-
ObjectDection Human Bbox Detection
- YoloV3
- RFCN
- CornerNet
-
2D pose estimation (kps2d__detection)
- Simple BaseLine
- High Resolution Network (hr_net)
- Open Pose
-
3D pose estimation (kps3d_detection)
- VideoPose3D
-
Object Tracking
- lighttrack
- pose flow
-
ActionRecgnition
- ST-GCN
- 2S-AGCN
Install pytorch >= v1.0.0 pip install -r requirment.txt
cd kps2d_detection/hr_net/lib/ make
cd pose_track/lighttrack/graph/torchlight python setup.py install
vim ~/.bashrc
export PATH=/path/to/cvToolBox:$PATH
export PYTHONPATH=/path/to/cvToolBox:$PYTHONPATH
```
from object_detection.yolo_v3.human_detector import load_model
from object_detection.yolo_v3.human_detector import inference
import cv2
im = cv2.imread('data/test.png')
model = load_model()
# return bbox and its probability
inference(im, model)
```
cd pose_track/lighttrack/
- python demo.py -p 0 (pose estimator is simple-baseline, pose speed 90 person/s)
- python demo.py -p 1 (pose estimator is hrnet, pose speed 25 person/s)