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Non Square image rasterization for pointclouds

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Summary:
Similar to non square image rasterization for meshes, apply the same updates to the pointcloud rasterizer.

Main API Change:
- PointRasterizationSettings now accepts a tuple/list of (H, W) for the image size.

Reviewed By: jcjohnson

Differential Revision: D25465206

fbshipit-source-id: 7370d83c431af1b972158cecae19d82364623380
This commit is contained in:
Nikhila Ravi
2020-12-15 14:14:27 -08:00
committed by Facebook GitHub Bot
parent 569e5229a9
commit 3d769a66cb
22 changed files with 712 additions and 263 deletions
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16
pytorch3d/csrc/compositing/alpha_composite.cu
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@@ -30,15 +30,15 @@ __global__ void alphaCompositeCudaForwardKernel(
// Get the batch and index
const int batch = blockIdx.x;
const int num_pixels = C * W * H;
const int num_pixels = C * H * W;
const int num_threads = gridDim.y * blockDim.x;
const int tid = blockIdx.y * blockDim.x + threadIdx.x;
// Iterate over each feature in each pixel
for (int pid = tid; pid < num_pixels; pid += num_threads) {
int ch = pid / (W * H);
int j = (pid % (W * H)) / H;
int i = (pid % (W * H)) % H;
int ch = pid / (H * W);
int j = (pid % (H * W)) / W;
int i = (pid % (H * W)) % W;
// alphacomposite the different values
float cum_alpha = 1.;
@@ -81,16 +81,16 @@ __global__ void alphaCompositeCudaBackwardKernel(
// Get the batch and index
const int batch = blockIdx.x;
const int num_pixels = C * W * H;
const int num_pixels = C * H * W;
const int num_threads = gridDim.y * blockDim.x;
const int tid = blockIdx.y * blockDim.x + threadIdx.x;
// Parallelize over each feature in each pixel in images of size H * W,
// for each image in the batch of size batch_size
for (int pid = tid; pid < num_pixels; pid += num_threads) {
int ch = pid / (W * H);
int j = (pid % (W * H)) / H;
int i = (pid % (W * H)) % H;
int ch = pid / (H * W);
int j = (pid % (H * W)) / W;
int i = (pid % (H * W)) % W;
// alphacomposite the different values
float cum_alpha = 1.;