PointRend复现

# PointRend A PyTorch implementation of `PointRend: Image Segmentation as Rendering`  ### [[arxiv]](https://arxiv.org/pdf/1912.08193.pdf) [[Official Implementation: Detectron2]](https://github.com/facebookresearch/detectron2/tree/master/projects/PointRend) <hr> This repo for Only Semantic Segmentation on the PascalVOC dataset. Many details differ from the paper for feasibilty check. <hr> ## Reproduce Fig 5. Sampled Points showing from different strategies on A Dog image. See [test_point_sampling.ipynb](tests/test_point_sampling.ipynb) Original Figure  Reference : [Pytorch Deeplab Tutorial](https://pytorch.org/hub/pytorch_vision_deeplabv3_resnet101/) <hr> ## How to use: First, fix data path in [default.yaml](config/default.yaml) Multi GPU Training See details in `Single GPU Training` ``` ➜ python3 -m torch.distributed.launch --nproc_per_node={your_gpus} main.py -h ``` Sinle GPU Training ``` ➜ python3 main.py -h usage: main.py [-h] config save PyTorch Object Detection Training positional arguments: config It must be config/*.yaml save Save path in out directory optional arguments: -h, --help show this help message and exit ``` e.g.) ``` python3 main.py config/default.yaml test_codes ``` <hr>