Note that our testing code is based on detection results from original tf-cpn (In COCO validation, detector AP is 41.1 whose human AP is 55.3).
| Method | Base Model | Input Size | AP @0.5:0.95 | AP @0.5 | AP @0.75 | AP medium | AP large |
|---|---|---|---|---|---|---|---|
| CPN | ResNet-50 | 384x288 | 71.1 | 88.9 | 77.7 | 67.2 | 78.0 |
You can download our model here: https://github.com/Longqi-S/keras_cpn/releases/download/v0.1/cpn_resnet50_cpn_0065.h5
-
Download MSCOCO images from http://cocodataset.org/#download. We train in COCO trainvalminusminival dataset and validate in minival dataset. Then put the data and evaluation PythonAPI in $CPN_ROOT/data/COCO/MSCOCO.
We use the human detection results same with tf-cpn, you can download it here: https://github.com/Longqi-S/keras_cpn/releases/download/v0.1/person_detection_minival411_human553.json.coco
After preparation, file stucture should be like below:
data/
|->COCO/
| |->dets/
| | |->person_detection_minival411_human553.json.coco
| |->MSCOCO/
| | |->PythonAPI/
| | |->train2014/
| | |->val2014/
| | |->person_keypoints_minival2014.json
| | |->person_keypoints_trainvalminusminival2014.json
- Download the base model (ResNet) weights from [keras model_zoo]
cd $CPN_ROOT/data
sh get_pretrain_model.sh
- Setup your environment by first running
pip3 install -r requirement.txt
To train a CPN model, use train.py in root folder.
python3 train.py --model data/pretrain/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5 --cfg configs/e2e_CPN_ResNet50_FPN_cfg.py
After the training finished, output is written underneath $CPN_ROOT/logs/ which looks like below
logs/
|->resnet50_cpn20180819T1607/
| |->events.out.tfevents.1534666165.9507
| |->cpn_resnet50_cpn_0001.h5
| |->cpn_resnet50_cpn_0002.h5
| |->...
Run the testing code in the postprocessing folder.
cd postprocessing
python3 mptest.py -d 0 -m cpn_resnet50_cpn_0002.h5 -c ../configs/e2e_CPN_ResNet50_FPN_cfg.py
We can only use just one GPU to test.
python3 draw_net.py --mode 0 --cfg configs/e2e_CPN_ResNet50_FPN_cfg.py
mode: 0 means train; 1 means inference; cfg : choose which network to draw;
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent