ChamferDistancePytorch:Pytorch 中的倒角距离与 f-score

`pip install torch ninja` # Pytorch Chamfer Distance. Include a **CUDA** version, and a **PYTHON** version with pytorch standard operations. NB : In this depo, dist1 and dist2 are squared pointcloud euclidean distances, so you should adapt thresholds accordingly. - [x] F - Score ### CUDA VERSION - [x] JIT compilation - [x] Supports multi-gpu - [x] 2D point clouds. - [x] 3D point clouds. - [x] 5D point clouds. - [x] Contiguous() safe. ### Python Version - [x] Supports any dimension ### Usage ```python import torch, chamfer3D.dist_chamfer_3D, fscore chamLoss = chamfer3D.dist_chamfer_3D.chamfer_3DDist() points1 = torch.rand(32, 1000, 3).cuda() points2 = torch.rand(32, 2000, 3, requires_grad=True).cuda() dist1, dist2, idx1, idx2 = chamLoss(points1, points2) f_score, precision, recall = fscore.fscore(dist1, dist2) ``` ### Add it to your project as a submodule ```shell git submodule add https://github.com/ThibaultGROUEIX/ChamferDistancePytorch ``` ### Benchmark: [forward + backward] pass - [x] CUDA 10.1, NVIDIA 435, Pytorch 1.4 - [x] p1 : 32 x 2000 x dim - [x] p2 : 32 x 1000 x dim | *Timing (sec * 1000)* | 2D | 3D | 5D | | ---------- | -------- | ------- | ------- | | **Cuda Compiled** | **1.2** | 1.4 |1.8 | | **Cuda JIT** | 1.3 | **1.4** |**1.5** | | **Python** | 37 | 37 | 37 | | *Memory (MB)* | 2D | 3D | 5D | | ---------- | -------- | ------- | ------- | | **Cuda Compiled** | 529 | 529 | 549 | | **Cuda JIT** | **520** | **529** |**549** | | **Python** | 2495 | 2495 | 2495 | ### What is the chamfer distance ? [Stanford course](http://graphics.stanford.edu/courses/cs468-17-spring/LectureSlides/L14%20-%203d%20deep%20learning%20on%20point%20cloud%20representation%20(analysis).pdf) on 3D deep Learning ### Aknowledgment Original backbone from [Fei Xia](https://github.com/fxia22/pointGAN/blob/master/nndistance/src/nnd_cuda.cu). JIT cool trick from [Christian Diller](https://github.com/chrdiller) ### Troubleshoot - `Undefined symbol: Zxxxxxxxxxxxxxxxxx `: --> Fix: Make sure to `import torch` before you `import chamfer`. --> Use pytorch.version >= 1.1.0 - [RuntimeError: Ninja is required to load C++ extension](https://github.com/zhanghang1989/PyTorch-Encoding/issues/167) ```shell wget https://github.com/ninja-build/ninja/releases/download/v1.8.2/ninja-linux.zip sudo unzip ninja-linux.zip -d /usr/local/bin/ sudo update-alternatives --install /usr/bin/ninja ninja /usr/local/bin/ninja 1 --force ``` #### TODO: * Discuss behaviour of torch.min() and tensor.min() which causes issues in some pytorch versions