https://github.com/acecoooool/roialign-roipool-pytorch

C++ extension implementation of RoIAlign & RolPool (both GPU and CPU) for PyTorch
https://github.com/acecoooool/roialign-roipool-pytorch

cpu gpu object-detection pytorch roialign roipooling

Last synced: 8 days ago
JSON representation

C++ extension implementation of RoIAlign & RolPool (both GPU and CPU) for PyTorch

• Host: GitHub
• URL: https://github.com/acecoooool/roialign-roipool-pytorch
• Owner: AceCoooool
• Created: 2018-04-19T07:27:56.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-11-24T12:25:08.000Z (almost 6 years ago)
• Last Synced: 2023-10-19T19:47:42.619Z (about 1 year ago)
• Topics: cpu, gpu, object-detection, pytorch, roialign, roipooling
• Language: C++
• Homepage:
• Size: 85.9 KB
• Stars: 71
• Watchers: 4
• Forks: 15
• Open Issues: 7
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# RoI-op-pytorch

C++ extension of RoIPool & RoIAlign (both CPU and GPU) in PyTorch，this code is converted from [caffe2](https://github.com/pytorch/pytorch/tree/master/caffe2/operators) operation. （need pytorch 0.4.0）

**Warning：**You may change `AT_CHECK` to `AT_ASSERT`（0.4 version using `AT_ASSERT`， and latest version using `AT_CHECK`）

**Note: **

1. `roi_xxx_cpu.cpp`&`roi_xxx_binding.cpp`：contains the cpu version of forward and backward operation.(Note: `roi_xxx_binding.cpp` is for pybind, you can put this code into `roi_xxx_cpu.cpp` as well) 

2. `roi_xxx_kernel.cu`&`roi_xxx_cuda.cpp`：contains the cuda version of forward and backward operation.

3. `main.py`&`temp.h`&`CMakeLists.txt`：help you to debug in c++ code, rather than to run `python setup.py install` to debug. (Note: only support cpu version ~ I don't know how to debug `.cu` code :persevere:)

4. `setup.py`：you can run `python setup.py install` to install this operation as a package (You can find this package in you python site-package)

5. `roi_xxx.py`：wrap `.cpp` code to pytorch's `Function & Module` ，there is also a small demo testing.

**Install**

```shell

cd roixxx   # roipool or roialign

python setup.py install

```

## RoI Pooling

The "strategy" of roi-pooling in this implementaion likes the follow picture:（:joy: so bad picture）

![oi_poo](png/roi_pool.png)

Note:  (please stand on point view rather than block view)

1. scale=0.5  

2. dotted line is the range of "seleted area" (int form in `[left, right)` and `[top, bottom)`)

## RoI Align

![oialig](png/roialign.png)

Note: left `sample=1`, `right sample=2`

There are several good resource to explain these two operations:

- [Region of interest pooling explained](https://blog.deepsense.ai/region-of-interest-pooling-explained/)

- [ROI Align --- chinese](http://blog.leanote.com/post/[email protected]/b5f4f526490b)

- [ROI Align --- youtube](https://www.youtube.com/watch?v=XGi-Mz3do2s)

### Reference

1. [caffe2 operator](https://github.com/pytorch/pytorch/tree/a2a28c0ef1d9a433972fe72fa5b0b9b850ccfcaf/caffe2/operators)：most of the code is coming from here.

2. [extension-cpp: tutorial](https://github.com/pytorch/extension-cpp)

3. [detectorch](https://github.com/ignacio-rocco/detectorch)