# pytorch_RFCN **Repository Path**: chen_hanxi/pytorch_RFCN ## Basic Information - **Project Name**: pytorch_RFCN - **Description**: pytorch version of rfcn - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2020-02-17 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # RFCN with PyTorch **Note:** This project is pytorch implementation of [RFCN](https://arxiv.org/abs/1605.06409), Resnet101_without_dilation. This project is mainly based on [faster_rcnn_pytorch](https://github.com/longcw/faster_rcnn_pytorch), while psroi_pooling modules is copied from another pytorch version of RFCN, [pytorch_RFCN](https://github.com/PureDiors/pytorch_RFCN) **Difference** Since dilation isn't used in resnet, so the space_scale is 1/32.0 in psroi_pooling, not 1/16.0 in original paper. As result, I set SCALES=800 and MAX_SIZE=1200. ### Installation and demo 0. Install the requirements (you can use pip or [Anaconda](https://www.continuum.io/downloads)): ``` conda install pip pyyaml sympy h5py cython numpy scipy conda install -c menpo opencv3 pip install easydict ``` 1. Clone the Faster RFCN repository ```bash git clone https://github.com/xingmimfl/pytorch_RFCN.git ``` 2. Build the Cython modules for nms and the roi_pooling layer ```bash cd pytorch_RFCN/faster_rcnn ./make.sh ``` ### Training on Pascal VOC 2007 This project use ResNet-101 model converted from Caffe, and you can get it following [RuotianLuo-pytorch-ResNet](https://github.com/ruotianluo/pytorch-resnet). Since the program loading the data in `pytorch_RFCN/data` by default, you can set the data path as following. ```bash cd pytorch_RFCN mkdir data cd data ln -s $VOCdevkit VOCdevkit2007 ``` Then you can set some hyper-parameters in `train.py` and training parameters in the `.yml` file. ### Evaluation Set the path of the trained model in `test.py`. ```bash cd pytorch_RFCN python demo.py ``` ![image](https://github.com/xingmimfl/pytorch_RFCN/blob/master/demo/out.jpg) License: MIT license (MIT)