An easy PyTorch implement of SlowFast-Network "SlowFast Networks for Video Recognition".
We also complete a real-time action detection demo. The demo is orgnized as:
Yolo v3
│
│
deepsort
│
│
SlowFast Network
1.Clone the repository
git clone https://github.com/MagicChuyi/SlowFast-Network-pytorch.git
2.Download Yolo v3 model: https://pan.baidu.com/s/1tT2uzI44KD3zzAgMskU1Aw
3.Download DeepSort re-id model: https://pan.baidu.com/s/1D1_Lw_lq-O75xFX-zFEEbg
4.Download Pre-trained SlowFast Network model: https://pan.baidu.com/s/17GLB2k3VhPgRsVCadVmjaA
5.Modify the model path and your video path in video_demo.py.
6.Run video_demo.py.
1.Download AVA dataset.
2.Discard corrupted data.
3.Dataset should be orgnized as:
ava/ava
│ │ preproc_train
│ │ │ clips
│ │ │ keyframes
│ │ │ ava_train_v2.2.csv
│ │ preproc_val
│ │ clips
│ │ keyframes
│ │ ...
4.Modify the params in config.py and train_config.py.
5.Run train_video.py.
python 3
PyTorch >= 1.0
tensorboardX
OpenCV
[1] https://github.com/Guocode/SlowFast-Networks/
[2] https://github.com/potterhsu/easy-faster-rcnn.pytorch