZXhZbOEShKmgAbJjodU+GI1r6BmnSJSO+7wo5nsxSmUKFlPc0M1CyKxD0ULmEDPHIQ8/ZJ6VXIAkMRAPgHiY/iRx1t72pOTjNZ8SQP362VTUSG0qXou6sQz7k8ybUSQIo7zoF8IkEy1BWP0xvTKFajHCV1IoKfeiVKqMHPko+fu6e1Ty1qBBB0LIQYaihcwhhmdFZeIjSVKRkgyB4WD0Ps9RGUegOKYca90cW3iMMVajto6E3zwpFpnnqeSFMcVLVBUypWcgWeLE+fgBOx/Fledi2FopI2+ibgghswBFC5krRnuzYBT+ifvAYBsY9kehn52KFImm+RxN+/qYVOQ06mcJGp2kneLhKB/GFi9hlL7PvTDmMHaujdeeGuNKoisTK1o6TgiZRShayPyRL7TDPjDYSgVLPMgWXyP/o4nIaLIG+tr4+o6zvkrhJymcUtfXlzBba0AWYovjTMAYOTCmeAlb5byYfOI8p8hM5nV5nMS8nVICTWnoog0fmkjITEPRQuYLrTOxspkKluEgzVMR26K6wNV9zvuZ5/Y0rDNB/ybX5EMUEjq9r3GWH4TByPuSe12idto0iDLviyuMY1YPGWKmNF8Do80qIu8TqQkhBxWKFjI3nP+5fwL0N4Ht9SxnJYbTszJpaMXuP80qoXHyXKZxPU3xijMjYTlO0vBbnAmYYT89HrWAsJ2JmQBAmPYrPC65ULEmcM3nuthSQvEUw36EkD2DooXMDxs3UtFiihVgOvkfrjF2IhYabr/iPLdf6RvOefWo6ipJAJUl88YDIOynYaOoBQStVMDk1Upj4VF2jv1aCCGzA5/yTOaHrTvZfivWt2w7R6WOLH1jx+te3VySpySfu8l4e7EuS7Yox/FSp3wjvqy0fLAN9DeA7Y30dbA1KjWX9r/RdTci96BZuS169OaXfv5/qr8+QsiBgqKFEEIIITMBw0Pk0HP+pz9UPjBpNY+vTdPckqZzNQ032ZU/49rgap+PV7e3zE7uYzGfBhCnVUdJVnkUD4Cokybr5om75v4u3rCRVDlkf1ZIEua1EDJrULSQ+WOSEuVJN1RtIkycZbwee3zHx7FBGmuvEnilOXQySpLOxUsrEy9By7hPDQ3TgPvxATu2nBCyx1C0kEPN+Z/60Bh7fWRIQmKvq29c9pniaVqeFXvuaVc8NR2vVJKclUvrvOJomIqXsJ1WHnkfmGigxjWCEHKQoWghhxtpMW6yf8pO91ipQ4pMNBFRTcTFTsutJwlb+cax7TFfpXbmZEn2rKc8dNSK07BRGBlJtY6+jX/ZhJBZgaKFHFoquSxNwkJ2u51+QR9HWIxb3lxnpzmHa4yxvSAT4Jq/0XhGmXQ/GT11u9VNS6TNJ0r7Bq9sfNfYAELIAYKihRxKKoKlCVKprr3wm8eajjnO+aYixjWOJBBcnpdxIieThqImFVPSQDoGhtsj4dLupeEiIA0ZAULIKNv9VsEIKSnqFUJmFIoWcjiZdmjEJy6azu9apF1CZZwdb007XUUxLvEwjgfGJ0Bc19vU09Lkd5Yn6uos36WdDR51RsLFHlC8Tua4EDKLULSQQ8f5nxaSb13sRt5Hfr42Z2PC465zO00antTLk7f3eVWajtEInSbn9nUqXID0tdXLdtJ1DShlOhNCZgmKFjLfjOPZsPtox3uz3aTrYhNPDlBdh3fCTsXOuP19Ibe6ewuk4aJB9vyiYs+VXjlUVOmbHRinbJoQcmCgaCGHirE2krMZ17PR5Pyk6+Kk80k0EQBN+o5rS9N++a77LgHmFW/ZE7pjDWxnjds9I0HXmEMZg1GvEDKTULSQw01d3sROFvRJk1P3AjvU4/OGNL0Hu3Vd43qkxPyZJE3ShUo9KK0uoEJHrlDDPV4IIQcOihZyaGhUMeQI4Who6ERDaw0NDQUFpUY/u+KpmOa+Zz5PhfTZPpfdAwBAUj6ntJreNefn7flrE3AhC5BSG50Kl22VelpaXUOcGAOUjhFCZgmKFnK4aFSBgtJCHccxhoMBBoMh4ngIQCEMQ0StCFEUIQxDBK5nizrzLTx2jLvv2bRLks18GA1orZEkCeIkRpIkqXjLhFsQKARBiCAMEATBSMA0LVf2ebbq7DRp2kcn6ROiVZDmtoStslel+N3T20LILELRQg4FxXb9dd/w8zYaSJIE/X4fG5sb2NzYQH+7jzhJEAQK7XYb3W4X3W4XnW4XKkwHVvZCJy3IdYv6JJU5k+ISLAB0opEkMQbDIQb9AQaDPgaDIZIkhtYaSqXirdVqo91Of8IoE3BNBUZTj88k1yjdew0AmXAJIqC3BCAcCZRCKCos9HoTTEoI2U8oWsjhQAqzuEImmXdha2sLN2/exK1bN7G5sYHBYAhAIwhDtNtt9Lo9LCwuYDFJsNBbAABErQiqqD4RbJDe+2hSsTSNsYzxtE7fxPEQ29vb2NzcwubmJra3tzDo9zGM48ITEUUR2u02FhYWsLCwiF6vh1arld6DprZJYbBp5ce4ysqTIdBfB6JWmpgrGBsEDu8ZIeTAQtFCDg9NvtVnHpbNzU1cu3YV169dx+bmBuI49S5AKQTDIeI4RhzHSHQCFQQIszLaIFAIw2gyIeEqU266kVsdDfJjtNYYDgcAgM2tLazfuYP1O+vY3NxEv7+NYZyGiHLREiiFqBVha2sLw+EwzXEJUjEDZPkudbZKYTCXl2RaXiiN9CGL2+vprrlhhPThiaNOiqKFkJmDf7WEEEIImQnoaSEzj7dqyPr2rqGxvb2Na9eu4sqVK9jc3EQSx6NUD53W0CRJknocALRaLXQ7XQBAp9NGEOpyQmqDyhxvvs20wj81bTU0hvEQW1tbAIDbt27jzp3b2NjYQL/fT71NSZLei8zTkgCIkwRJtnmbUgphECJYSL/vhEHo93Y0sXe3yqihgcE20N8AeiuViX72F35xFyYmhOwmFC3kcOIQCvEwxo0b13Ht2jVsbmwgTpJKJ40s72M4RL/fx9bWFgaDNKSitR7lczRlWovyOALADr8gFWKDwQAbGxsAgDu3b+PO+p2RYNFWCXAm4GCcC8MQnU4HrVYLABC0gzQ5uekW/k0TlKdVBo44FS2tLtBqT2FQQsh+QtFCDh+OHAmdaNy5cwdXr17FnTt3Ck/KiPKCprVGkue2JOnOq0mSFJU1QpfJFttxPSjSvLXd0mvpb2/jzp07AID19XVsb28jjuPa/nml1fr6elFRBSAtCVceb4vNtNvVjaEBDAepcIms8mdCyMxB0UIOH7a3IVvo4yTGzZs3sLG+IQiWKhpAku1hUkrenEaox7CrJLAm2a+kyVSJxnAYY3NzE5ubmwCAwWDguQ9VQ3Tmqdna2kJ/exsA0O10EYTByPvk2xfGtH+SSqJx9uAx59MJMNgE4sU0KZe6hZCZhYm4ZKY5/9Mfqt/YNBMZm5ubuHXzFgb5Q/YakO9VEgTp5mqBMhbonEk3VrX3dIHw2ccY86ZVQ2mJc7/fz0JCw2pIqGRIdbo8xJT/VESPL+zj2r9mmt4X1/zDQZrfYpw//5EPN5yYEHJQoGghs0/NYqaTdIv+YbbjrXuhljrr8oZsklLIF+O6YV1tbM/NThdxYQ6t051/+/0+hsMhhsMhEq3T62tKmuyT7iCcj5GLlibC0fauNLln5tyToI03g63RZ60BBZx/gsKFkFmC4SFy6MmFRp6LopRKhYsrlKGMWI1SUEG6nT0AdxJuk9yWaYYlfKESSyDo7H9JkiCOk5FoayxYssGE+VRdaMs81lSY+e7duDk9ZrthfzRAcVwXwuX8k081HJQQsl9QtJDDS7E+ZYJDAVGrhSAIkMRxaeHKW6bH8moYhSAI0mTTfDO1QFgtdyJQprlbrBRmMsZRatI81FGnXPQFKig++0SNs4Jo0rwdV75ME9GoYyCJ0+39i3OjRhQvhBx8GB4ihwt74TZ+lArQarUQRpH1DCEhs1alC3IritDpdNFqtdBqtdLFWhIo44Q67L7mq/3el3JinzOv1xonfWp1MMrNCYKqgqmxXyFNRA6CAGEUIoyEZ/o0wZeoOy6upGhRLCXp9v4KDi9TeowhI0IOLvS0kJlF3FTOs3hGUVTsMTIcDsubygnDRFGEbq+HhYUFtFvt9LjtaanbOM5s0+S8VP3iomHFjYLKtt4P0Wq1EIXpIwn6SpWvXxxvZJAKAkTZc5miKNunRTkufhzPkS3SdhJGq+sfD4EWHC4nlhURctChp4XMDa12K33wX/bQvyAIRKdJEARotdtYXFzE8soKFhYWEEURoiiq5rRMUtFiJ6FOkoRr40vyBRCoAFHUQrfbQ6fTRafTTa9H1fwTkD1bKFAKURih1W4Xwq/Vao1KwB3zVt67bM9fd3L9+Vz2fTA/xwOhQbUtvS2EHEwoWsihR2X/i8IIvV4PS8vLWFpaQrfXQ6vdTgVJGGaeiDa63S6WlpawsrKK5aVltDvtUUjFxLc4ut6nBpVfXe3Gocbbo5RCGIXo9broLfTQW+ih0+kgDEMrVFYdN1AKQZh6abrdLnq9BbTaLbTaufBzeFp8n23b89em/aR76spvMT/HA5RdQO62FC6EHDwoWshs41sMzUVMAUEYoNPtYnl5BSsrq1haWsbCwgJ6vR463S663R4WFhewsrKCtbUjWFtbxcLiAqL8qc75j+nVkDZOs2mSJOpqtxOs6w/DCJ1uF0tLy1haWsbi4hI63Q6iMErFh1LlNKBsj5ooEysLiwup2Ot2C89TYHpqpHtiX9u419T0nvramugmvzDQ40LIAYU5LWS2GSPnQymFKIqwuLiIqBWht9DDdvZcoSRJy6FbrTTvpdPpot1pIwrtpN0G845pl8g4eTDmZ1eJMbLE4lYLC4sLaRedIFAKG5sb4vOHAhUgDMP0nnS7aWhtYbHw0ORjjlU5JSUZjxsem2QH3fz96imrjZbzW/Kyd52WRLOiiJCDAUULOfyUKppV6nHppB6GbqeLOImhk3SzsTAIEEZR6n0IA3+10DTyNpt6XerOu0JOZhM1euBh2lRl+Tut4qGQcRwXC3kQBGhFLbQ7bfR6PfR6C+h0u2i1omqorInNJtO8f665m4ghZ2jMrIqicCHkoKBqdgfdqYOakF1DrB6ScCRpaq1HP9mJfA8S0YMwLjvZb2U3BVF2DxKdbsnf7/fR3+5noiXbMTi7D1EUodVqod1uIWq1SqGkgt0uupnW/QCA4+dqBvdNlp6jeCFkTxD/EJnTQgghhJCZgJ4WMrN4PS0+L0PTxFi7DWraTTr2NBhnXxTjrzrRCZI4QRzHiOMYSRIXuarp4wvSvJb8oZFpsu4UvFB11Ds8xr+3x88ZfXR2Hxpci5D3Qm8LIbuO+JdJ0UJmmsYhonmjbtEHSiKnFCYzc4CybfsVIOd/TEOUNRGErn6uiitprGPnJrA1T8iVx6R4IWTXYHiIkLFkuFTCu1cyfqfzNC0xzhZj26sShiHCIEzze6RNYOzN7Ny74vvnbrKjsDSmz6sljPX2t729uTetRObScdxPlkQTsrfQ00JmGtHTMs2QzG4nxe7WGOOEx6Y1Z9Nxdrrz7SR97QRcbcSYXBVErnJoD/S8EDI16Gkhc4L0Ddz2DEw6Vj6eC9eOrnaBStOdXutscY0xTtjEN7cvxDTO/Wy6F4trg7pJQ0iVAWw7pI1j8vPjun+A80/87Jh2EULGgaKFzDTnf/1j9Y2U8TMNxhnHtX9IzfYgJXw7zfrGkDZ/bSqKJhF50wijmfvNuDavHXPsb3vnO1G5sebTqbU2PC8N0NqyoazIGDIiZPegaCHzi+vb/E4W3zovwk68PS7vyTi2NBVckrCyRYRrgztp6xPpvY19f8YRdp4xv/Ctm/6JlRK8Ko72Om+v8R8//efOIelxIWR3YE4LORRMrYpor3M+mpT27gW7OddeXoc15zve8Q48++rtye3RQLGl/wQwx4WQiWFOCzm8NAoTmbjk+E4FSJPjdWGbSfNP6vB5esZP35iM3fwaJNzXZDisths3vKfzWFXV+E9+5i+83RkqImS6ULSQ+WQ3vvk3rdax8zWajJOPVdfGbGvPURfyqcOX4OujSRLupKEzaZ5snHc++k4898amMUeTCYx8lZJ4lBORvuc73o3f+J2Pw3cBFC6ETA+KFnJoKHlbpvmNvul+I9JnV3KrKx/ER5M25vjTGtPXdgcJspVx6sSchEucAXjm0k1L6KkG46tqDpEvHSZIN9975dJlvHLpcrVx9pHChZDpQNFC5otxPQvme1dJsL3gNhEMuxUmGbdEe5J2uzG3OYYrcdd3/y0ee+djZZucIbcGilTpUVPBW7O6sow/+dRn8Cef+kx5AsszReFCyM6haCGHisLb4vuWPG51kCRMXO2ajNOk7TRpGpLZjdCN7575hGDd+5rxvvjKdWNwQ3jY7Zv8InKxojCqMjLEy/u+57uK92moyGhfzJNC4ULIzqBoIYcOZ1Ju/s3XtxBqq+1usBOPxiQCQkoElsqSXQJvtzxHrnHHFZXWeI+987FMXNQoxGKPFmkejWLvFqkk2vi8uLBQOvUv/tXHsvPZwJJgIoRMBEULOdyM803d1a/J8XFokrvhq/IZ1wZ7Pmk9d43bNI/G127csJFrvxfX3NZYX/zWjYZGIBMk1pzmudJcDqM1cP/ZM7j/7Jmsm8Kt27dRdtGNOP8R7uFCyKRwnxZyaHHu3WLmN9QtjNPwuDSZAzVt6sbfSf/9xnd/xr3/9jOGdjT5+G2L8BCAn/yJH0vLpUtdRmNwDxdCvIh/bPS0EEIIIWQmoGghhxZnbss44YdxvoS7Po+ToDsJvv1XXHkqLnsnzSfxXX8ddaGlnfp7tfGmMlbNjS/dFyGGZHmq77nrVPH+N37n95xeFkBzq39CJoCihRxqvDvlTiOc4tt3ZTeDq03HduWpuPaJsXOAmswjJfWOe29NceDYd0Vsb34uhYaMBsp409guXe5rX18xZHnA7/ve7yp9/t2n/9BsbL2f1XgeIfsHRQs59Jz/9Y9Vxcs468U4Zc7jeFiazlNXFiwxqWiyxUNdGbTUZpK12MwvamK7PceJc4ZtLsMb3BBtXJTpRTHfVx6umI+d9nvbm99UHN3c2kIlb9Asgf4IS6AJGQeKFjI3eL0udfu5+I6Z7DTMM80xfYJKOp6v9bZ4mKTMWprTN4atM5pe87H70h/UiYqGg5ql0uY4xf4szo5Fv3c99o6SUPnN3/29kegx73HWjXu3ENIcihYyV4heF8Bf7jtpyGRcfHkok4xj03Qtl6IYUhtfLo1rLBdSybGEef74OYz2UGlYmz1usaS2PlSuVx7wR3/w/aXPv/G7v5cKmaI/CzMJmQSKFjKXjP1UaJMm62PT/U2kPjtNdTCF1U4TYpt6WaTcniYCpEn+inQ+z1/RGsUGcXW2FTkthtej1K8mpKRNZZXnvKjKIUBjbXUF7VarNNJvffxpDPOnTlveIHpbCGkG92khc493PxeXJ6HJHi/TYCdz7IV9Tea3X3fK8fuE/U/MCZvapz2hJKGteRHOXB/jvAb+xe98DMqYIwgCvO97vgvHjhxBKwqhgtH3Ru7bQkgJ8a+MooWQDKd4mRRXZdFujenLP23q+fG1c4m4nV7fOPOaFUJmwq3Kk2ezc0rqPM6kY9jqHErjhRdfxqf+4nOVM6sryziyuoLT99yDB+47UxI2FC+EAKBoIaQZhXjZKy/HfnlE6qqDpiFQ6ubAGDYcP1ejQcY3UGtdJM0G0jOGzCHNOca4d//y9/8A/f6gMm8uVJYWFvBjH/h+KJV6XShaCAFA0ULIeIwVNpoG43hmpuU9mVafnY5ht68TLHZopzKfwwAjfKOTBOsbm7izsQFkrZeWFrHQ65U8Hzt11ugkwW/+69/3tgmDAP/Fh340/aAUhQshFC2ETEajsFGTvA1Xsqrvc5Mxxp3DxyRiw2XP1HJYzgn5J9bEjYTF6EOSJLhx8xYuvvItXH7jSnosjnH82FG86YH7sbqyjCAIRt4Vnf1ylarPhRHO/9UzX8KXvvo172V2Ox0AwE/86AcoWgihaCFk5zTOe2kSPphyusWeekiaeoV24hE6ds6o9lHVhk1CWELYKIlj3Lh1G89fuIiXLl3CxsZm2lRrtFoR7jp5Am956EHcdfJEKly812H+MmHYZgiX7L35MEUff/s978KD5+6jcCHzDkULIdPGK2L2SkS4RNBuJc7uNmM/qRnGdZmixq700YAG7mxs4hsvXMCFl17G7TvrlaHCMMDRtTU88vBDuPvUCXQ6nXK4qLFbrXzulUuv4k8+9ZlGl/OT/+DHcP5XP9qoLSGHFIoWQnaTqVcf+djLqp1x1uadeFZKlUENx3HFwzTEEE6/38eFl17BV7/xTdy4dcsxpIYKAqwuL+O+M/fi/rOnsdhbQBiFlngZh/SCmnpbzt57Dz756T+bcC5CDgUULYTsJXsqYnKaembQoF2TOaYhniTPyriVTbVoaA1cv3EDz3z5a/jWq5cRx7G7dVbd02m3cerEcdx96iTuPnUSK0uLpb1VCoPyjedq7Pra89/EZ//qi40s/smf+HGGiMg8I/41RXttBSHzgr3r7lgiZhwPhnmuiZiYNI8mb2O2m1Sw1IWAlMNbYifWmrvUmrvTVuxSSJIYb1y9jhs3b3oFC4DCo7Ld7+OVVy/jjavX8NobV/DwA+dw8sRxRGFYGtuLYc+bH3qwsWhxPSKAkHmG2/gTQgghZCZgeIiQA8T5n/rQzsM2u5lsO+nYdZ6VHeWwNDinNe5sbOCLz30FF19+BcOh39MiEYYBjqyu4oFzZ/HA2bPodNpj9B5d4L/9xKfw6muvN+p14cKFse0k5JDAnBZCZoH7779fPB6oAP/p3/8AAKAVRWk45MqL6clJ81R223TengAAIABJREFUo8KoECgNY1q1G8VZ3Yr9UhztHPuovPb6G/jCl76M169cRc2/e1563S7e/NADeOThh9Bu5w9FdOwbY+7zYkSyfuN36xNytdZ48cUXJ7aTkBmHOS2EzDK9Xme0b0j+92x7MMzSX521q+x1YrfXwJWL5fHMNbi054g9jEN8iNU7DhvEipysrd1FYXTAmbNTPRHHMdY3NrGxubkjwQIAm1tb+Mo3nodSCo88/CBarVbVmJLHS1WuQSlVa4dSCuef+DCTcQkxYE4LIQcIl5cFAE4cO4ZABQhU4N7orDiu0sW7EDBKTuzMF9Xj58oeEmWMlXs1ivbmlNnqrGvamQd9a7W50JfG0XJfbR2TxtYa29t9XLtxs/IMoEnZ3u7jK19/Hi9cfBlaJ4JR8Eaw/vMf+5Gp2EHIvEHRQsiMsLy0WK3eMbEX8IJcACh/Q222t0SO2RX2ccOT0CSsVBIilh3K+qytZraIMe+H1tb8o7E2Njdx6/ZtDOO4OueEbG5v49mvfg03bt62znhuQnYqipo5uT8tPCGakHmGooWQGWFpcdGrWVLPimNBVvYHKUwjjCe2cVgwlhZQqNphhprMZlKOimSDmRczCi8lWmN9YwN3NjayUufpZCkrAOvrG/jSV76GOI5ry6ht3v6WN9W2ef7CSxNaR8jhhKKFkAOCLzQUBgFWlpcwWugdMREtLMgTOxa04W2p886gPpRTa4yqvs3zcpqMpYxjhlcpjmPcWd/A1nbfM/dkaAAvXXoVr71xBa+9caV8v7TZqsq3P/r22vEn3oCXkEMKE3EJmQGCIEC71bIWc1ieD7lqplIGLeadOHazM3NkKuEXewxzcIxEhLbGaYQ1vydXt47hcIit7T50Yuee7ByVjf/CxdQjctfJEwiUMq7ZY6RSjRJyCSEj6GkhZAYIwgCdtrEviFJVz0bhkahZBMXokEONmI6W2q/90gKtqlpI6lZZuG2FJXwU7TFDROnLME4wjIdTFQf2WK++9gZefe0NbG1tW+LO9oqZgwD/4Ed+aGo2ETIPULQQcgDwhYYAIAojo9wZcMRlrM+C16MOMdEW7lwZkfpE1MqxylOUHR0aOWrK1TtaJ9BaT1W02A9O7A8G6A8GuHbjhmCKQ7gooNvtTM0mQuYBihZCZoBOu5VuKOdFW+JCTkwt5aeUFvLcQyCVJltqQUxxKVSCaFq1vWmHOaFtt22Mdsxh9S+0i0pDNjvID6kTPHki7vWb1pOjxw6LEUJ8ULQQMgN0u930232xzkvf3q24jzO0Y7SrHHd8tBdtZQskY1Jn1ZF0UBnnPVVJ5oMR8z1oKsOpkZ06tVEDUIFCu91uXGYsWloTGss9Of1+H4l5rxokEAdBwLwWQhpC0ULIDLC8tJi+KdZ57agUMkM75TBJ5b2E6NlAWRCUDXF7ZGzvSiUHRzSgOm++0Z23kshob3qMMpvDMEQYBLXiY1JUllQ7HMYjAeLMwS0ffPe3vdNp10KvN1U7CZl1KFoImQE67TZU4PCEOMM4TRZoQSSYfc2wjZIEQ+5xsUM9GIkmu4+3LDsTHdI12SLMKV7KDQIVIApDtFqtNEy0i0RROBIgCnIYy+Lh+885z73loQenYhchhwWKFkIOOGEYoNvtWN/GVfmt1pXDVexKHMMVkFfw2JU8dthGrDoyf1DVTZU8YTkpdWSXXXFkV0e5bEFVJCgFpYB2u4XFXi97TtDkuMI4gUrzZnq9rtm6HMZy9Q3d/wy/6cFzE1hJyOGFooWQfcZXOaQBhEGIxV5vVABkhl0KsSIkysJuZ+XBmNv6mxU8diWPvdjaybzFcSEeJC7UplByn67aWb2Eyr2whJ1Cev+WFhexsryMXq+LVqtVeai0yx9S1UCyKmy322i321jo9gxvji2ymnl5TGHU6bC6iBATihZCCCGEzATcEZeQA4xCmifRyxMyzXSNoipIlyuEzATQ4tU+4JmwIK/UkdoInp1x80WaNrcTWsX3enQvoEqdoijE4kIPx46sYhgP0Yoi3Lp9B3EcYxjHyFOFivxZw9NR3FKti91rlRAGW1pYAACsLC9WPUPjXBvqK5UImWcoWgg54Cz0eujlYQJhKxNRWEhoc2HP+uViw1w8i/dWDMXqWjknGWjnpoy9INf1yZWG4x4ohSBIdxM+fuwoWq02Fns93F5Zx8bGJvqDAeJ8e3+d7rcCBQyH6cMP8510k0QjiWPo7F7pbF4FoNVu4dTJ4wCAxUy8lMyr2GUctMNdpumeqyZkXqFoIeSAorVGECgcXVtDq90qC47KIm0thCKCt0VywIiLP6rCRWwvumWyt5Msw8qx8APyCSUej6IIi2GIVhRhdWUJd9Y3MBgMsLW9jSQTLcNhjDhJMBgMkegE/f4AcRyj3+9jEA8xHKbvtQaSJEGcxGi3Wjh6ZA33nDoFAOVEX6dIs10r8pW/6cEHcP7Jp+SThMwpFC2EHGBarTaOHT2CVhiWT4hVPNIibng+6hwWPo+AOedeuwBKXhwzBOZy91TiLUURU7fTQRS10O10EMcxNNIHHuYMBqlnJQ8dDYdD9PsDDIZDbG5tYzAcpBvIJRpKpWLorhMncPTIGgBkj1qoq+Syb7bsannXY+9wDUDI3ELRQsgBRSmFo2urOHpkFap47pBrJbQWQinE06Db6LNLADVQLJKHQQxrNcA1pa/CyNUp2yAvCgMAAVpRlOaxZKG3PJcl97wkSZL+aI3BYIAk0dju91Oxo4FEJ2i3WlhbWUa7bXpYMgFpVmdJrqzinpRtbbUiLPR6O9rBl5DDCv8qCNlH7veUO3c7Hdx18gSWFhbrkzOLcJGUPKtH551JrXa/OqXg2TBFEhCNcm6AdA8XIyTkDD25RFpNO6jRHJapKhM1QRRmteZhVt2t0e10kCQJlrGYiZk0dBcEQXWn3Vwsakm4SGE8jSAICrF0/5kzuOvUCXcdNiFzDEULIQeIvEolCkOsrizjyOoK2q4N0cxFsU5sOEM7HlHhdaz4hIE2vA21A1lD+nJYXPM3tdOYw7RVyrvJX7QGggBKawR5iC4XM4AgJg1xIlZs1buN3vaWN2FpcYGZuIQIcJ8WQg4YSil0ux2cOnEcR4+sVbfvHzU0dj+zXwV8G72ZGbZihZC1BVvpo52dm4kglbtK7PM1OJtP4Hqo20ZfeqSAbUyeP2P8pJenBJNsd5bdwLeVXcrK8lKWG0MIseFfBiH7SJh9e1dZaW673cbK8hLuPnkSd504nj5zqBJuMRa9Qrg0yJItvB7mWJUGDmeAFauxQzfattEeX1UFhLR++3Jf8jmkNd8lTurCag00SzW1J/OiOD1CPs+KNGCax0IIqYd/KYTsI8tLi+j3+wCAKGphcaGHo2urOHn8GNbWVtGKIisdQkjudGyqVogZO3TkSACtT761x7bGqCT/+nJdhKlKxwRblH09Qn6Izv7PJ1ZKl2S31UJlkm2jR9zZ81TayUqn2+lge7tfMyAhhKKFkH3if/25n8GZe+5OFysFtFupl+XI6gqWl5bQzr992xEH8aDxWiSxusJKLovq8i2E3A9Itjlo0s5Mxq21z4wjuYSEkYRsd1OSuFEQH+hoa8ImG+WZ+Tw11VxrK8u4eeu2fzxCCEULIfuFUgr3nb632CckiiJ02m10Om2EYZiFhVTVM5B2hlMB2I6R2nCGhyZ97MiQJBwAj9CxPSbChM5xJa+SqFAsjWeokJLnqcabpBxtnXjElHHwrpMncfGVS+I5QsgIihZC9gkFYG11BdA6i0goBEqlYqW03b7ZSVrQHRVA+Tf9unCGb42UhIUtOExPRuFdQHZcqCyq2GqIBOn5Sea45h4opXnNfq6KIG3YJNhih4VKT8G27Co9EmESgVFWlqsry+l/C8U5ChdCJJiIS8h+oYAwCBCGIaIoTPf7CAJjsaxZtExPgNRUZ2P4cm+bkI9TeEzMk2q0iNvtVe7FsBJyzXalU4JHA7bA0NWImGVO9YS2zudvrHbesJl17UXlkNVp3PubJRd32m1893sex3e/5/GSMeef+PCYAxJyuKGnhZB9w861yFdxadEVVtTRI4hlD0xD7eNOSrX7e0JMoofCvD4psdYaQxw7v0Yj9OOsMBLCQCXviULFm5K3EcdzGFvkDEnNBBvMPuKwGr1uF71u12cAIQT0tBCyL8jfoJ0r4ehtrmtyz4YvimB7MgCISabFuTp14+hb8aZI7RqEOnxN7FCRKUq01agSVhI+284fZR8E3GXUHjtLNujGgqjTbgm//kncYoQcbihaCCGEEDITULQQsm80/SZt5WSY38jFHA6rbeWgNW7FU+LCMw+U4f2xwy+6ZniXB0dyFVntK14SVx8L+zZI+SmmW8ZniuiRcSRHV+ZMXwP7Kd4VIwkhAEULIfuIJ2FUbOdZPHcyf0n42CES61hdaERrYe0XFu/SQm+Fv8x+YqKrL4TmCrFVBil39UbllL+NWNFVM38TMwkhFShaCNkvKgub72t5dr5Y7CbwmGjrR0SN2hYfVTOhNM5CXNqzRciH8eq3GmPqnjckisVp5o/YCc2VxCLHx2nbQcjhg6KFkH3Hl+AKeJWA6XnwhYq0RlEu7BQXHo9KI7Hgm9910FjgpcqeUudGWa0YlSPXUAoLuUSUdaw45ZtAWec9Yzt1So14I2ROoWghZL9Q9iI8xgpV6aqr50pzedwgtiYQB/KVKRm2uBZhJU1i2VSp+tEjUeETRJKtJd1gG6TF6UdzG/k59o02Q0aVNkL70rS2B8a2oZKsxBASIRYULYTsMaNyZ0GsmOKjaQkwgPLurbCSX2vEkLVOjmyxck0q3oYGdmmd/ZiTNBBnuUhx2uaa2BBXyj4nzWPHywxBUxJKgodE3ATQur7S77PhtZcmoauFEBOKFkL2GmfOhavaxNVey4t3vm7bi7Zz/dPlBToXKCUdoEaLrvfbv3lej/qV9oeRFm8hOdaHKGIaeIOQC6hcnLjiZfbvwpeHIhmnHaLH+l1I3UthQcVdcQkxoGghZK8pci6kUIK0GrsW4nxhtUJDrqck2wmf5uJYEhqAvKW+YJ/T4+F7L+EJkTXxGLnyeSrOClVuWxGQjjHEEJCjfTGP1c4UKiXHkyDYapOJCZlPKFoI2Q/qkmbLDfMTvsGMNk0EgiFUtLSamlPWiQUbT/uSF8E6Ucpfsedocl2OCb1hNjsEJrWx2jXOQbLusRQhK4WZHHYRQgooWgjZa7whAcBb/VKb5lDnCREGdD6gUfvFlXNINQox2fY6hzI8E9KjBqQN65rkezhLj+33utByIr7QWiOUfB9K5unRddHTQogIRQshe420MNpeDzvsU1fxIo6tR+P48mh8g3kXa0diRpEmYuTA2CJDEjTySj46VEyXC60GYqoyvhSSa0CT6iefAXZT0aOjRtfVtGybkDmDooWQfcUSJmIYIj9tr3q6qmtKQkCN+pnVRdLUYmKsb9U0V2FPSCmft1LqqxxrvifHpJjOuJbCO+ExszS8dB9U1ZNTsUW41kaiwiNqKr8v4wQFCyEi0X4bQMi8UFSB5OkZlXwGRxJonlgrJcRWugu5H6XjlggoHA+5wMmbCOM3pZToatife26cYzpyarwhpbydLfhcXbQl4lzjN8ihUU2a6WpD4dDoRDYwU1oIEaGnhZC9IvcKVL60u7waDXJKKt0UGu2nYjR3f7YG8OXZONtYK/M4gsXb3m7XMEyjc0HguEfaEA5N8d3nPL9H9BjZjQXXEz0uhJSgaCFkryhyFionIIcdapIgzG/s9jwVDWCOb4VUfMmnTZJoRWdRzWpbyWkRwja+vt7z9jjGzSjsEzxJtrhoMp8rrUVjJFB9l1Z3udLvl5A5hqKFkIOGr3rGXOhzj4GkbXyOglw82bmllf1CHGEKKf2l0j8XTkpe9H2ekTpRUpekaoenmnpNXALE9xRnlx3K7KcbhMXyV8G7xVARIQUULYQQQgiZCShaCNlXxNrXapMiTNAkZiPlyAjH7NwK89k4FU+C0d+ZByMlAMPvVamgUKl0ct0ir0Mms7d03+zznr7e01JekjVucbvMJGrJ42QMUvoVOe41IXMORQshe4WYb+vJW7FDPXnIoRQeERZju4S3CJGYYsBYmLXdDqMQVUmQqHJ736VUFn774nU6hzIW+VJzXb1++3wuSKTF3rTXTmbWDWIudeE1F9qYs5JEXRfWMn63zGMhRISihZC9ws6ZqCzqtvvAs3qJ3g0Ncf8Te43Nh614WmwPjp0sK43nUTCVRGCPUXWVNFKysdnMKX4k01w3xGlMNc/GJ9wq53T5vDSePYZzJ19C5huKFkL2C7G6x/g23mTX15LGUWUPhXNeJSzclkG516VigkfB1FXHiF6m3HtjiY464eWyQxQk8IuEYjKPMKlsjpe3EVSSso9LSsYhjKTHE4gb3xEyn1C0EHLQqF2gHW19z+5xkoscS+w410lPJY3tHBin8sX0nNjjVj+gJHa8XguXmBEbOz5WEnyq44tjeG6oqBlzMWl7z0RjCZlLKFoI2Q8qG8Dp6rkCVW0jjpeHZCZZ5exwjociwdRIdhWGcyfs1ggNoJzsmnd2hXrsJzXLH4TP1qHa5zMpuU0pryYXjsINqPNElY6Nq/oImQ8oWgjZDyqeBVU9l1N80fcsYM4nNdsDCYLIEVFxHiiEUYPkXHGYBgJJelZSJeziN7N8whYAdqIxICY4116Xtm6FFe5yzVXMaQo4WwQ2EKuEzBlK+7/x8K+FkClQPHdo2kzjy3iTMUqeHDRI0TATiwURVtIPwtiOrhWbxiqnFgepmWSH3W0b88+1/bJXBZx/8qnJ7SNkdhH/QuhpIWQvEMMKru8E1rd8s52Zw2EufJXqFrOPMLaJchwvtVHldsr6kciTee157fnsnXcLp5GRZyMl9Bb7ykgeJLO9496X7JuQOhOKB1Hq8udKvoxjbEJICYoWQvYCySPg3I7eWthKTyQ2cjiUtfC75istkEIsqMniXSzMUjtxta7mpNjnXfMUb4wxlHGuJHoy1STlBhVTOe59E1HgTYsRBJzDhEoJsy10aj1XhBCAooWQ/WWs5NdxOtveGjgEh8rET52nBeWF2T45ViC5iXdBEhqeIQuvS4PkVy+63KfiETHulbaESN5X2e0rxhr30xCoJS8aI/OESFC0ELInNAhjiH0y6pJlK+ET2/NiNKqUCftiPDXzSvb5LlGyTdudmtwnwV5JlJUOCSGziudEVYWKabNZFVQkBudKRVmiq5K8Yxts2Wp60ZTYhJB5h6KFkD3BclU0WYy81ULWIFJOiP2+OGYsjpU5a2xqlP+C+nydUnttXatLRDWYV2xTiiuVj1VCWIKbxScYcxEj7hfjCYkVQsjnkRGGIGTOoWghZL8oORdcCbI+fBmwRriiWKDtRblmyIpjQFr8zYZSjo3gTbAPS6k2LuNKXhnTc6KtNsLcttgQ9Y0vMcWwtTDBuLfSAycrQ9liyS/Oaqo7CZk7KFoI2ROs0EThTGgiKOoWLkfeRBGuqFmIS+ecq6280JfCPY6cGXEsa9xazMVemK8khmzhYHlMXNqrdMxhkxn1McuZ7YiW6O3yqTNlaM38vcb1Gzcd7QmZTyhaCNkTHC6MSlhEalYXUqpZjUvjeBZNey5bpJhPVhbxiKLKqZq2lR2DXcLLUgtFcqsWxJAUEvIZ4ThUCBchEdefLeyf0oggaq3RHwzwv/9fv97EWELmBooWQgghhMwE0X4bQMh8YHwLzz0BWqVJqGKlidGnFE5yjJkOLE9dcghIHgjJRqFvaX8Ys4LGP32pr/tiLHsdSbCAdQ32uMb7yrVKx1zeEeFYMbwVFiq8O5KtVr9ShZF0HoiTBFev38DNW7flMQmZYyhaCNkT7NXdU1kCoAhveCMODeIcpf4+weIaTzJAOT4ax512N4rNZGPk98ASKbXjWuLQzn0RRU+t4eUxSuXRnj7K+iDcSq01BoMBNre2AQCvX72GV19/A4PB0G8HIXMIRQshe0Wev1JaLwVXhbbbaCGHoiEl50M+vpn8a9uI6kLrJfcYOeb19XM1ykWF9yGQHs9U9QaOYZxxjyTRWHxu4OHyTZuN0+/38cJLr+DGrdsYDmMAwPrGBoZxjM997nPNxiVkjqBoIWSvcEYyJM+FKi+QrgiSOJ5nbvt9MYZHyHgxQ1zWeK5dap1G5KesixGvzTemMK9Lx2jr5tmbu0lirKQxfdduTa41Eq0RxzGUUrhx8za+8NyX0adHhZDGULQQstfYOSElPOeU1M5aIF1awLXg68yeolJIWoQtm8WBjfPe8ItokOO4J9w07hOeK8InF0RNPSZ2mMlji7LtVrh+8xZu3bqN67duY2NzE8M4xu07683tJ4QAoGghZB9whUUwxkIsug3cY1cET3awFKJScn8rHHL+yadG75/48KhRKSnVJ34qBmXntbDgO5r7Ql3avLbSQYeYapRJLByz81qMdtbt/Otnn8N2fwCtNbTWUEoVr8Vo2bWoScKAhMwJFC2E7BnS4ujyrEjhjZ3sA2JWIjlCK6VwhzyXKVjszyMBY1TvFN6gbF4z/8UWHGKYrAbxCc4NkodzGuTdujt5wl/Woa3t/uhUZrMtTszPzGchRIaihZA9Q0rOUNa6ZyyIFU9Dg/CMM79FEEaV9dbt2mhFEX7hl5/0XRzOP/kU3vWud0EphR967/fKXg0pGjNWqMeR+GucLntdrDCafc0uIegTM6Vy5wahLELI1KBoIWTPsZSDK6+i0cKXeTQkrWGKF2m8kmfFGAuqvJhrYHVluYkx+PznP4/HH38cf/gnn6ycc4VFbH7ovd9rdRRsd+EKIzlziIQQFiCLGdsJ5RQ1DW0lhIwNd8QlZF9xhS208d581caBfAjfCjrG/IXnoLxgq0AhCJr/U5GHNuyH/ZlhkUYPAhSbeLws/o7NTudCzm4jCUNpHK2tkw2us+iq+YBEQmqgaCFkzzAFh7aOW00qFUH5otlAoNi6pqmmyZNkrXLdQI0nWoBUuNjeFHNBlhJQ7ffOJNzyqCjfv7KHSMQXWsrvfSW/RhhTHMcSfbrayCVMlFJQSjGfhRAPFC2E7BmmejAWQa3kJibC4jc6Z3tesp/G3gwzfmQLqFSwTFLRYi++rjHM40opMbTkFHn2DSs95NESM/b9cN23ytSG0HTeBm2cFwSnOY3jPnzuc5+jYCGkBooWQvYa25tQSsJ1YOmJ8rrtWEkrZcCiMRBXYiNvIxgzPGTiChU5rdGW0BATclyeFD06rS2B4fOeSCE3sZ3Pg2P+Iu0GTHIhZFpQtBCyV5jhB3ERt0t7zE4Q1m17gc8Pme+N9tLaXPJMGJMUBTepYAl2sHeIFCqyqe5Rkico28mw1v3IPSjasL0Ir0n30xijOGQJjko+i/XZvpTKr9L1+62S57HQw0JIMyhaCNkrlLbyRjwLmzYWYO1qaxwvbTufVxRZrhlleR+0sfij3DQ/nuazhFATelpy6kIfjcNPphgx809Kgk64V3YILk/ozQWPKWAqprhcXOZ4liJ0XI+UnMzN5AhpDkueCdkz7MXJrtwxPlQ2XKvJaXE9v6gYXBjDGVbK+mT5LDv1tJiYwuXxxx8XjwPZRnWOyFXFztEH4b10yM6BcdyfyjxFslD9nKbtxi64kkChl4WQ5tDTQgghhJCZgJ4WQvYap2fE+uB1AGRf5aXdYSvjOzwIGnA/GiAdN81pUWPsNtKcWg9DI+eOy1sl4LzU/H4Lv5fKHK42PhPLHhZzcz16WQgZD3paCNkrzERc81ipjauyyG5rhX7MBFx7US0SVYXx7UXfaftuyJaGmPb7kHJzSsnIQoJygzyUkh3Kuu9yQ694omAhZHLoaSFkT5BKeQQvifSUYzOdwkZMwPV4BkoJwPVeCmlPtT1HSoy1xZ+znza8Uea9ys5Zw/pzaOzqJFen8uc//JNP0rtCyJSgaCFkr6iEbIwFz37iMUanasMkhTDR1sJqz+lRP64IUl4dvK/bywuioJQcm1GIPFOoWfejduz/v7072Y3kys4AfCJyIFmDpJYst92AAT+E6s0a8La9s4H2qxgw/AZaCJBYe8OADdlWay6VisUhM5kxeJEDg8HIiWSReUvftymyMjIyGAUqfp177r07XM6q4NTxWVa6hftheAgexCKkdD3866upu+usCg6bdlNe/5dbqarq1u+9d8vbuKIvaLH2TLOg1DXMtpxWXm83/FW3vlgEpLaOSo7AAvdDpQUeTKuqsvyrTd2j0fi/+g3Tczvf3zEdd4dTVHUV02mx5efdp1VjVs2X2z/MuqGj9pDc4vste1mWh7WH29Zfu8AC90dogQdQ13Vk6x52XbNSmg/f9gOzOfNn0YR7bYfmrqGg1kN7Uw/H/Lonk8uYPEpoWTW00xxKWzF01DnLpzUkt9OCdi1r793i3+UWM42AtQwPwQP4x3/+lyjKIopy/vBvjyp0zUpZ2xTaOOBa70rrwdx+U9dsmq7rqeuoqioml5fx5vQsfvn1zZqLeQfafcs3dAS8a+9p9bo037dte07d+rP5wroCy66hCNiaSgs8kMWD/+mTJ3F0eBC9PI8b+xDd5kF3I6OsmRV0bYSpq0l39mdZlnE+GkdZVfH27DyKstz9uu7iRjWo+YOsuEerbt2N4aD5111r3CyOW1S5FtWSa6NQ2ZpcuEX5Crg1oQUeyP/85buIiHj+9El8+snH8cHzZzEcDCLqurHMSn31XM2yzY+/9r47Tdeen81hkY6mlsXQUj3rYTk5PYtfT95GUZZxfjGKaflIjbhdfSRrj1vhRghZc9+aQ2g3hudan9cZGBvDdvIL3CuhBR7I63ml5ez8PE5Oz+Jv//rT+KuPP4qqqqKqZkEiz/Po5XnkvfmfeR51XUdV1VHXV8FhsY/NYm+grBlwls/NZl9Fu9wSywpPXddR1XXUdUSeRfx68ja+/+nnOD27iDrqGF9O4/PPP3+Xt2aCHPX1AAALbElEQVSDdp/OFoc2v7lWpGmGkEWTc1cwab13zYjbymtQdYF7J7TAA6nmIWE8uYzLaRHjySSKsoyiKKIsy6jmzbp5L49Bvx/DwSAOhoO4nBZRFEUUZblcLyWLiCyfHXcwHMbR0UEMB4MoyzKmxeK4Onp5L/r9fgwG/Rj0+7MFzubnmFxO43w0itF4HGVZRhZZDAaD+PHVL/HryUlcTov92IW4zloBYEUY2DZYLI9bUUVZHlffPGZTc+2Nxf1WHwrsLtuwaJRfObhnL168WD43Dw8OIs+yqKO+tr5cnuXR6/Xi4GAQ0+kssJRlFc1fybqO6PV6Mej34mA4jH6/F+PJZUyn02XlJsuzGA76cTA8iA+ePY2PPnweb0/PIyLi9clJXIzGURRlRNSRZ3kMh4M4O7+IaTGdVV7y2XV88cUXD3qPIiL+9A9/bFQ5GgFiWf3YoReoK9DsXAhZ0x18bcTt6sR/+qc/7/IBwJXO306VFngEi9/G8WQSWZZ1rjib51lcjPL50E29clXaRTUki4iyYxG4bF5V+OXNmzj4cRij8TgiIoqiaE24yWZVl+Y5GsvPP7xF42wrXTTHwba9tFUVmHXBpatfpTlc1FyBeFUjNHCvhBZ4ZKvCSFlWUWWbi53rAk1EzKsudYzHk5hMJrHqoVrXdZSt8zxqqXXt+ii3WAOlXbGJWJ8v1g01Za0DbvQ262eBd8E6LfDIugJHc4O9ZiipW1WXbfYEWlZiOhdj219XWwdc9eFcVTk2DQe1F1mpbwaNG+9Ze8L1n9e8tdtcH3ArQgsAkAShBR7YNnvRNPtcmj0l16smsbIfpqk9fNRVqVl3jsfqafnmu+/nXy2GghrVlk1ubCK5xZvWHtKo9kRsNW72uDtjw/tJaIFH1hUK6lYD7LrgsClUtF9vh55tzvEY/uO/vp49+JcjPNte4zsKC6uCU/vjstm/3/nFxbu5DvgN04gLe2iXENEOOHc9374oyzJ+PXkbw8Fgvm5NP7LItmjAvcPPurF/tmOqc8fx5xcX8fU3397+OoBO1mmBR/LixYuVr20TRO6q3ezbNSSVZVl89dVX7/Q6Vnnx4kU8OTqMD58/j6dPjuKT330UHz5/FoN+f0VwueuMnY7tDdYe3tHcW9cxmU7jP//76/jXf/v3O1wL/OZZpwVS0BUmmq8t3DXUdL2/3SPz2BWa84tRjMeT6PV68eqX1/GHv/l9/P7TT+Lo8LC1NMp8+s5iWvOqvYVWLAJ386DWIi5dhy63SYioq6veoP/9y3fxw0+vbvPjAhsILfBIjo+P47PPPuvsOen6uuv7+7LqM7/88st38nm7qOo6qqKIN6dns60HLkbx93/3hzgYDiPPZ215zQX2Zn/RkTJWbSDZXIr4mvXrudR1PVtLp6qiKIqIiLgYj+P/vv0+pvPvgfsltMAjevny5WxZ/w3DQV2vd80u2mTV5zzEcNRttK9pNJnEtz/8GEVZxMcffRRPjg4jIpZ9L/1+P3q9PPKu3a9XrVp7ba+gxqJ1i72H2uepY7aR5HgSF+NxjCeTGI0nERHx06vXMbm8vO2PC2wgtMAeuG0j7aq/XxVydj3PPirKMn746VWcnJ7Fk8NZaDk6Ooyjw8N49uQojg4PYzichZhlJWbx5saGkVcvrAgwi5fmQaY5Pfz8YhQ///I6zs4v4nw0WlZa3p7N9nXaZlo7sDuNuLAH1jXlbrJNleQ2lZR9ePBuui/5/Gfq9/sxHA7i6OAgnj55Es+fPY3nT5/G4eFB9HuNlR2yLPL5UNJso8p2AWYWahY7cldVNV/XZvb1bD+ocXzz3Q/x5vQ0JpPL2VDQ4vj5GjgvX768x7sAv0kacWFf3WXYZpswklIlZReLcHE5nca0KGI0Gsfbs/N48/ZtPH/2ND784HkM+7P/zOW9XuRZtty5uj/fIbvX681ez/Oo5/0pRVnF5fQyptMiyqqKoihnK/VnWfz8+nX89Op1lGU5//yr6LOvw2zwvhBaYA+8fPnyWlPu4uG37QPwtg/LVX0x+1Bladq2mlTWdZSXlzEtZg27p2fn0Z8PE11VZXoxGAxiOBjEwWAQw4NBREQcDg+iKMtZr8poFON5FWU6LSJiVn3J8yzenJxGUZaNT95uEUDg7oQW2BOLptyI3R9+t31Y7vtDthnedmlGrqo6qqqIt2fn876WWTVkNjQUkWd59Hp5DIfDODwYRkTE4cFhTKaXMRqNYzotYloUy16VOiLqqoq8l7cCC/CQ9LTAnmn2cbzr4Yau8+9TlaXd03Jfs58W06OzPIssm/W8DPv9KMoyyqpa9rJcnX+LhXjn9un+QcI6f+PsPQR7ZvHQe+j+iH3c4K8dAO4y+6m9aWQ1X2elmFdURpNJXE6nUSx7VeYVlrreOrAA75ZKC+ypu8wouo19rRA82H2Yr7+ybQDqOm5f7yEkSKUFUnJ8fHyv1Y9159r3h209n0rcXCvlNudYK9u+x2ffe4HgfSW0AABJMDwECdi01P9t+1/2vcKy0LVH0666Np+87Tnb703lPkJCDA9Bqo6Pj2+sstocLtlW8/iUHrTt3acjbjbWrrMIGfe1g7XhIXgcKi2QqFUNqvs+jfk2tqm07FI52aVq1fV9xFVwSf3ewp7q/AUVWoAkLELaXcNJM3Tcx7RyoQXeCcNDwPth22GxrkDS3B5hXbWl6/v2kJzAAg9LaAGSsAgIq/Zkus/p4e3zbwo5wMMQWoBktCsbzcrHNj0v29jU4KyXBR6PnhYgOZumgC/cpmdl03uEFXgQelqA98Px8fHGIaJdV8/dZgq1wAKPS6UFSNY2+xKZIQRJMuUZeD81p0NH3OxvucswkcACj0JoAd5v97kjtLACj0poAX47dmnWjTArCPaM0AL89jS3AGiGGOEE9prQAgAkwZRnACBdQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIgtACACRBaAEAkiC0AABJEFoAgCQILQBAEoQWACAJ/Q2vZw9yFQAAG6i0AABJEFoAgCQILQBAEoQWACAJQgsAkAShBQBIwv8DPWGlOpv1o9QAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 10))\n", - "plt.imshow(images[0, ..., :3].cpu().numpy())\n", - "plt.grid(\"off\")\n", - "plt.axis(\"off\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Rotate the object, modify the material properties or light properties\n", - "\n", - "We can also change many other settings in the rendering pipeline. Here we:\n", - "\n", - "- change the **viewing angle** of the camera\n", - "- change the **position** of the point light\n", - "- change the **material reflectance** properties of the mesh" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Rotate the object by increasing the azimuth angle\n", - "R, T = look_at_view_transform(dist=2.7, elev=10, azim=50)\n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", - "\n", - "# Move the light location to be in front of the object again\n", - "lights.location = torch.tensor([[5.0, 5.0, -2.0]], device=device)\n", - "\n", - "# Change specular color to green and change material shininess \n", - "materials = Materials(\n", - " device=device,\n", - " specular_color=[[0.0, 1.0, 0.0]],\n", - " shininess=10.0\n", - ")\n", - "\n", - "# Re render the mesh, passing in keyword arguments for the modified components.\n", - "images = renderer(mesh, lights=lights, materials=materials, cameras=cameras)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(-0.5, 511.5, 511.5, -0.5)" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(10, 10))\n", - "plt.imshow(images[0, ..., :3].cpu().numpy())\n", - "plt.grid(\"off\")\n", - "plt.axis(\"off\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Batched Rendering\n", - "\n", - "One of the core design choices of the PyTorch3d API is to suport **batched inputs for all components**. \n", - "The renderer and associated components can take batched inputs and **render a batch of output images in one forward pass**. We will now use this feature to render the mesh from many different viewpoints.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "# Set batch size - this is the number of different viewpoints from which we want to render the mesh.\n", - "batch_size = 20\n", - "\n", - "# Create a batch of meshes by repeating the cow mesh and associated textures. \n", - "# Meshes has a useful `extend` method which allows us do this very easily. \n", - "# This also extends the textures. \n", - "meshes = mesh.extend(batch_size)\n", - "\n", - "# Get a batch of viewing angles. \n", - "elev = torch.linspace(0, 360, batch_size)\n", - "azim = torch.linspace(0, 360, batch_size)\n", - "\n", - "# All the cameras helper methods support mixed type inputs and broadcasting. So we can \n", - "# view the camera from the same distance and specify dist=2.7 as a float,\n", - "# and then specify elevation and azimuth angles for each viewpoint as tensors. \n", - "R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)\n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", - "\n", - "# Move the light back in front of the object\n", - "lights.location = torch.tensor([[1.0, 1.0, -5.0]], device=device)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [], - "source": [ - "# We can pass arbirary keyword arguments to the rasterizer/shader via the renderer\n", - "# so the renderer does not need to be reinitialized if any of the settings change.\n", - "images = renderer(meshes, cameras=cameras, lights=lights)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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All rights reserved. - - -# # Render a textured mesh -# -# This tutorial shows how to: -# - load a mesh and textures from an `.obj` file. -# - set up a renderer -# - render the mesh -# - vary the rendering settings such as lighting and camera position -# - use the batching features of the pytorch3d API to render the mesh from different viewpoints - -# ## Import modules - -# In[1]: - - -import os -import torch -import matplotlib.pyplot as plt -from skimage.io import imread - -# Util function for loading meshes -from pytorch3d.io import load_obj - -# Data structures and functions for rendering -from pytorch3d.structures import Meshes, Textures -from pytorch3d.renderer import ( - look_at_view_transform, - OpenGLPerspectiveCameras, - PointLights, - DirectionalLights, - Materials, - RasterizationSettings, - MeshRenderer, - MeshRasterizer, - TexturedPhongShader -) - -# add path for demo utils -import sys -import os -sys.path.append(os.path.abspath('')) -from utils import image_grid - - -# ### Load a mesh and texture file -# -# Load an `.obj` file and it's associated `.mtl` file and create a **Textures** and **Meshes** object. -# -# **Meshes** is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes. -# -# **Textures** is an auxillary datastructure for storing texture information about meshes. -# -# **Meshes** has several class methods which are used throughout the rendering pipeline. - -# In[2]: - - -# Setup -device = torch.device("cuda:0") -torch.cuda.set_device(device) - -# Set paths -DATA_DIR = "./data" -obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj") - -# Load obj file -verts, faces, aux = load_obj(obj_filename) -faces_idx = faces.verts_idx.to(device) -verts = verts.to(device) - -# Get textures from the outputs of the load_obj function -# the `aux` variable contains the texture maps and vertex uv coordinates. -# Refer to the `obj_io.load_obj` function for full API reference. -# Here we only have one texture map for the whole mesh. -verts_uvs = aux.verts_uvs[None, ...].to(device) # (N, V, 2) -faces_uvs = faces.textures_idx[None, ...].to(device) # (N, F, 3) -tex_maps = aux.texture_images -texture_image = list(tex_maps.values())[0] -texture_image = texture_image[None, ...].to(device) # (N, H, W, 3) - -# Create a textures object -tex = Textures(verts_uvs=verts_uvs, faces_uvs=faces_uvs, maps=texture_image) - -# Create a meshes object with textures -mesh = Meshes(verts=[verts], faces=[faces_idx], textures=tex) - - -# #### Let's visualize the texture map - -# In[3]: - - -plt.figure(figsize=(7,7)) -plt.imshow(texture_image.squeeze().cpu().numpy()) -plt.grid("off") -plt.axis('off') - - -# ## Create a renderer -# -# A renderer in PyTorch3d is composed of a **rasterizer** and a **shader** which each have a number of subcomponents such as a **camera** (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest. -# -# In this example we will first create a **renderer** which uses a **perspective camera**, a **point light** and applies **phong shading**. Then we learn how to vary different components using the modular API. - -# In[4]: - - -# Initialize an OpenGL perspective camera. -R, T = look_at_view_transform(2.7, 10, 20) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) - -# Define the settings for rasterization and shading. Here we set the output image to be of size -# 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1 -# and blur_radius=0.0. Refer to rasterize_meshes.py for explanations of these parameters. -raster_settings = RasterizationSettings( - image_size=512, - blur_radius=0.0, - faces_per_pixel=1, - bin_size=0 -) - -# Place a point light in front of the object -lights = PointLights(device=device, location=[[1.0, 1.0, -2.0]]) - -# Create a phong renderer by composing a rasterizer and a shader. The textured phong shader will -# interpolate the texture uv coordinates for each vertex, sample from a texture image and -# apply the Phong lighting model -renderer = MeshRenderer( - rasterizer=MeshRasterizer( - cameras=cameras, - raster_settings=raster_settings - ), - shader=TexturedPhongShader( - device=device, - cameras=cameras, - lights=lights - ) -) - - -# ## Render the mesh - -# The light is in front of the object so it is bright and the image has specular highlights. - -# In[5]: - - -images = renderer(mesh) -plt.figure(figsize=(10, 10)) -plt.imshow(images[0, ..., :3].cpu().numpy()) -plt.grid("off") -plt.axis("off") - - -# ## Move the light behind the object and re-render -# -# We can pass arbirary keyword arguments to the `rasterizer`/`shader` via the call to the `renderer` so the renderer does not need to be reinitialized if any of the settings change/ -# -# In this case, we can simply update the location of the lights and pass them into the call to the renderer. -# -# The image is now dark as there is only ambient lighting, and there are no specular highlights. - -# In[6]: - - -lights.location = torch.tensor([0.0, 0.0, +1.0], device=device)[None] -images = renderer(mesh, lights=lights) - - -# In[7]: - - -plt.figure(figsize=(10, 10)) -plt.imshow(images[0, ..., :3].cpu().numpy()) -plt.grid("off") -plt.axis("off") - - -# ## Rotate the object, modify the material properties or light properties -# -# We can also change many other settings in the rendering pipeline. Here we: -# -# - change the **viewing angle** of the camera -# - change the **position** of the point light -# - change the **material reflectance** properties of the mesh - -# In[8]: - - -# Rotate the object by increasing the azimuth angle -R, T = look_at_view_transform(dist=2.7, elev=10, azim=50) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) - -# Move the light location to be in front of the object again -lights.location = torch.tensor([[5.0, 5.0, -2.0]], device=device) - -# Change specular color to green and change material shininess -materials = Materials( - device=device, - specular_color=[[0.0, 1.0, 0.0]], - shininess=10.0 -) - -# Re render the mesh, passing in keyword arguments for the modified components. -images = renderer(mesh, lights=lights, materials=materials, cameras=cameras) - - -# In[9]: - - -plt.figure(figsize=(10, 10)) -plt.imshow(images[0, ..., :3].cpu().numpy()) -plt.grid("off") -plt.axis("off") - - -# ## Batched Rendering -# -# One of the core design choices of the PyTorch3d API is to suport **batched inputs for all components**. -# The renderer and associated components can take batched inputs and **render a batch of output images in one forward pass**. We will now use this feature to render the mesh from many different viewpoints. -# - -# In[10]: - - -# Set batch size - this is the number of different viewpoints from which we want to render the mesh. -batch_size = 20 - -# Create a batch of meshes by repeating the cow mesh and associated textures. -# Meshes has a useful `extend` method which allows us do this very easily. -# This also extends the textures. -meshes = mesh.extend(batch_size) - -# Get a batch of viewing angles. -elev = torch.linspace(0, 360, batch_size) -azim = torch.linspace(0, 360, batch_size) - -# All the cameras helper methods support mixed type inputs and broadcasting. So we can -# view the camera from the same distance and specify dist=2.7 as a float, -# and then specify elevation and azimuth angles for each viewpoint as tensors. -R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) - -# Move the light back in front of the object -lights.location = torch.tensor([[1.0, 1.0, -5.0]], device=device) - - -# In[11]: - - -# We can pass arbirary keyword arguments to the rasterizer/shader via the renderer -# so the renderer does not need to be reinitialized if any of the settings change. -images = renderer(meshes, cameras=cameras, lights=lights) - - -# In[12]: - - -image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True) - diff --git a/help.html b/help.html index e6a592b9..2f3d008f 100644 --- a/help.html +++ b/help.html @@ -12,4 +12,4 @@

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/help/index.html b/help/index.html index e6a592b9..2f3d008f 100644 --- a/help/index.html +++ b/help/index.html @@ -12,4 +12,4 @@

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/index.html b/index.html index d767e71f..d522c74e 100644 --- a/index.html +++ b/index.html @@ -31,4 +31,4 @@ sample_sphere = sample_points_from_meshes(sphere_mesh, 5000) loss_chamfer, _ = chamfer_distance(sample_sphere, sample_test) - \ No newline at end of file + \ No newline at end of file diff --git a/tutorials/bundle_adjustment.html b/tutorials/bundle_adjustment.html deleted file mode 100644 index a5b4d718..00000000 --- a/tutorials/bundle_adjustment.html +++ /dev/null @@ -1,8314 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
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In [1]:
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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-

Absolute camera orientation given set of relative camera pairs

This tutorial showcases the cameras, transforms and so3 API.

-

The problem we deal with is defined as follows:

-

Given an optical system of $N$ cameras with extrinsics $\{g_1, ..., g_N | g_i \in SE(3)\}$, and a set of relative camera positions $\{g_{ij} | g_{ij}\in SE(3)\}$ that map between coordinate frames of randomly selected pairs of cameras $(i, j)$, we search for the absolute extrinsic parameters $\{g_1, ..., g_N\}$ that are consistent with the relative camera motions.

-

More formally: -$$ -g_1, ..., g_N = -{\arg \min}_{g_1, ..., g_N} \sum_{g_{ij}} d(g_{ij}, g_i^{-1} g_j), -$$, -where $d(g_i, g_j)$ is a suitable metric that compares the extrinsics of cameras $g_i$ and $g_j$.

-

Visually, the problem can be described as follows. The picture below depicts the situation at the beginning of our optimization. The ground truth cameras are plotted in green while the randomly initialized estimated cameras are plotted in blue: -Initialization

-

Our optimization seeks to align the estimated (blue) cameras with the ground truth (green) cameras, by minimizing the discrepancies between pairs of relative cameras. Thus, the solution to the problem should look as follows: -Solution

-

In practice, the camera extrinsics $g_{ij}$ and $g_i$ are represented using objects from the SfMPerspectiveCameras class initialized with the corresponding rotation and translation matrices R_absolute and T_absolute that define the extrinsic parameters $g = (R, T); R \in SO(3); T \in \mathbb{R}^3$. In order to ensure that R_absolute is a valid rotation matrix, we represent it using an exponential map (implemented with so3_exponential_map) of the axis-angle representation of the rotation log_R_absolute.

-

Note that the solution to this problem could only be recovered up to an unknown global rigid transformation $g_{glob} \in SE(3)$. Thus, for simplicity, we assume knowledge of the absolute extrinsics of the first camera $g_0$. We set $g_0$ as a trivial camera $g_0 = (I, \vec{0})$.

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0. Import Modules

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In [2]:
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# imports
-import torch
-from pytorch3d.transforms.so3 import (
-    so3_exponential_map,
-    so3_relative_angle,
-)
-from pytorch3d.renderer.cameras import (
-    SfMPerspectiveCameras,
-)
-
-# add path for demo utils
-import sys
-import os
-sys.path.append(os.path.abspath(''))
-from utils import plot_camera_scene
-
-# set for reproducibility
-torch.manual_seed(42)
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Out[2]:
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<torch._C.Generator at 0x7efd99023130>
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1. Set up Cameras and load ground truth positions

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In [3]:
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# load the SE3 graph of relative/absolute camera positions
-camera_graph_file = './data/camera_graph.pth'
-(R_absolute_gt, T_absolute_gt), \
-    (R_relative, T_relative), \
-    relative_edges = \
-        torch.load(camera_graph_file)
-
-# create the relative cameras
-cameras_relative = SfMPerspectiveCameras(
-    R = R_relative.cuda(),
-    T = T_relative.cuda(),
-    device = "cuda",
-)
-
-# create the absolute ground truth cameras
-cameras_absolute_gt = SfMPerspectiveCameras(
-    R = R_absolute_gt.cuda(),
-    T = T_absolute_gt.cuda(),
-    device = "cuda",
-)
-
-# the number of absolute camera positions
-N = R_absolute_gt.shape[0]
-
-
-
-
-
-
-
-
-

2. Define optimization functions

Relative cameras and camera distance

We now define two functions crucial for the optimization.

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calc_camera_distance compares a pair of cameras. This function is important as it defines the loss that we are minimizing. The method utilizes the so3_relative_angle function from the SO3 API.

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get_relative_camera computes the parameters of a relative camera that maps between a pair of absolute cameras. Here we utilize the compose and inverse class methods from the PyTorch3d Transforms API.

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In [ ]:
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def calc_camera_distance(cam_1, cam_2):
-    """
-    Calculates the divergence of a batch of pairs of cameras cam_1, cam_2.
-    The distance is composed of the cosine of the relative angle between 
-    the rotation components of the camera extrinsics and the l2 distance
-    between the translation vectors.
-    """
-    # rotation distance
-    R_distance = (1.-so3_relative_angle(cam_1.R, cam_2.R, cos_angle=True)).mean()
-    # translation distance
-    T_distance = ((cam_1.T - cam_2.T)**2).sum(1).mean()
-    # the final distance is the sum
-    return R_distance + T_distance
-
-def get_relative_camera(cams, edges):
-    """
-    For each pair of indices (i,j) in "edges" generate a camera
-    that maps from the coordinates of the camera cams[i] to 
-    the coordinates of the camera cams[j]
-    """
-
-    # first generate the world-to-view Transform3d objects of each 
-    # camera pair (i, j) according to the edges argument
-    trans_i, trans_j = [
-        SfMPerspectiveCameras(
-            R = cams.R[edges[:, i]],
-            T = cams.T[edges[:, i]],
-            device = "cuda",
-        ).get_world_to_view_transform()
-         for i in (0, 1)
-    ]
-    
-    # compose the relative transformation as g_i^{-1} g_j
-    trans_rel = trans_i.inverse().compose(trans_j)
-    
-    # generate a camera from the relative transform
-    matrix_rel = trans_rel.get_matrix()
-    cams_relative = SfMPerspectiveCameras(
-                        R = matrix_rel[:, :3, :3],
-                        T = matrix_rel[:, 3, :3],
-                        device = "cuda",
-                    )
-    return cams_relative
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3. Optimization

Finally, we start the optimization of the absolute cameras.

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We use SGD with momentum and optimize over log_R_absolute and T_absolute.

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As mentioned earlier, log_R_absolute is the axis angle representation of the rotation part of our absolute cameras. We can obtain the 3x3 rotation matrix R_absolute that corresponds to log_R_absolute with:

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R_absolute = so3_exponential_map(log_R_absolute)

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# initialize the absolute log-rotations/translations with random entries
-log_R_absolute_init = torch.randn(N, 3).float().cuda()
-T_absolute_init = torch.randn(N, 3).float().cuda()
-
-# futhermore, we know that the first camera is a trivial one 
-#    (see the description above)
-log_R_absolute_init[0, :] = 0.
-T_absolute_init[0, :] = 0.
-
-# instantiate a copy of the initialization of log_R / T
-log_R_absolute = log_R_absolute_init.clone().detach()
-log_R_absolute.requires_grad = True
-T_absolute = T_absolute_init.clone().detach()
-T_absolute.requires_grad = True
-
-# the mask the specifies which cameras are going to be optimized
-#     (since we know the first camera is already correct, 
-#      we only optimize over the 2nd-to-last cameras)
-camera_mask = torch.ones(N, 1).float().cuda()
-camera_mask[0] = 0.
-
-# init the optimizer
-optimizer = torch.optim.SGD([log_R_absolute, T_absolute], lr=.1, momentum=0.9)
-
-# run the optimization
-n_iter = 2000  # fix the number of iterations
-for it in range(n_iter):
-    # re-init the optimizer gradients
-    optimizer.zero_grad()
-
-    # compute the absolute camera rotations as 
-    # an exponential map of the logarithms (=axis-angles)
-    # of the absolute rotations
-    R_absolute = so3_exponential_map(log_R_absolute * camera_mask)
-
-    # get the current absolute cameras
-    cameras_absolute = SfMPerspectiveCameras(
-        R = R_absolute,
-        T = T_absolute * camera_mask,
-        device = "cuda",
-    )
-
-    # compute the relative cameras as a compositon of the absolute cameras
-    cameras_relative_composed = \
-        get_relative_camera(cameras_absolute, relative_edges)
-
-    # compare the composed cameras with the ground truth relative cameras
-    # camera_distance corresponds to $d$ from the description
-    camera_distance = \
-        calc_camera_distance(cameras_relative_composed, cameras_relative)
-
-    # our loss function is the camera_distance
-    camera_distance.backward()
-    
-    # apply the gradients
-    optimizer.step()
-
-    # plot and print status message
-    if it % 200==0 or it==n_iter-1:
-        status = 'iteration=%3d; camera_distance=%1.3e' % (it, camera_distance)
-        plot_camera_scene(cameras_absolute, cameras_absolute_gt, status)
-
-print('Optimization finished.')
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\ No newline at end of file diff --git a/tutorials/bundle_adjustment/index.html b/tutorials/bundle_adjustment/index.html deleted file mode 100644 index a5b4d718..00000000 --- a/tutorials/bundle_adjustment/index.html +++ /dev/null @@ -1,8314 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [1]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Absolute camera orientation given set of relative camera pairs

This tutorial showcases the cameras, transforms and so3 API.

-

The problem we deal with is defined as follows:

-

Given an optical system of $N$ cameras with extrinsics $\{g_1, ..., g_N | g_i \in SE(3)\}$, and a set of relative camera positions $\{g_{ij} | g_{ij}\in SE(3)\}$ that map between coordinate frames of randomly selected pairs of cameras $(i, j)$, we search for the absolute extrinsic parameters $\{g_1, ..., g_N\}$ that are consistent with the relative camera motions.

-

More formally: -$$ -g_1, ..., g_N = -{\arg \min}_{g_1, ..., g_N} \sum_{g_{ij}} d(g_{ij}, g_i^{-1} g_j), -$$, -where $d(g_i, g_j)$ is a suitable metric that compares the extrinsics of cameras $g_i$ and $g_j$.

-

Visually, the problem can be described as follows. The picture below depicts the situation at the beginning of our optimization. The ground truth cameras are plotted in green while the randomly initialized estimated cameras are plotted in blue: -Initialization

-

Our optimization seeks to align the estimated (blue) cameras with the ground truth (green) cameras, by minimizing the discrepancies between pairs of relative cameras. Thus, the solution to the problem should look as follows: -Solution

-

In practice, the camera extrinsics $g_{ij}$ and $g_i$ are represented using objects from the SfMPerspectiveCameras class initialized with the corresponding rotation and translation matrices R_absolute and T_absolute that define the extrinsic parameters $g = (R, T); R \in SO(3); T \in \mathbb{R}^3$. In order to ensure that R_absolute is a valid rotation matrix, we represent it using an exponential map (implemented with so3_exponential_map) of the axis-angle representation of the rotation log_R_absolute.

-

Note that the solution to this problem could only be recovered up to an unknown global rigid transformation $g_{glob} \in SE(3)$. Thus, for simplicity, we assume knowledge of the absolute extrinsics of the first camera $g_0$. We set $g_0$ as a trivial camera $g_0 = (I, \vec{0})$.

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0. Import Modules

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In [2]:
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# imports
-import torch
-from pytorch3d.transforms.so3 import (
-    so3_exponential_map,
-    so3_relative_angle,
-)
-from pytorch3d.renderer.cameras import (
-    SfMPerspectiveCameras,
-)
-
-# add path for demo utils
-import sys
-import os
-sys.path.append(os.path.abspath(''))
-from utils import plot_camera_scene
-
-# set for reproducibility
-torch.manual_seed(42)
-
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Out[2]:
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<torch._C.Generator at 0x7efd99023130>
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1. Set up Cameras and load ground truth positions

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In [3]:
-
-
-
# load the SE3 graph of relative/absolute camera positions
-camera_graph_file = './data/camera_graph.pth'
-(R_absolute_gt, T_absolute_gt), \
-    (R_relative, T_relative), \
-    relative_edges = \
-        torch.load(camera_graph_file)
-
-# create the relative cameras
-cameras_relative = SfMPerspectiveCameras(
-    R = R_relative.cuda(),
-    T = T_relative.cuda(),
-    device = "cuda",
-)
-
-# create the absolute ground truth cameras
-cameras_absolute_gt = SfMPerspectiveCameras(
-    R = R_absolute_gt.cuda(),
-    T = T_absolute_gt.cuda(),
-    device = "cuda",
-)
-
-# the number of absolute camera positions
-N = R_absolute_gt.shape[0]
-
-
-
-
-
-
-
-
-

2. Define optimization functions

Relative cameras and camera distance

We now define two functions crucial for the optimization.

-

calc_camera_distance compares a pair of cameras. This function is important as it defines the loss that we are minimizing. The method utilizes the so3_relative_angle function from the SO3 API.

-

get_relative_camera computes the parameters of a relative camera that maps between a pair of absolute cameras. Here we utilize the compose and inverse class methods from the PyTorch3d Transforms API.

-
-
-
-
-
-
In [ ]:
-
-
-
def calc_camera_distance(cam_1, cam_2):
-    """
-    Calculates the divergence of a batch of pairs of cameras cam_1, cam_2.
-    The distance is composed of the cosine of the relative angle between 
-    the rotation components of the camera extrinsics and the l2 distance
-    between the translation vectors.
-    """
-    # rotation distance
-    R_distance = (1.-so3_relative_angle(cam_1.R, cam_2.R, cos_angle=True)).mean()
-    # translation distance
-    T_distance = ((cam_1.T - cam_2.T)**2).sum(1).mean()
-    # the final distance is the sum
-    return R_distance + T_distance
-
-def get_relative_camera(cams, edges):
-    """
-    For each pair of indices (i,j) in "edges" generate a camera
-    that maps from the coordinates of the camera cams[i] to 
-    the coordinates of the camera cams[j]
-    """
-
-    # first generate the world-to-view Transform3d objects of each 
-    # camera pair (i, j) according to the edges argument
-    trans_i, trans_j = [
-        SfMPerspectiveCameras(
-            R = cams.R[edges[:, i]],
-            T = cams.T[edges[:, i]],
-            device = "cuda",
-        ).get_world_to_view_transform()
-         for i in (0, 1)
-    ]
-    
-    # compose the relative transformation as g_i^{-1} g_j
-    trans_rel = trans_i.inverse().compose(trans_j)
-    
-    # generate a camera from the relative transform
-    matrix_rel = trans_rel.get_matrix()
-    cams_relative = SfMPerspectiveCameras(
-                        R = matrix_rel[:, :3, :3],
-                        T = matrix_rel[:, 3, :3],
-                        device = "cuda",
-                    )
-    return cams_relative
-
-
-
-
-
-
-
-
-

3. Optimization

Finally, we start the optimization of the absolute cameras.

-

We use SGD with momentum and optimize over log_R_absolute and T_absolute.

-

As mentioned earlier, log_R_absolute is the axis angle representation of the rotation part of our absolute cameras. We can obtain the 3x3 rotation matrix R_absolute that corresponds to log_R_absolute with:

-

R_absolute = so3_exponential_map(log_R_absolute)

-
-
-
-
-
-
In [ ]:
-
-
-
# initialize the absolute log-rotations/translations with random entries
-log_R_absolute_init = torch.randn(N, 3).float().cuda()
-T_absolute_init = torch.randn(N, 3).float().cuda()
-
-# futhermore, we know that the first camera is a trivial one 
-#    (see the description above)
-log_R_absolute_init[0, :] = 0.
-T_absolute_init[0, :] = 0.
-
-# instantiate a copy of the initialization of log_R / T
-log_R_absolute = log_R_absolute_init.clone().detach()
-log_R_absolute.requires_grad = True
-T_absolute = T_absolute_init.clone().detach()
-T_absolute.requires_grad = True
-
-# the mask the specifies which cameras are going to be optimized
-#     (since we know the first camera is already correct, 
-#      we only optimize over the 2nd-to-last cameras)
-camera_mask = torch.ones(N, 1).float().cuda()
-camera_mask[0] = 0.
-
-# init the optimizer
-optimizer = torch.optim.SGD([log_R_absolute, T_absolute], lr=.1, momentum=0.9)
-
-# run the optimization
-n_iter = 2000  # fix the number of iterations
-for it in range(n_iter):
-    # re-init the optimizer gradients
-    optimizer.zero_grad()
-
-    # compute the absolute camera rotations as 
-    # an exponential map of the logarithms (=axis-angles)
-    # of the absolute rotations
-    R_absolute = so3_exponential_map(log_R_absolute * camera_mask)
-
-    # get the current absolute cameras
-    cameras_absolute = SfMPerspectiveCameras(
-        R = R_absolute,
-        T = T_absolute * camera_mask,
-        device = "cuda",
-    )
-
-    # compute the relative cameras as a compositon of the absolute cameras
-    cameras_relative_composed = \
-        get_relative_camera(cameras_absolute, relative_edges)
-
-    # compare the composed cameras with the ground truth relative cameras
-    # camera_distance corresponds to $d$ from the description
-    camera_distance = \
-        calc_camera_distance(cameras_relative_composed, cameras_relative)
-
-    # our loss function is the camera_distance
-    camera_distance.backward()
-    
-    # apply the gradients
-    optimizer.step()
-
-    # plot and print status message
-    if it % 200==0 or it==n_iter-1:
-        status = 'iteration=%3d; camera_distance=%1.3e' % (it, camera_distance)
-        plot_camera_scene(cameras_absolute, cameras_absolute_gt, status)
-
-print('Optimization finished.')
-
-
-
-
-
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-
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\ No newline at end of file diff --git a/tutorials/camera_position_optimization_with_differentiable_rendering.html b/tutorials/camera_position_optimization_with_differentiable_rendering.html deleted file mode 100644 index 67efc010..00000000 --- a/tutorials/camera_position_optimization_with_differentiable_rendering.html +++ /dev/null @@ -1,3815 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [5]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Camera position optimization using differentiable rendering

In this tutorial we will learn the [x, y, z] position of a camera given a reference image using differentiable rendering.

-

We will first initialize a renderer with a starting position for the camera. We will then use this to generate an image, compute a loss with the reference image, and finally backpropagate through the entire pipeline to update the position of the camera.

-

This tutorial shows how to:

-
    -
  • load a mesh from an .obj file
    • -
  • initialize a Camera, Shader and Renderer,
    • -
  • render a mesh
    • -
  • set up an optimization loop with a loss function and optimizer
    • -
-
-
-
-
-
-
-

Set up and imports

-
-
-
-
-
-
In [5]:
-
-
-
import os
-import torch
-import numpy as np
-from tqdm import tqdm_notebook
-import imageio
-import torch.nn as nn
-import torch.nn.functional as F
-import matplotlib.pyplot as plt
-from skimage import img_as_ubyte
-
-# io utils
-from pytorch3d.io import load_obj
-
-# datastructures
-from pytorch3d.structures import Meshes, Textures
-
-# 3D transformations functions
-from pytorch3d.transforms import Rotate, Translate
-
-# rendering components
-from pytorch3d.renderer import (
-    OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, 
-    RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams,
-    SilhouetteShader, PhongShader, PointLights
-)
-
-
-
-
-
-
-
-
-

Load the Obj

We will load an obj file and create a Meshes object. Meshes is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes. It has several useful class methods which are used in the rendering pipeline.

-
-
-
-
-
-
In [6]:
-
-
-
# Set the cuda device 
-device = torch.device("cuda:0")
-torch.cuda.set_device(device)
-
-# Load the obj and ignore the textures and materials.
-verts, faces_idx, _ = load_obj("./data/teapot.obj")
-faces = faces_idx.verts_idx
-
-# Initialize each vertex to be white in color.
-verts_rgb = torch.ones_like(verts)[None]  # (1, V, 3)
-textures = Textures(verts_rgb=verts_rgb.to(device))
-
-# Create a Meshes object for the teapot. Here we have only one mesh in the batch.
-teapot_mesh = Meshes(
-    verts=[verts.to(device)],   
-    faces=[faces.to(device)], 
-    textures=textures
-)
-
-
-
-
-
-
-
-
-

Optimization setup

-
-
-
-
-
-
-

Create a renderer

A renderer in PyTorch3d is composed of a rasterizer and a shader which each have a number of subcomponents such as a camera (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest.

-

For optimizing the camera position we will use a renderer which produces a silhouette of the object only and does not apply any lighting or shading. We will also initialize another renderer which applies full phong shading and use this for visualizing the outputs.

-
-
-
-
-
-
In [7]:
-
-
-
# Initialize an OpenGL perspective camera.
-cameras = OpenGLPerspectiveCameras(device=device)
-
-# To blend the 100 faces we set a few parameters which control the opacity and the sharpness of 
-# edges. Refer to blending.py for more details. 
-blend_params = BlendParams(sigma=1e-4, gamma=1e-4)
-
-# Define the settings for rasterization and shading. Here we set the output image to be of size
-# 256x256. To form the blended image we use 100 faces for each pixel. Refer to rasterize_meshes.py
-# for an explanation of this parameter. 
-raster_settings = RasterizationSettings(
-    image_size=256, 
-    blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, 
-    faces_per_pixel=100, 
-    bin_size=0
-)
-
-# Create a silhouette mesh renderer by composing a rasterizer and a shader. 
-silhouette_renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=SilhouetteShader(blend_params=blend_params)
-)
-
-
-# We will also create a phong renderer. This is simpler and only needs to render one face per pixel.
-raster_settings = RasterizationSettings(
-    image_size=256, 
-    blur_radius=0.0, 
-    faces_per_pixel=1, 
-    bin_size=0
-)
-# We can add a point light in front of the object. 
-lights = PointLights(device=device, location=((2.0, 2.0, -2.0),))
-phong_renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=PhongShader(device=device, lights=lights)
-)
-
-
-
-
-
-
-
-
-

Create a reference image

We will first position the teapot and generate an image. We use helper functions to rotate the teapot to a desired viewpoint. Then we can use the renderers to produce an image. Here we will use both renderers and visualize the silhouette and full shaded image.

-
-
-
-
-
-
In [8]:
-
-
-
# Select the viewpoint using spherical angles  
-distance = 3   # distance from camera to the object
-elevation = 40.0   # angle of elevation in degrees
-azimuth = 10.0  # angle of azimuth rotation in degrees
-
-# Get the position of the camera based on the spherical angles
-R, T = look_at_view_transform(distance, elevation, azimuth, device=device)
-
-# Render the teapot providing the values of R and T. 
-silhouete = silhouette_renderer(meshes_world=teapot_mesh, R=R, T=T)
-image_ref = phong_renderer(meshes_world=teapot_mesh, R=R, T=T)
-
-silhouete = silhouete.cpu().numpy()
-image_ref = image_ref.cpu().numpy()
-
-plt.figure(figsize=(10, 10))
-plt.subplot(1, 2, 1)
-plt.imshow(silhouete.squeeze()[..., 3])  # only plot the alpha channel of the RGBA image
-plt.grid("off")
-plt.subplot(1, 2, 2)
-plt.imshow(image_ref.squeeze())
-plt.grid("off")
-
-
-
-
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Set up a basic model

Here we create a simple model class and initialize a parameter for the camera position.

-
-
-
-
-
-
In [10]:
-
-
-
class Model(nn.Module):
-    def __init__(self, meshes, renderer, image_ref):
-        super().__init__()
-        self.meshes = meshes
-        self.device = meshes.device
-        self.renderer = renderer
-        
-        # Get the silhouette of the reference RGB image by finding all the non zero values. 
-        image_ref = torch.from_numpy((image_ref[..., :3].max(-1) != 0).astype(np.float32))
-        self.register_buffer('image_ref', image_ref)
-        
-        # Create an optimizable parameter for the x, y, z position of the camera. 
-        self.camera_position = nn.Parameter(
-            torch.from_numpy(np.array([3.0,  6.9, -2.5], dtype=np.float32)).to(meshes.device))
-
-    def forward(self):
-        
-        # Render the image using the updated camera position. Based on the new position of the 
-        # camer we calculate the rotation and translation matrices
-        R = look_at_rotation(self.camera_position[None, :], device=self.device)  # (1, 3, 3)
-        T = -torch.bmm(R.transpose(1, 2), self.camera_position[None, :, None])[:, :, 0]   # (1, 3)
-        
-        image = self.renderer(meshes_world=self.meshes.clone(), R=R, T=T)
-        
-        # Calculate the silhouette loss
-        loss = torch.sum((image[..., 3] - self.image_ref) ** 2)
-        return loss, image
-  
-
-
-
-
-
-
-
-
-

Initialize the model and optimizer

Now we can create an instance of the model above and set up an optimizer for the camera position parameter.

-
-
-
-
-
-
In [11]:
-
-
-
# We will save images periodically and compose them into a GIF.
-filename_output = "./teapot_optimization_demo.gif"
-writer = imageio.get_writer(filename_output, mode='I', duration=0.3)
-
-# Initialize a model using the renderer, mesh and reference image
-model = Model(meshes=teapot_mesh, renderer=silhouette_renderer, image_ref=image_ref).to(device)
-
-# Create an optimizer. Here we are using Adam and we pass in the parameters of the model
-optimizer = torch.optim.Adam(model.parameters(), lr=0.05)
-
-
-
-
-
-
-
-
-

Visualise the starting position and the reference position

-
-
-
-
-
-
In [12]:
-
-
-
plt.figure(figsize=(10, 10))
-
-_, image_init = model()
-plt.subplot(1, 2, 1)
-plt.imshow(image_init.detach().squeeze().cpu().numpy()[..., 3])
-plt.grid("off")
-plt.title("Starting position")
-
-plt.subplot(1, 2, 2)
-plt.imshow(model.image_ref.cpu().numpy().squeeze())
-plt.grid("off")
-plt.title("Reference silhouette")
-
-
-
-
-
-
-
-
Out[12]:
-
-
Text(0.5,1,'Reference silhouette')
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Run the optimization

We run several iterations of the forward and backward pass and save outputs every 10 iterations. When this has finished take a look at ./teapot_optimization_demo.gif for a cool gif of the optimization process!

-
-
-
-
-
-
In [13]:
-
-
-
loop = tqdm_notebook(range(200))
-for i in loop:
-    optimizer.zero_grad()
-    loss, _ = model()
-    loss.backward()
-    optimizer.step()
-    
-    loop.set_description('Optimizing (loss %.4f)' % loss.data)
-    
-    if loss.item() < 200:
-        break
-    
-    # Save outputs to create a GIF. 
-    if i % 10 == 0:
-        R = look_at_rotation(model.camera_position[None, :], device=model.device)
-        T = -torch.bmm(R.transpose(1, 2), model.camera_position[None, :, None])[:, :, 0]   # (1, 3)
-        image = phong_renderer(meshes_world=model.meshes.clone(), R=R, T=T)
-        image = image[0, ..., :3].detach().squeeze().cpu().numpy()
-        image = img_as_ubyte(image)
-        writer.append_data(image)
-        
-        plt.figure()
-        plt.imshow(image[..., :3])
-        plt.title("iter: %d, loss: %0.2f" % (i, loss.data))
-        plt.grid("off")
-        plt.axis("off")
-    
-writer.close()
-
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\ No newline at end of file diff --git a/tutorials/camera_position_optimization_with_differentiable_rendering/index.html b/tutorials/camera_position_optimization_with_differentiable_rendering/index.html deleted file mode 100644 index 67efc010..00000000 --- a/tutorials/camera_position_optimization_with_differentiable_rendering/index.html +++ /dev/null @@ -1,3815 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [5]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Camera position optimization using differentiable rendering

In this tutorial we will learn the [x, y, z] position of a camera given a reference image using differentiable rendering.

-

We will first initialize a renderer with a starting position for the camera. We will then use this to generate an image, compute a loss with the reference image, and finally backpropagate through the entire pipeline to update the position of the camera.

-

This tutorial shows how to:

-
    -
  • load a mesh from an .obj file
    • -
  • initialize a Camera, Shader and Renderer,
    • -
  • render a mesh
    • -
  • set up an optimization loop with a loss function and optimizer
    • -
-
-
-
-
-
-
-

Set up and imports

-
-
-
-
-
-
In [5]:
-
-
-
import os
-import torch
-import numpy as np
-from tqdm import tqdm_notebook
-import imageio
-import torch.nn as nn
-import torch.nn.functional as F
-import matplotlib.pyplot as plt
-from skimage import img_as_ubyte
-
-# io utils
-from pytorch3d.io import load_obj
-
-# datastructures
-from pytorch3d.structures import Meshes, Textures
-
-# 3D transformations functions
-from pytorch3d.transforms import Rotate, Translate
-
-# rendering components
-from pytorch3d.renderer import (
-    OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, 
-    RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams,
-    SilhouetteShader, PhongShader, PointLights
-)
-
-
-
-
-
-
-
-
-

Load the Obj

We will load an obj file and create a Meshes object. Meshes is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes. It has several useful class methods which are used in the rendering pipeline.

-
-
-
-
-
-
In [6]:
-
-
-
# Set the cuda device 
-device = torch.device("cuda:0")
-torch.cuda.set_device(device)
-
-# Load the obj and ignore the textures and materials.
-verts, faces_idx, _ = load_obj("./data/teapot.obj")
-faces = faces_idx.verts_idx
-
-# Initialize each vertex to be white in color.
-verts_rgb = torch.ones_like(verts)[None]  # (1, V, 3)
-textures = Textures(verts_rgb=verts_rgb.to(device))
-
-# Create a Meshes object for the teapot. Here we have only one mesh in the batch.
-teapot_mesh = Meshes(
-    verts=[verts.to(device)],   
-    faces=[faces.to(device)], 
-    textures=textures
-)
-
-
-
-
-
-
-
-
-

Optimization setup

-
-
-
-
-
-
-

Create a renderer

A renderer in PyTorch3d is composed of a rasterizer and a shader which each have a number of subcomponents such as a camera (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest.

-

For optimizing the camera position we will use a renderer which produces a silhouette of the object only and does not apply any lighting or shading. We will also initialize another renderer which applies full phong shading and use this for visualizing the outputs.

-
-
-
-
-
-
In [7]:
-
-
-
# Initialize an OpenGL perspective camera.
-cameras = OpenGLPerspectiveCameras(device=device)
-
-# To blend the 100 faces we set a few parameters which control the opacity and the sharpness of 
-# edges. Refer to blending.py for more details. 
-blend_params = BlendParams(sigma=1e-4, gamma=1e-4)
-
-# Define the settings for rasterization and shading. Here we set the output image to be of size
-# 256x256. To form the blended image we use 100 faces for each pixel. Refer to rasterize_meshes.py
-# for an explanation of this parameter. 
-raster_settings = RasterizationSettings(
-    image_size=256, 
-    blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, 
-    faces_per_pixel=100, 
-    bin_size=0
-)
-
-# Create a silhouette mesh renderer by composing a rasterizer and a shader. 
-silhouette_renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=SilhouetteShader(blend_params=blend_params)
-)
-
-
-# We will also create a phong renderer. This is simpler and only needs to render one face per pixel.
-raster_settings = RasterizationSettings(
-    image_size=256, 
-    blur_radius=0.0, 
-    faces_per_pixel=1, 
-    bin_size=0
-)
-# We can add a point light in front of the object. 
-lights = PointLights(device=device, location=((2.0, 2.0, -2.0),))
-phong_renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=PhongShader(device=device, lights=lights)
-)
-
-
-
-
-
-
-
-
-

Create a reference image

We will first position the teapot and generate an image. We use helper functions to rotate the teapot to a desired viewpoint. Then we can use the renderers to produce an image. Here we will use both renderers and visualize the silhouette and full shaded image.

-
-
-
-
-
-
In [8]:
-
-
-
# Select the viewpoint using spherical angles  
-distance = 3   # distance from camera to the object
-elevation = 40.0   # angle of elevation in degrees
-azimuth = 10.0  # angle of azimuth rotation in degrees
-
-# Get the position of the camera based on the spherical angles
-R, T = look_at_view_transform(distance, elevation, azimuth, device=device)
-
-# Render the teapot providing the values of R and T. 
-silhouete = silhouette_renderer(meshes_world=teapot_mesh, R=R, T=T)
-image_ref = phong_renderer(meshes_world=teapot_mesh, R=R, T=T)
-
-silhouete = silhouete.cpu().numpy()
-image_ref = image_ref.cpu().numpy()
-
-plt.figure(figsize=(10, 10))
-plt.subplot(1, 2, 1)
-plt.imshow(silhouete.squeeze()[..., 3])  # only plot the alpha channel of the RGBA image
-plt.grid("off")
-plt.subplot(1, 2, 2)
-plt.imshow(image_ref.squeeze())
-plt.grid("off")
-
-
-
-
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Set up a basic model

Here we create a simple model class and initialize a parameter for the camera position.

-
-
-
-
-
-
In [10]:
-
-
-
class Model(nn.Module):
-    def __init__(self, meshes, renderer, image_ref):
-        super().__init__()
-        self.meshes = meshes
-        self.device = meshes.device
-        self.renderer = renderer
-        
-        # Get the silhouette of the reference RGB image by finding all the non zero values. 
-        image_ref = torch.from_numpy((image_ref[..., :3].max(-1) != 0).astype(np.float32))
-        self.register_buffer('image_ref', image_ref)
-        
-        # Create an optimizable parameter for the x, y, z position of the camera. 
-        self.camera_position = nn.Parameter(
-            torch.from_numpy(np.array([3.0,  6.9, -2.5], dtype=np.float32)).to(meshes.device))
-
-    def forward(self):
-        
-        # Render the image using the updated camera position. Based on the new position of the 
-        # camer we calculate the rotation and translation matrices
-        R = look_at_rotation(self.camera_position[None, :], device=self.device)  # (1, 3, 3)
-        T = -torch.bmm(R.transpose(1, 2), self.camera_position[None, :, None])[:, :, 0]   # (1, 3)
-        
-        image = self.renderer(meshes_world=self.meshes.clone(), R=R, T=T)
-        
-        # Calculate the silhouette loss
-        loss = torch.sum((image[..., 3] - self.image_ref) ** 2)
-        return loss, image
-  
-
-
-
-
-
-
-
-
-

Initialize the model and optimizer

Now we can create an instance of the model above and set up an optimizer for the camera position parameter.

-
-
-
-
-
-
In [11]:
-
-
-
# We will save images periodically and compose them into a GIF.
-filename_output = "./teapot_optimization_demo.gif"
-writer = imageio.get_writer(filename_output, mode='I', duration=0.3)
-
-# Initialize a model using the renderer, mesh and reference image
-model = Model(meshes=teapot_mesh, renderer=silhouette_renderer, image_ref=image_ref).to(device)
-
-# Create an optimizer. Here we are using Adam and we pass in the parameters of the model
-optimizer = torch.optim.Adam(model.parameters(), lr=0.05)
-
-
-
-
-
-
-
-
-

Visualise the starting position and the reference position

-
-
-
-
-
-
In [12]:
-
-
-
plt.figure(figsize=(10, 10))
-
-_, image_init = model()
-plt.subplot(1, 2, 1)
-plt.imshow(image_init.detach().squeeze().cpu().numpy()[..., 3])
-plt.grid("off")
-plt.title("Starting position")
-
-plt.subplot(1, 2, 2)
-plt.imshow(model.image_ref.cpu().numpy().squeeze())
-plt.grid("off")
-plt.title("Reference silhouette")
-
-
-
-
-
-
-
-
Out[12]:
-
-
Text(0.5,1,'Reference silhouette')
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Run the optimization

We run several iterations of the forward and backward pass and save outputs every 10 iterations. When this has finished take a look at ./teapot_optimization_demo.gif for a cool gif of the optimization process!

-
-
-
-
-
-
In [13]:
-
-
-
loop = tqdm_notebook(range(200))
-for i in loop:
-    optimizer.zero_grad()
-    loss, _ = model()
-    loss.backward()
-    optimizer.step()
-    
-    loop.set_description('Optimizing (loss %.4f)' % loss.data)
-    
-    if loss.item() < 200:
-        break
-    
-    # Save outputs to create a GIF. 
-    if i % 10 == 0:
-        R = look_at_rotation(model.camera_position[None, :], device=model.device)
-        T = -torch.bmm(R.transpose(1, 2), model.camera_position[None, :, None])[:, :, 0]   # (1, 3)
-        image = phong_renderer(meshes_world=model.meshes.clone(), R=R, T=T)
-        image = image[0, ..., :3].detach().squeeze().cpu().numpy()
-        image = img_as_ubyte(image)
-        writer.append_data(image)
-        
-        plt.figure()
-        plt.imshow(image[..., :3])
-        plt.title("iter: %d, loss: %0.2f" % (i, loss.data))
-        plt.grid("off")
-        plt.axis("off")
-    
-writer.close()
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\ No newline at end of file diff --git a/tutorials/deform_source_mesh_to_target_mesh.html b/tutorials/deform_source_mesh_to_target_mesh.html deleted file mode 100644 index c363063c..00000000 --- a/tutorials/deform_source_mesh_to_target_mesh.html +++ /dev/null @@ -1,15018 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
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In [1]:
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
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-

Deform a source mesh to form a target mesh using 3D loss functions

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-

In this tutorial, we learn to deform an initial generic shape (e.g. sphere) to fit a target shape.

-

We will cover:

-
    -
  • How to load a mesh from an .obj file
    • -
  • How to use the PyTorch3d Meshes datastructure
    • -
  • How to use 4 different PyTorch3d mesh loss functions
    • -
  • How to set up an optimization loop
    • -
-

Starting from a sphere mesh, we learn the offset to each vertex in the mesh such that -the predicted mesh is closer to the target mesh at each optimization step. To achieve this we minimize:

-
    -
  • chamfer_distance, the distance between the predicted (deformed) and target mesh, defined as the chamfer distance between the set of pointclouds resulting from differentiably sampling points from their surfaces.
    • -
-

However, solely minimizing the chamfer distance between the predicted and the target mesh will lead to a non-smooth shape (verify this by setting w_chamfer=1.0 and all other weights to 0.0).

-

We enforce smoothness by adding shape regularizers to the objective. Namely, we add:

-
    -
  • mesh_edge_length, which minimizes the length of the edges in the predicted mesh.
    • -
  • mesh_normal_consistency, which enforces consistency across the normals of neighboring faces.
    • -
  • mesh_laplacian_smoothing, which is the laplacian regularizer.
    • -
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0. Import modules

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In [2]:
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import os
-import torch
-from pytorch3d.io import load_obj, save_obj
-from pytorch3d.structures import Meshes
-from pytorch3d.utils import ico_sphere
-from pytorch3d.ops import sample_points_from_meshes
-from pytorch3d.loss import (
-    chamfer_distance, 
-    mesh_edge_loss, 
-    mesh_laplacian_smoothing, 
-    mesh_normal_consistency,
-)
-import numpy as np
-from tqdm import tqdm_notebook
-%matplotlib notebook 
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.pyplot as plt
-import matplotlib as mpl
-mpl.rcParams['savefig.dpi'] = 80
-mpl.rcParams['figure.dpi'] = 80
-
-# Set the device
-device = torch.device("cuda:0")
-
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-

1. Load an obj file and create a Meshes object

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In [4]:
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# The path to the target 3D model we wish to fit
-# e.g. download https://free3d.com/3d-model/-dolphin-v1--12175.html and save in ./data/dolphin
-trg_obj = os.path.join('./data/doplhin', '10014_dolphin_v2_max2011_it2.obj')
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In [6]:
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# We read the target 3D model using load_obj
-verts, faces, aux = load_obj(trg_obj)
-
-# verts is a FloatTensor of shape (V, 3) where V is the number of vertices in the mesh
-# faces is an object which contains the following LongTensors: verts_idx, normals_idx and textures_idx
-# For this tutorial, normals and textures are ignored.
-faces_idx = faces.verts_idx.to(device)
-verts = verts.to(device)
-
-# We scale normalize and center the target mesh to fit in a sphere of radius 1 centered at (0,0,0). 
-# (scale, center) will be used to bring the predicted mesh to its original center and scale
-# Note that normalizing the target mesh, speeds up the optimization but is not necessary!
-center = verts.mean(0)
-verts = verts - center
-scale = max(verts.abs().max(0)[0])
-verts = verts / scale
-
-# We construct a Meshes structure for the target mesh
-trg_mesh = Meshes(verts=[verts], faces=[faces_idx])
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In [11]:
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# We initialize the source shape to be a sphere of radius 1
-src_mesh = ico_sphere(4, device)
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Visualize the source and target meshes

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In [12]:
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def plot_pointcloud(mesh, title=""):
-    verts = mesh.verts_packed()
-    faces = mesh.faces_packed()
-    x, y, z = verts.clone().detach().cpu().unbind(1)    
-    fig = plt.figure(figsize=(5, 5))
-    ax = Axes3D(fig)
-    ax.scatter3D(x, z, -y)
-    ax.set_xlabel('x')
-    ax.set_ylabel('z')
-    ax.set_zlabel('y')
-    ax.set_title(title)
-    plt.show()
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In [13]:
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%matplotlib notebook
-plot_pointcloud(trg_mesh, "Target mesh")
-plot_pointcloud(src_mesh, "Source mesh")
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3. Optimization loop

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In [14]:
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# We will learn to deform the source mesh by offsetting its vertices
-# The shape of the derform parameters is equal to the total number of vertices in src_mesh
-deform_verts = torch.full(src_mesh.verts_packed().shape, 0.0, device=device, requires_grad=True)
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In [15]:
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# The optimizer
-optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)
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In [16]:
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# Number of optimization steps
-Niter = 2000
-# Weight for the chamfer loss
-w_chamfer = 1.0 
-# Weight for mesh edge loss
-w_edge = 1.0 
-# Weight for mesh normal consistency
-w_normal = 0.01 
-# Weight for mesh laplacian smoothing
-w_laplacian = 0.1 
-# Plot period for the losses
-plot_period = 250
-loop = tqdm_notebook(range(Niter))
-
-chamfer_losses = []
-laplacian_losses = []
-edge_losses = []
-normal_losses = []
-
-%matplotlib inline
-
-for i in loop:
-    # Initialize optimizer
-    optimizer.zero_grad()
-    
-    # Deform the mesh
-    new_src_mesh = src_mesh.offset_verts(deform_verts)
-    
-    # We sample 5k points from the surface of each mesh 
-    sample_trg = sample_points_from_meshes(trg_mesh, 5000)
-    sample_src = sample_points_from_meshes(new_src_mesh, 5000)
-    
-    # We compare the two sets of pointclouds by computing (a) the chamfer loss
-    loss_chamfer, _ = chamfer_distance(sample_trg, sample_src)
-    
-    # and (b) the edge length of the predicted mesh
-    loss_edge = mesh_edge_loss(new_src_mesh)
-    
-    # mesh normal consistency
-    loss_normal = mesh_normal_consistency(new_src_mesh)
-    
-    # mesh laplacian smoothing
-    loss_laplacian = mesh_laplacian_smoothing(new_src_mesh, method="uniform")
-    
-    # Weighted sum of the losses
-    loss = loss_chamfer * w_chamfer + loss_edge * w_edge + loss_normal * w_normal + loss_laplacian * w_laplacian
-    
-    # Print the losses
-    loop.set_description('total_loss = %.6f' % loss)
-    
-    # Save the losses for plotting
-    chamfer_losses.append(loss_chamfer)
-    edge_losses.append(loss_edge)
-    normal_losses.append(loss_normal)
-    laplacian_losses.append(loss_laplacian)
-    
-    # Plot mesh
-    if i % plot_period == 0:
-        plot_pointcloud(new_src_mesh, title="iter: %d" % i)
-        
-    # Optimization step
-    loss.backward()
-    optimizer.step()
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4. Visualize the loss

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In [17]:
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fig = plt.figure(figsize=(13, 5))
-ax = fig.gca()
-ax.plot(chamfer_losses, label="chamfer loss")
-ax.plot(edge_losses, label="edge loss")
-ax.plot(normal_losses, label="normal loss")
-ax.plot(laplacian_losses, label="laplacian loss")
-ax.legend(fontsize="16")
-ax.set_xlabel("Iteration", fontsize="16")
-ax.set_ylabel("Loss", fontsize="16")
-ax.set_title("Loss vs iterations", fontsize="16")
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Text(0.5,1,'Loss vs iterations')
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5. Save the predicted mesh

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In [ ]:
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# Fetch the verts and faces of the final predicted mesh
-final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
-
-# Scale normalize back to the original target size
-final_verts = final_verts * scale + center
-
-# Store the predicted mesh using save_obj
-final_obj = os.path.join('./', 'final_model.obj')
-save_obj(final_obj, final_verts, final_faces)
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-

6. Conclusion

In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3d datastructure called Meshes, set up an optimization loop and use four different PyTorch3d mesh loss functions.

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\ No newline at end of file diff --git a/tutorials/deform_source_mesh_to_target_mesh/index.html b/tutorials/deform_source_mesh_to_target_mesh/index.html deleted file mode 100644 index c363063c..00000000 --- a/tutorials/deform_source_mesh_to_target_mesh/index.html +++ /dev/null @@ -1,15018 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [1]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Deform a source mesh to form a target mesh using 3D loss functions

-
-
-
-
-
-
-

In this tutorial, we learn to deform an initial generic shape (e.g. sphere) to fit a target shape.

-

We will cover:

-
    -
  • How to load a mesh from an .obj file
    • -
  • How to use the PyTorch3d Meshes datastructure
    • -
  • How to use 4 different PyTorch3d mesh loss functions
    • -
  • How to set up an optimization loop
    • -
-

Starting from a sphere mesh, we learn the offset to each vertex in the mesh such that -the predicted mesh is closer to the target mesh at each optimization step. To achieve this we minimize:

-
    -
  • chamfer_distance, the distance between the predicted (deformed) and target mesh, defined as the chamfer distance between the set of pointclouds resulting from differentiably sampling points from their surfaces.
    • -
-

However, solely minimizing the chamfer distance between the predicted and the target mesh will lead to a non-smooth shape (verify this by setting w_chamfer=1.0 and all other weights to 0.0).

-

We enforce smoothness by adding shape regularizers to the objective. Namely, we add:

-
    -
  • mesh_edge_length, which minimizes the length of the edges in the predicted mesh.
    • -
  • mesh_normal_consistency, which enforces consistency across the normals of neighboring faces.
    • -
  • mesh_laplacian_smoothing, which is the laplacian regularizer.
    • -
-
-
-
-
-
-
-

0. Import modules

-
-
-
-
-
-
In [2]:
-
-
-
import os
-import torch
-from pytorch3d.io import load_obj, save_obj
-from pytorch3d.structures import Meshes
-from pytorch3d.utils import ico_sphere
-from pytorch3d.ops import sample_points_from_meshes
-from pytorch3d.loss import (
-    chamfer_distance, 
-    mesh_edge_loss, 
-    mesh_laplacian_smoothing, 
-    mesh_normal_consistency,
-)
-import numpy as np
-from tqdm import tqdm_notebook
-%matplotlib notebook 
-from mpl_toolkits.mplot3d import Axes3D
-import matplotlib.pyplot as plt
-import matplotlib as mpl
-mpl.rcParams['savefig.dpi'] = 80
-mpl.rcParams['figure.dpi'] = 80
-
-# Set the device
-device = torch.device("cuda:0")
-
-
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-
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-
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-

1. Load an obj file and create a Meshes object

-
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In [4]:
-
-
-
# The path to the target 3D model we wish to fit
-# e.g. download https://free3d.com/3d-model/-dolphin-v1--12175.html and save in ./data/dolphin
-trg_obj = os.path.join('./data/doplhin', '10014_dolphin_v2_max2011_it2.obj')
-
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In [6]:
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# We read the target 3D model using load_obj
-verts, faces, aux = load_obj(trg_obj)
-
-# verts is a FloatTensor of shape (V, 3) where V is the number of vertices in the mesh
-# faces is an object which contains the following LongTensors: verts_idx, normals_idx and textures_idx
-# For this tutorial, normals and textures are ignored.
-faces_idx = faces.verts_idx.to(device)
-verts = verts.to(device)
-
-# We scale normalize and center the target mesh to fit in a sphere of radius 1 centered at (0,0,0). 
-# (scale, center) will be used to bring the predicted mesh to its original center and scale
-# Note that normalizing the target mesh, speeds up the optimization but is not necessary!
-center = verts.mean(0)
-verts = verts - center
-scale = max(verts.abs().max(0)[0])
-verts = verts / scale
-
-# We construct a Meshes structure for the target mesh
-trg_mesh = Meshes(verts=[verts], faces=[faces_idx])
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In [11]:
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# We initialize the source shape to be a sphere of radius 1
-src_mesh = ico_sphere(4, device)
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Visualize the source and target meshes

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In [12]:
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def plot_pointcloud(mesh, title=""):
-    verts = mesh.verts_packed()
-    faces = mesh.faces_packed()
-    x, y, z = verts.clone().detach().cpu().unbind(1)    
-    fig = plt.figure(figsize=(5, 5))
-    ax = Axes3D(fig)
-    ax.scatter3D(x, z, -y)
-    ax.set_xlabel('x')
-    ax.set_ylabel('z')
-    ax.set_zlabel('y')
-    ax.set_title(title)
-    plt.show()
-
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%matplotlib notebook
-plot_pointcloud(trg_mesh, "Target mesh")
-plot_pointcloud(src_mesh, "Source mesh")
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3. Optimization loop

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In [14]:
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# We will learn to deform the source mesh by offsetting its vertices
-# The shape of the derform parameters is equal to the total number of vertices in src_mesh
-deform_verts = torch.full(src_mesh.verts_packed().shape, 0.0, device=device, requires_grad=True)
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# The optimizer
-optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)
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In [16]:
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# Number of optimization steps
-Niter = 2000
-# Weight for the chamfer loss
-w_chamfer = 1.0 
-# Weight for mesh edge loss
-w_edge = 1.0 
-# Weight for mesh normal consistency
-w_normal = 0.01 
-# Weight for mesh laplacian smoothing
-w_laplacian = 0.1 
-# Plot period for the losses
-plot_period = 250
-loop = tqdm_notebook(range(Niter))
-
-chamfer_losses = []
-laplacian_losses = []
-edge_losses = []
-normal_losses = []
-
-%matplotlib inline
-
-for i in loop:
-    # Initialize optimizer
-    optimizer.zero_grad()
-    
-    # Deform the mesh
-    new_src_mesh = src_mesh.offset_verts(deform_verts)
-    
-    # We sample 5k points from the surface of each mesh 
-    sample_trg = sample_points_from_meshes(trg_mesh, 5000)
-    sample_src = sample_points_from_meshes(new_src_mesh, 5000)
-    
-    # We compare the two sets of pointclouds by computing (a) the chamfer loss
-    loss_chamfer, _ = chamfer_distance(sample_trg, sample_src)
-    
-    # and (b) the edge length of the predicted mesh
-    loss_edge = mesh_edge_loss(new_src_mesh)
-    
-    # mesh normal consistency
-    loss_normal = mesh_normal_consistency(new_src_mesh)
-    
-    # mesh laplacian smoothing
-    loss_laplacian = mesh_laplacian_smoothing(new_src_mesh, method="uniform")
-    
-    # Weighted sum of the losses
-    loss = loss_chamfer * w_chamfer + loss_edge * w_edge + loss_normal * w_normal + loss_laplacian * w_laplacian
-    
-    # Print the losses
-    loop.set_description('total_loss = %.6f' % loss)
-    
-    # Save the losses for plotting
-    chamfer_losses.append(loss_chamfer)
-    edge_losses.append(loss_edge)
-    normal_losses.append(loss_normal)
-    laplacian_losses.append(loss_laplacian)
-    
-    # Plot mesh
-    if i % plot_period == 0:
-        plot_pointcloud(new_src_mesh, title="iter: %d" % i)
-        
-    # Optimization step
-    loss.backward()
-    optimizer.step()
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4. Visualize the loss

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In [17]:
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fig = plt.figure(figsize=(13, 5))
-ax = fig.gca()
-ax.plot(chamfer_losses, label="chamfer loss")
-ax.plot(edge_losses, label="edge loss")
-ax.plot(normal_losses, label="normal loss")
-ax.plot(laplacian_losses, label="laplacian loss")
-ax.legend(fontsize="16")
-ax.set_xlabel("Iteration", fontsize="16")
-ax.set_ylabel("Loss", fontsize="16")
-ax.set_title("Loss vs iterations", fontsize="16")
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Text(0.5,1,'Loss vs iterations')
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5. Save the predicted mesh

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In [ ]:
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# Fetch the verts and faces of the final predicted mesh
-final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
-
-# Scale normalize back to the original target size
-final_verts = final_verts * scale + center
-
-# Store the predicted mesh using save_obj
-final_obj = os.path.join('./', 'final_model.obj')
-save_obj(final_obj, final_verts, final_faces)
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6. Conclusion

In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3d datastructure called Meshes, set up an optimization loop and use four different PyTorch3d mesh loss functions.

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-
-
-
\ No newline at end of file diff --git a/tutorials/index.html b/tutorials/index.html index ee0338fb..db22d201 100644 --- a/tutorials/index.html +++ b/tutorials/index.html @@ -62,7 +62,7 @@ }; } }); -

Welcome to the PyTorch3D Tutorials

Here you can learn about the structure and applications of Pytorch3D from examples which are in the form of ipython notebooks.

Run interactively

At the top of each example you can find a button named "Open in Colab" which will open the notebook in Google Colaboratory where you can run the code directly in the browser with access to GPU support e.g.

Open In Colab

You can modify the code and experiment with varying different settings. Remember to install pytorch, torchvision, fvcore and pytorch3d in the first cell of the colab notebook by running: 

!pip install torch torchvision
-!pip install 'git+https://github.com/facebookresearch/pytorch3d.git
-
-

Run locally

There is also a button to download the notebook and source code to run it locally.

\ No newline at end of file +

Welcome to the PyTorch3D Tutorials

Here you can learn about the structure and applications of Pytorch3D from examples which are in the form of ipython notebooks.

Run interactively

At the top of each example you can find a button named "Run in Google Colab" which will open the notebook in Google Colaboratory where you can run the code directly in the browser with access to GPU support - it looks like this:

Run in Google Colab

You can modify the code and experiment with varying different settings. Remember to install pytorch, torchvision, fvcore and pytorch3d in the first cell of the colab notebook by running: 

!pip install torch torchvision
+!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
+
+
This installs the latest stable version of PyTorch3D from github.

Run locally

There is also a button to download the notebook and source code to run it locally.

\ No newline at end of file diff --git a/tutorials/render_textured_meshes.html b/tutorials/render_textured_meshes.html deleted file mode 100644 index 4d9f8780..00000000 --- a/tutorials/render_textured_meshes.html +++ /dev/null @@ -1,517 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [ ]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Render a textured mesh

This tutorial shows how to:

-
    -
  • load a mesh and textures from an .obj file.
    • -
  • set up a renderer
    • -
  • render the mesh
    • -
  • vary the rendering settings such as lighting and camera position
    • -
  • use the batching features of the pytorch3d API to render the mesh from different viewpoints
    • -
-
-
-
-
-
-
-

Import modules

-
-
-
-
-
-
In [1]:
-
-
-
import os
-import torch
-import matplotlib.pyplot as plt
-from skimage.io import imread
-
-# Util function for loading meshes
-from pytorch3d.io import load_obj
-
-# Data structures and functions for rendering
-from pytorch3d.structures import Meshes, Textures
-from pytorch3d.renderer import (
-    look_at_view_transform,
-    OpenGLPerspectiveCameras, 
-    PointLights, 
-    DirectionalLights, 
-    Materials, 
-    RasterizationSettings, 
-    MeshRenderer, 
-    MeshRasterizer,  
-    TexturedPhongShader
-)
-
-# add path for demo utils
-import sys
-import os
-sys.path.append(os.path.abspath(''))
-from utils import image_grid
-
-
-
-
-
-
-
-
-

Load a mesh and texture file

Load an .obj file and it's associated .mtl file and create a Textures and Meshes object.

-

Meshes is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes.

-

Textures is an auxillary datastructure for storing texture information about meshes.

-

Meshes has several class methods which are used throughout the rendering pipeline.

-
-
-
-
-
-
In [2]:
-
-
-
# Setup
-device = torch.device("cuda:0")
-torch.cuda.set_device(device)
-
-# Set paths
-DATA_DIR = "./data"
-obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj")
-
-# Load obj file
-verts, faces, aux = load_obj(obj_filename)
-faces_idx = faces.verts_idx.to(device)
-verts = verts.to(device)
-
-# Get textures from the outputs of the load_obj function
-# the `aux` variable contains the texture maps and vertex uv coordinates. 
-# Refer to the `obj_io.load_obj` function for full API reference. 
-# Here we only have one texture map for the whole mesh. 
-verts_uvs = aux.verts_uvs[None, ...].to(device)       # (N, V, 2)
-faces_uvs = faces.textures_idx[None, ...].to(device)  # (N, F, 3)
-tex_maps = aux.texture_images
-texture_image = list(tex_maps.values())[0]
-texture_image = texture_image[None, ...].to(device)   # (N, H, W, 3)
-
-# Create a textures object
-tex = Textures(verts_uvs=verts_uvs, faces_uvs=faces_uvs, maps=texture_image)
-
-# Create a meshes object with textures
-mesh = Meshes(verts=[verts], faces=[faces_idx], textures=tex)
-
-
-
-
-
-
-
-
-

Let's visualize the texture map

-
-
-
-
-
-
In [3]:
-
-
-
plt.figure(figsize=(7,7))
-plt.imshow(texture_image.squeeze().cpu().numpy())
-plt.grid("off")
-plt.axis('off')
-
-
-
-
-
-
-
-
Out[3]:
-
-
(-0.5, 1023.5, 1023.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Create a renderer

A renderer in PyTorch3d is composed of a rasterizer and a shader which each have a number of subcomponents such as a camera (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest.

-

In this example we will first create a renderer which uses a perspective camera, a point light and applies phong shading. Then we learn how to vary different components using the modular API.

-
-
-
-
-
-
In [4]:
-
-
-
# Initialize an OpenGL perspective camera.
-R, T = look_at_view_transform(2.7, 10, 20)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Define the settings for rasterization and shading. Here we set the output image to be of size
-# 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1
-# and blur_radius=0.0. Refer to rasterize_meshes.py for explanations of these parameters. 
-raster_settings = RasterizationSettings(
-    image_size=512, 
-    blur_radius=0.0, 
-    faces_per_pixel=1, 
-    bin_size=0
-)
-
-# Place a point light in front of the object
-lights = PointLights(device=device, location=[[1.0, 1.0, -2.0]])
-
-# Create a phong renderer by composing a rasterizer and a shader. The textured phong shader will 
-# interpolate the texture uv coordinates for each vertex, sample from a texture image and 
-# apply the Phong lighting model
-renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=TexturedPhongShader(
-        device=device, 
-        cameras=cameras,
-        lights=lights
-    )
-)
-
-
-
-
-
-
-
-
-

Render the mesh

-
-
-
-
-
-
-

The light is in front of the object so it is bright and the image has specular highlights.

-
-
-
-
-
-
In [5]:
-
-
-
images = renderer(mesh)
-plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[5]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Move the light behind the object and re-render

We can pass arbirary keyword arguments to the rasterizer/shader via the call to the renderer so the renderer does not need to be reinitialized if any of the settings change/

-

In this case, we can simply update the location of the lights and pass them into the call to the renderer.

-

The image is now dark as there is only ambient lighting, and there are no specular highlights.

-
-
-
-
-
-
In [6]:
-
-
-
lights.location = torch.tensor([0.0, 0.0, +1.0], device=device)[None]
-images = renderer(mesh, lights=lights)
-
-
-
-
-
-
-
-
In [7]:
-
-
-
plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[7]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Rotate the object, modify the material properties or light properties

We can also change many other settings in the rendering pipeline. Here we:

-
    -
  • change the viewing angle of the camera
    • -
  • change the position of the point light
    • -
  • change the material reflectance properties of the mesh
    • -
-
-
-
-
-
-
In [8]:
-
-
-
# Rotate the object by increasing the azimuth angle
-R, T = look_at_view_transform(dist=2.7, elev=10, azim=50)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Move the light location to be in front of the object again
-lights.location = torch.tensor([[5.0, 5.0, -2.0]], device=device)
-
-# Change specular color to green and change material shininess 
-materials = Materials(
-    device=device,
-    specular_color=[[0.0, 1.0, 0.0]],
-    shininess=10.0
-)
-
-# Re render the mesh, passing in keyword arguments for the modified components.
-images = renderer(mesh, lights=lights, materials=materials, cameras=cameras)
-
-
-
-
-
-
-
-
In [9]:
-
-
-
plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[9]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Batched Rendering

One of the core design choices of the PyTorch3d API is to suport batched inputs for all components. -The renderer and associated components can take batched inputs and render a batch of output images in one forward pass. We will now use this feature to render the mesh from many different viewpoints.

-
-
-
-
-
-
In [10]:
-
-
-
# Set batch size - this is the number of different viewpoints from which we want to render the mesh.
-batch_size = 20
-
-# Create a batch of meshes by repeating the cow mesh and associated textures. 
-# Meshes has a useful `extend` method which allows us do this very easily. 
-# This also extends the textures. 
-meshes = mesh.extend(batch_size)
-
-# Get a batch of viewing angles. 
-elev = torch.linspace(0, 360, batch_size)
-azim = torch.linspace(0, 360, batch_size)
-
-# All the cameras helper methods support mixed type inputs and broadcasting. So we can 
-# view the camera from the same distance and specify dist=2.7 as a float,
-# and then specify elevation and azimuth angles for each viewpoint as tensors. 
-R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Move the light back in front of the object
-lights.location = torch.tensor([[1.0, 1.0, -5.0]], device=device)
-
-
-
-
-
-
-
-
In [11]:
-
-
-
# We can pass arbirary keyword arguments to the rasterizer/shader via the renderer
-# so the renderer does not need to be reinitialized if any of the settings change.
-images = renderer(meshes, cameras=cameras, lights=lights)
-
-
-
-
-
-
-
-
In [12]:
-
-
-
image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True)
-
-
-
-
-
-
-
-
-
- -
-
-
-
-
-
\ No newline at end of file diff --git a/tutorials/render_textured_meshes/index.html b/tutorials/render_textured_meshes/index.html deleted file mode 100644 index 4d9f8780..00000000 --- a/tutorials/render_textured_meshes/index.html +++ /dev/null @@ -1,517 +0,0 @@ -PyTorch3D · A library for deep learning with 3D data
Open In Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
- - -
-
-
-
In [ ]:
-
-
-
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
-
-
-
-
-
-
-
-
-

Render a textured mesh

This tutorial shows how to:

-
    -
  • load a mesh and textures from an .obj file.
    • -
  • set up a renderer
    • -
  • render the mesh
    • -
  • vary the rendering settings such as lighting and camera position
    • -
  • use the batching features of the pytorch3d API to render the mesh from different viewpoints
    • -
-
-
-
-
-
-
-

Import modules

-
-
-
-
-
-
In [1]:
-
-
-
import os
-import torch
-import matplotlib.pyplot as plt
-from skimage.io import imread
-
-# Util function for loading meshes
-from pytorch3d.io import load_obj
-
-# Data structures and functions for rendering
-from pytorch3d.structures import Meshes, Textures
-from pytorch3d.renderer import (
-    look_at_view_transform,
-    OpenGLPerspectiveCameras, 
-    PointLights, 
-    DirectionalLights, 
-    Materials, 
-    RasterizationSettings, 
-    MeshRenderer, 
-    MeshRasterizer,  
-    TexturedPhongShader
-)
-
-# add path for demo utils
-import sys
-import os
-sys.path.append(os.path.abspath(''))
-from utils import image_grid
-
-
-
-
-
-
-
-
-

Load a mesh and texture file

Load an .obj file and it's associated .mtl file and create a Textures and Meshes object.

-

Meshes is a unique datastructure provided in PyTorch3d for working with batches of meshes of different sizes.

-

Textures is an auxillary datastructure for storing texture information about meshes.

-

Meshes has several class methods which are used throughout the rendering pipeline.

-
-
-
-
-
-
In [2]:
-
-
-
# Setup
-device = torch.device("cuda:0")
-torch.cuda.set_device(device)
-
-# Set paths
-DATA_DIR = "./data"
-obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj")
-
-# Load obj file
-verts, faces, aux = load_obj(obj_filename)
-faces_idx = faces.verts_idx.to(device)
-verts = verts.to(device)
-
-# Get textures from the outputs of the load_obj function
-# the `aux` variable contains the texture maps and vertex uv coordinates. 
-# Refer to the `obj_io.load_obj` function for full API reference. 
-# Here we only have one texture map for the whole mesh. 
-verts_uvs = aux.verts_uvs[None, ...].to(device)       # (N, V, 2)
-faces_uvs = faces.textures_idx[None, ...].to(device)  # (N, F, 3)
-tex_maps = aux.texture_images
-texture_image = list(tex_maps.values())[0]
-texture_image = texture_image[None, ...].to(device)   # (N, H, W, 3)
-
-# Create a textures object
-tex = Textures(verts_uvs=verts_uvs, faces_uvs=faces_uvs, maps=texture_image)
-
-# Create a meshes object with textures
-mesh = Meshes(verts=[verts], faces=[faces_idx], textures=tex)
-
-
-
-
-
-
-
-
-

Let's visualize the texture map

-
-
-
-
-
-
In [3]:
-
-
-
plt.figure(figsize=(7,7))
-plt.imshow(texture_image.squeeze().cpu().numpy())
-plt.grid("off")
-plt.axis('off')
-
-
-
-
-
-
-
-
Out[3]:
-
-
(-0.5, 1023.5, 1023.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Create a renderer

A renderer in PyTorch3d is composed of a rasterizer and a shader which each have a number of subcomponents such as a camera (orthgraphic/perspective). Here we initialize some of these components and use default values for the rest.

-

In this example we will first create a renderer which uses a perspective camera, a point light and applies phong shading. Then we learn how to vary different components using the modular API.

-
-
-
-
-
-
In [4]:
-
-
-
# Initialize an OpenGL perspective camera.
-R, T = look_at_view_transform(2.7, 10, 20)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Define the settings for rasterization and shading. Here we set the output image to be of size
-# 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1
-# and blur_radius=0.0. Refer to rasterize_meshes.py for explanations of these parameters. 
-raster_settings = RasterizationSettings(
-    image_size=512, 
-    blur_radius=0.0, 
-    faces_per_pixel=1, 
-    bin_size=0
-)
-
-# Place a point light in front of the object
-lights = PointLights(device=device, location=[[1.0, 1.0, -2.0]])
-
-# Create a phong renderer by composing a rasterizer and a shader. The textured phong shader will 
-# interpolate the texture uv coordinates for each vertex, sample from a texture image and 
-# apply the Phong lighting model
-renderer = MeshRenderer(
-    rasterizer=MeshRasterizer(
-        cameras=cameras, 
-        raster_settings=raster_settings
-    ),
-    shader=TexturedPhongShader(
-        device=device, 
-        cameras=cameras,
-        lights=lights
-    )
-)
-
-
-
-
-
-
-
-
-

Render the mesh

-
-
-
-
-
-
-

The light is in front of the object so it is bright and the image has specular highlights.

-
-
-
-
-
-
In [5]:
-
-
-
images = renderer(mesh)
-plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[5]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Move the light behind the object and re-render

We can pass arbirary keyword arguments to the rasterizer/shader via the call to the renderer so the renderer does not need to be reinitialized if any of the settings change/

-

In this case, we can simply update the location of the lights and pass them into the call to the renderer.

-

The image is now dark as there is only ambient lighting, and there are no specular highlights.

-
-
-
-
-
-
In [6]:
-
-
-
lights.location = torch.tensor([0.0, 0.0, +1.0], device=device)[None]
-images = renderer(mesh, lights=lights)
-
-
-
-
-
-
-
-
In [7]:
-
-
-
plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[7]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Rotate the object, modify the material properties or light properties

We can also change many other settings in the rendering pipeline. Here we:

-
    -
  • change the viewing angle of the camera
    • -
  • change the position of the point light
    • -
  • change the material reflectance properties of the mesh
    • -
-
-
-
-
-
-
In [8]:
-
-
-
# Rotate the object by increasing the azimuth angle
-R, T = look_at_view_transform(dist=2.7, elev=10, azim=50)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Move the light location to be in front of the object again
-lights.location = torch.tensor([[5.0, 5.0, -2.0]], device=device)
-
-# Change specular color to green and change material shininess 
-materials = Materials(
-    device=device,
-    specular_color=[[0.0, 1.0, 0.0]],
-    shininess=10.0
-)
-
-# Re render the mesh, passing in keyword arguments for the modified components.
-images = renderer(mesh, lights=lights, materials=materials, cameras=cameras)
-
-
-
-
-
-
-
-
In [9]:
-
-
-
plt.figure(figsize=(10, 10))
-plt.imshow(images[0, ..., :3].cpu().numpy())
-plt.grid("off")
-plt.axis("off")
-
-
-
-
-
-
-
-
Out[9]:
-
-
(-0.5, 511.5, 511.5, -0.5)
-
-
-
-
-
- -
-
-
-
-
-
-
-
-

Batched Rendering

One of the core design choices of the PyTorch3d API is to suport batched inputs for all components. -The renderer and associated components can take batched inputs and render a batch of output images in one forward pass. We will now use this feature to render the mesh from many different viewpoints.

-
-
-
-
-
-
In [10]:
-
-
-
# Set batch size - this is the number of different viewpoints from which we want to render the mesh.
-batch_size = 20
-
-# Create a batch of meshes by repeating the cow mesh and associated textures. 
-# Meshes has a useful `extend` method which allows us do this very easily. 
-# This also extends the textures. 
-meshes = mesh.extend(batch_size)
-
-# Get a batch of viewing angles. 
-elev = torch.linspace(0, 360, batch_size)
-azim = torch.linspace(0, 360, batch_size)
-
-# All the cameras helper methods support mixed type inputs and broadcasting. So we can 
-# view the camera from the same distance and specify dist=2.7 as a float,
-# and then specify elevation and azimuth angles for each viewpoint as tensors. 
-R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)
-cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
-
-# Move the light back in front of the object
-lights.location = torch.tensor([[1.0, 1.0, -5.0]], device=device)
-
-
-
-
-
-
-
-
In [11]:
-
-
-
# We can pass arbirary keyword arguments to the rasterizer/shader via the renderer
-# so the renderer does not need to be reinitialized if any of the settings change.
-images = renderer(meshes, cameras=cameras, lights=lights)
-
-
-
-
-
-
-
-
In [12]:
-
-
-
image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True)
-
-
-
-
-
-
-
-
-
- -
-
-
-
-
-
\ No newline at end of file diff --git a/users.html b/users.html index 7d0d8fb4..fbccd852 100644 --- a/users.html +++ b/users.html @@ -6,4 +6,4 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file +

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file diff --git a/users/index.html b/users/index.html index 7d0d8fb4..fbccd852 100644 --- a/users/index.html +++ b/users/index.html @@ -6,4 +6,4 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file +

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file