By Yunhang Shen, Rongrong Ji, Zhiwei Chen, Xiaopeng Hong, Feng Zheng, Jianzhuang Liu, Mingliang Xu, Qi Tian.
CVPR 2020 Paper.
This project is based on Detectron.
NA-fWebSOD is released under the Apache 2.0 license. See the NOTICE file for additional details.
If you find NA-fWebSOD useful in your research, please consider citing:
@inproceedings{NA-fWebSOD_2020_CVPR,
author = {Shen, Yunhang and Ji, Rongrong and Chen, Zhiwei and Hong, Xiaopeng and Zheng, Feng and Liu, Jianzhuang and Xu, Mingliang and Tian, Qi},
title = {Noise-Aware Fully Webly Supervised Object Detection},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2020},
}
Requirements:
- NVIDIA GPU, Linux, Python3.6
- Caffe2 in pytorch v1.3.0, various standard Python packages, and the COCO API; Instructions for installing these dependencies are found below
Clone the pytorch repository:
# pytorch=/path/to/clone/pytorch
git clone https://github.com/pytorch/pytorch.git $pytorch
cd $pytorch
git checkout v1.3.0
git submodule update --init --recursive
Install Python dependencies:
pip3 install -r $pytorch/requirements.txt
Build caffe2:
cd $pytorch
sudo USE_OPENCV=On USE_LMDB=On BUILD_BINARY=On python3 setup.py install
Install the COCO API:
pip3 install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
Install the pycococreator:
pip3 install git+git:https://github.com/waspinator/[email protected]
Clone the NA-fWebSOD repository:
# NA-fWebSOD=/path/to/clone/NA-fWebSOD
git clone https://github.com/shenyunhang/NA-fWebSOD.git $NA-fWebSOD
cd $NA-fWebSOD
git submodule update --init --recursive
Install Python dependencies:
pip3 install -r requirements.txt
Set up Python modules:
make
Build the custom C++ operators library:
./build_ops.sh
Download flickr_voc from this here and untar File:
tar xvf flickr_voc.tar
ln -s /path/to/clone/flickr_voc $NA-fWebSOD/detectron/datasets/data/flickr_voc
Download flickr_coco from this here and untar File:
tar xvf flickr_coco.tar
ln -s /path/to/clone/flickr_coco $NA-fWebSOD/detectron/datasets/data/flickr_coco
Download flickr_clean from this here and untar File:
tar xvf flickr_clean.tar
ln -s /path/to/clone/flickr_clean $NA-fWebSOD/detectron/datasets/data/flickr_clean
Please follow this to creating symlinks for PASCAL VOC.
Download MCG proposal from here to detectron/datasets/data, and transform it to pickle serialization format:
cd detectron/datasets/data
tar xvzf MCG-Pascal-Main_trainvaltest_2007-boxes.tgz
cd ../../../
python3 tools/convert_mcg.py voc_2007_train detectron/datasets/data/MCG-Pascal-Main_trainvaltest_2007-boxes detectron/datasets/data/proposals/mcg_voc_2007_train.pkl
python3 tools/convert_mcg.py voc_2007_val detectron/datasets/data/MCG-Pascal-Main_trainvaltest_2007-boxes detectron/datasets/data/proposals/mcg_voc_2007_val.pkl
python3 tools/convert_mcg.py voc_2007_test detectron/datasets/data/MCG-Pascal-Main_trainvaltest_2007-boxes detectron/datasets/data/proposals/mcg_voc_2007_test.pkl
Finnally, We have the following directory structure:
NA-fWebSOD
|_ detectron
|_ datasets
|_ data
|_ flickr_voc
|_ images
|_ images.json
|_ images.txt
|_ ...
|_ flickr_coco
|_ images
|_ images.json
|_ images.txt
|_ ...
|_ flickr_clean
|_ images
|_ images.json
|_ images.txt
|_ ...
|_ VOC2007
|_ coco
|_ ...
Download models from this here and untar File:
tar xvf models.tar
mv models $NA-fWebSOD
Then We have the following directory structure:
NA-fWebSOD
|_ models
| |_ VGG
| |_ |_ VGG_ILSVRC_16_layers_v1.pkl
|_ ...
Flickr voc
./scripts/train_wsl.sh --cfg configs/flickr_voc/webly_wsddn_V-16-C5_1x.yaml OUTPUT_DIR experiments/webly_wsddn_v-16_flickr_voc_`date +'%Y-%m-%d_%H-%M-%S'`
Flickr clean
./scripts/train_wsl.sh --cfg configs/flickr_clean/webly_wsddn_V-16-C5_1x.yaml OUTPUT_DIR experiments/webly_wsddn_v-16_flickr_clean_`date +'%Y-%m-%d_%H-%M-%S'`
Flickr coco
./scripts/train_wsl.sh --cfg configs/flickr_coco/webly_wsddn_V-16-C5_1x.yaml OUTPUT_DIR experiments/webly_wsddn_v-16_flickr_coco_`date +'%Y-%m-%d_%H-%M-%S'`