Changes for CO3Dv2 release [part1]

Summary:
Implements several changes needed for the CO3Dv2 release:
- FrameData contains crop_bbox_xywh which defines the outline of the image crop corresponding to the image-shaped tensors in FrameData
- revised the definition of a bounding box inside JsonDatasetIndex: bbox_xyxy is [xmin, ymin, xmax, ymax], where xmax, ymax are not inclusive; bbox_xywh = [xmin, ymain, xmax-xmin, ymax-ymin]
- is_filtered for detecting whether the entries of the dataset were somehow filtered
- seq_frame_index_to_dataset_index allows to skip entries that are not present in the dataset

Reviewed By: shapovalov

Differential Revision: D37687547

fbshipit-source-id: 7842756b0517878cc0964fc0935d3c0769454d78

tests/implicitron/test_bbox.py

@@ -0,0 +1,78 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+import unittest
+
+import numpy as np
+
+import torch
+from pytorch3d.implicitron.dataset.json_index_dataset import (
+    _bbox_xywh_to_xyxy,
+    _bbox_xyxy_to_xywh,
+    _get_bbox_from_mask,
+)
+from tests.common_testing import TestCaseMixin
+
+
+class TestBBox(TestCaseMixin, unittest.TestCase):
+    def setUp(self):
+        torch.manual_seed(42)
+
+    def test_bbox_conversion(self):
+        bbox_xywh_list = torch.LongTensor(
+            [
+                [0, 0, 10, 20],
+                [10, 20, 5, 1],
+                [10, 20, 1, 1],
+                [5, 4, 0, 1],
+            ]
+        )
+        for bbox_xywh in bbox_xywh_list:
+            bbox_xyxy = _bbox_xywh_to_xyxy(bbox_xywh)
+            bbox_xywh_ = _bbox_xyxy_to_xywh(bbox_xyxy)
+            bbox_xyxy_ = _bbox_xywh_to_xyxy(bbox_xywh_)
+            self.assertClose(bbox_xywh_, bbox_xywh)
+            self.assertClose(bbox_xyxy, bbox_xyxy_)
+
+    def test_compare_to_expected(self):
+        bbox_xywh_to_xyxy_expected = torch.LongTensor(
+            [
+                [[0, 0, 10, 20], [0, 0, 10, 20]],
+                [[10, 20, 5, 1], [10, 20, 15, 21]],
+                [[10, 20, 1, 1], [10, 20, 11, 21]],
+                [[5, 4, 0, 1], [5, 4, 5, 5]],
+            ]
+        )
+        for bbox_xywh, bbox_xyxy_expected in bbox_xywh_to_xyxy_expected:
+            self.assertClose(_bbox_xywh_to_xyxy(bbox_xywh), bbox_xyxy_expected)
+            self.assertClose(_bbox_xyxy_to_xywh(bbox_xyxy_expected), bbox_xywh)
+
+        clamp_amnt = 3
+        bbox_xywh_to_xyxy_clamped_expected = torch.LongTensor(
+            [
+                [[0, 0, 10, 20], [0, 0, 10, 20]],
+                [[10, 20, 5, 1], [10, 20, 15, 20 + clamp_amnt]],
+                [[10, 20, 1, 1], [10, 20, 10 + clamp_amnt, 20 + clamp_amnt]],
+                [[5, 4, 0, 1], [5, 4, 5 + clamp_amnt, 4 + clamp_amnt]],
+            ]
+        )
+        for bbox_xywh, bbox_xyxy_expected in bbox_xywh_to_xyxy_clamped_expected:
+            self.assertClose(
+                _bbox_xywh_to_xyxy(bbox_xywh, clamp_size=clamp_amnt),
+                bbox_xyxy_expected,
+            )
+
+    def test_mask_to_bbox(self):
+        mask = np.array(
+            [
+                [0, 0, 0, 0, 0, 0],
+                [0, 0, 1, 1, 0, 0],
+                [0, 0, 0, 0, 0, 0],
+            ]
+        ).astype(np.float32)
+        expected_bbox_xywh = [2, 1, 2, 1]
+        bbox_xywh = _get_bbox_from_mask(mask, 0.5)
+        self.assertClose(bbox_xywh, expected_bbox_xywh)

tests/implicitron/test_dataset_visualize.py

@@ -14,6 +14,7 @@ import torch
 import torchvision
 from pytorch3d.implicitron.dataset.json_index_dataset import JsonIndexDataset
 from pytorch3d.implicitron.dataset.visualize import get_implicitron_sequence_pointcloud
+from pytorch3d.implicitron.tools.config import expand_args_fields
 from pytorch3d.implicitron.tools.point_cloud_utils import render_point_cloud_pytorch3d
 from pytorch3d.vis.plotly_vis import plot_scene
 
@@ -37,6 +38,7 @@ class TestDatasetVisualize(unittest.TestCase):
         frame_file = os.path.join(dataset_root, category, "frame_annotations.jgz")
         sequence_file = os.path.join(dataset_root, category, "sequence_annotations.jgz")
         self.image_size = 256
+        expand_args_fields(JsonIndexDataset)
         self.datasets = {
             "simple": JsonIndexDataset(
                 frame_annotations_file=frame_file,