APNet for Person Search
This is the code of Robust Partial Matching for Person Search in the Wild accepted in CVPR2020. The Align-to-Part Network(APNet) is proposed to alleviate the misalignment problem occurred in pedestrian detector, facilitating the downstream re-identification task. The code is based on maskrcnn-benchmark.
- Please follow the offical installation INSTALL.md. This code does not support the mixed precision training, so feel free to skip the installation of
NOTE: If you meet some problems during the installation, you may find a solution in issues of official maskrcnn-benchmark.
git clone https://github.com/zhongyingji/APNet.git cd APNet rm -rf build/ python setup.py build develop
Make sure you have downloaded the dataset of person search like PRW-v16.04.20.
- Since the training of APNet relies on the keypoint annotation, we provide the keypoint estimation file by AlphaPose in
keypoint_pred/. Copy all the files into the root dir of dataset, like
cp keypoint_pred/* /path_to_prw_dataset/PRW-v16.04.20/
- Symlink the path to the dataset to
ln -s /path_to_prw_dataset/PRW-v16.04.20/ maskrcnn_benchmark/datasets/PRW-v16.04.20
APNet composes of three modules, OIM, RSFE and BBA. To train the entire network, you can simply run:
which contains the training scripts of the three modules.
NOTE: Both RSFE and BBA are required to be intialised with the trained OIM. For more details, please check
You can alter the scripts in
train.sh in the following aspects:
We train OIM on 2 GPUS with batchsize 4. If you encounter out-of-memory (OOM) error, reduce the batchsize by setting
SOLVER.IMS_PER_BATCHto a smaller number.
If you want to use 1 GPU, replace the command of OIM with single GPU training script:
python tools/train_net.py --config-file "configs/reid/prw_R_50_C4.yaml" SOLVER.IMS_PER_BATCH 2 TEST.IMS_PER_BATCH 8 OUTPUT_DIR "models/prw_oim"
After each of the module has been trained, you can run exactly the same training script of that module to test the performance.
If you find this work or code is helpful in your research, please consider citing: