Merge branch 'main' of https://github.com/LiiNen/CV_skeleton_provider

README.md

@@ -1,2 +1,57 @@
 # CV_skeleton_provider
 ## OpenCV Project
+CV_skeleton_provider project made for detecting a skeleton structure easily. <br>
+This project contains how to use pretrained models and analize video with frames, using openCV. <br>
+For solving some discomports, we make it from the beginning and providing argparse to use it easily. <br>
+Also providing img preprocessing methods, you can use it with simple options when you use specific imgs <br>
+
+## How to use
+! prototxt file & caffemodel file are not included in both pypi package & project <br>
+! you should download these pre-trained models in website, and you can easily find it <br>
+### using pip package (recommended)
+1. install pypi package
+```bash
+$ pip install CV_skeleton_provider
+```
+2. python code
+```python
+from CV_skeleton_provider.SkeletonProvider import defaultDict, skprovider
+skprovider(defaultDict()) # show skeleton image over default img
+```
+3. custom parameter (when customizing)
+```python
+input_dict = defaultDict()
+input_dict['source']       =  './example.jpeg'   # input filepath. img(jpg, jpeg, png) or video(mp4, avi, mkv) supported
+input_dict['output']       =  './output'         # output filepath(exclude format). file format will be set by automatically.
+input_dict['option']       =  'skl'              # s for skeleton, k for keypoints, l for label. if string include these char, show it
+input_dict['exclude']      =  []                 # 0~17 interger list. that point will not be shown on result.
+input_dict['thres']        =  0.1                # threshold (float)
+input_dict['gray']         =  False              # using grayscale (bool)
+input_dict['back']         =  False              # remove background (bool)
+input_dict['selectRect']   =  False              # when removing background, you can set the object(human) size by drag img (bool)
+input_dict['autolocation'] =  False              # when removing background, code will automatically 'detect' human (bool)
+input_dict['comp']         =  1                  # for only video. video frame will be reduced to 1/comp (int)
+input_dict['gamma']        =  -1                 # img preprocessing gamma value. under 0 means not processing gamma (float)
+input_dict['b_propo']      =  False              # check black proportion and preprocessing reducing black part (bool)
+input_dict['proto']        =  './pose/coco/pose_deploy_linevec.prototxt'    # prototxt filepath
+input_dict['weight']       =  './pose/coco/pose_iter_440000.caffemodel'     # caffemodel filepath
+skprovider(input_dict)
+```
+
+### using clone project
+```bash
+$ git clone https://github.com/LiiNen/CV_skeleton_provider.git
+$ pip install -r ./CV_skeleton_provider/requirements.txt
+$ cd ./CV_skeleton_provider/CV_skeleton_provider
+$ python ./SkeletonProvider.py # show skeleton image over default img
+```
+you can use argparse with SkeletonProvider.py to change parameter <br>
+check it with following command in CLI
+```bash
+$ python SkeletonProvider.py --help
+```
+! as mentioned, prototxt & caffemodel must be existed. followings are default path <br>
+```
+./CV_skeleton_provider/CV_skeleton_provider/pose/coco/pose_deploy_linevec.prototxt
+./CV_skeleton_provider/CV_skeleton_provider/pose/coco/pose_iter_440000.caffemodel
+```