Added possibility to use it as a module in other projects

src/body.py → build/lib/openpose/body.py

@@ -8,8 +8,8 @@
 import torch
 from torchvision import transforms
 
-from src import util
-from src.model import bodypose_model
+from openpose import util
+from openpose.model import bodypose_model
 
 class Body(object):
     def __init__(self, model_path):

src/hand.py → build/lib/openpose/hand.py

@@ -9,8 +9,8 @@
 import torch
 from skimage.measure import label
 
-from src.model import handpose_model
-from src import util
+from openpose.model import handpose_model
+from openpose import util
 
 class Hand(object):
     def __init__(self, model_path):

src/hand_model_outputsize.py → build/lib/openpose/hand_model_outputsize.py

@@ -2,7 +2,7 @@
 from tqdm import tqdm
 import json
 
-from src.model import handpose_model
+from openpose.model import handpose_model
 
 model = handpose_model()
 

demo.py

@@ -3,10 +3,10 @@
 import copy
 import numpy as np
 
-from src import model
-from src import util
-from src.body import Body
-from src.hand import Hand
+from openpose import model
+from openpose import util
+from openpose.body import Body
+from openpose.hand import Hand
 
 body_estimation = Body('model/body_pose_model.pth')
 hand_estimation = Hand('model/hand_pose_model.pth')

demo_camera.py

@@ -4,10 +4,10 @@
 import numpy as np
 import torch
 
-from src import model
-from src import util
-from src.body import Body
-from src.hand import Hand
+from openpose import model
+from openpose import util
+from openpose.body import Body
+from openpose.hand import Hand
 
 body_estimation = Body('model/body_pose_model.pth')
 hand_estimation = Hand('model/hand_pose_model.pth')

pyproject.toml

@@ -0,0 +1,11 @@
+[build-system]
+requires = ["setuptools>=61.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "openpose" 
+readme = "README.md"
+version = "0.1.0"
+
+[tool.setuptools.dynamic]
+dependencies = {file = ["requirements.txt"]}

src/openpose.egg-info/PKG-INFO

@@ -0,0 +1,124 @@
+Metadata-Version: 2.1
+Name: openpose
+Version: 0.1.0
+Description-Content-Type: text/markdown
+
+## pytorch-openpose
+
+pytorch implementation of [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) including **Body and Hand Pose Estimation**, and the pytorch model is directly converted from [openpose](https://github.com/CMU-Perceptual-Computing-Lab/openpose) caffemodel by [caffemodel2pytorch](https://github.com/vadimkantorov/caffemodel2pytorch). You could implement face keypoint detection in the same way if you are interested in. Pay attention to that the face keypoint detector was trained using the procedure described in [Simon et al. 2017] for hands.
+
+openpose detects hand by the result of body pose estimation, please refer to the code of [handDetector.cpp](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/hand/handDetector.cpp).
+In the paper, it states as:
+```
+This is an important detail: to use the keypoint detector in any practical situation, 
+we need a way to generate this bounding box. 
+We directly use the body pose estimation models from [29] and [4], 
+and use the wrist and elbow position to approximate the hand location, 
+assuming the hand extends 0.15 times the length of the forearm in the same direction.
+```
+
+If anybody wants a pure python wrapper, please refer to my [pytorch implementation](https://github.com/Hzzone/pytorch-openpose) of openpose, maybe it helps you to implement a standalone hand keypoint detector.
+
+Don't be mean to star this repo if it helps your research.
+
+### Getting Started
+
+#### Install Requriements
+
+Create a python 3.7 environement, eg:
+
+    conda create -n pytorch-openpose python=3.7
+    conda activate pytorch-openpose
+
+Install pytorch by following the quick start guide here (use pip) https://download.pytorch.org/whl/torch_stable.html
+
+Install other requirements with pip
+
+    pip install -r requirements.txt
+
+#### Download the Models
+
+* [dropbox](https://www.dropbox.com/sh/7xbup2qsn7vvjxo/AABWFksdlgOMXR_r5v3RwKRYa?dl=0)
+* [baiduyun](https://pan.baidu.com/s/1IlkvuSi0ocNckwbnUe7j-g)
+* [google drive](https://drive.google.com/drive/folders/1JsvI4M4ZTg98fmnCZLFM-3TeovnCRElG?usp=sharing)
+
+`*.pth` files are pytorch model, you could also download caffemodel file if you want to use caffe as backend.
+
+Download the pytorch models and put them in a directory named `model` in the project root directory
+
+#### Run the Demo
+
+Run:
+
+    python demo_camera.py
+
+to run a demo with a feed from your webcam or run
+
+    python demo.py
+
+to use a image from the images folder or run 
+
+    python demo_video.py <video-file>
+
+to process a video file (requires [ffmpeg-python][ffmpeg]).
+
+[ffmpeg]: https://pypi.org/project/ffmpeg-python/
+
+### Todo list
+- [x] convert caffemodel to pytorch.
+- [x] Body Pose Estimation.
+- [x] Hand Pose Estimation.
+- [ ] Performance test.
+- [ ] Speed up.
+
+### Demo
+#### Skeleton
+
+![](images/skeleton.jpg)
+#### Body Pose Estimation
+
+![](images/body_preview.jpg)
+
+#### Hand Pose Estimation
+![](images/hand_preview.png)
+
+#### Body + Hand
+![](images/demo_preview.png)
+
+#### Video Body
+
+![](images/kc-e129SBb4-sample.processed.gif)
+
+Attribution: [this video](https://www.youtube.com/watch?v=kc-e129SBb4).
+
+#### Video Hand
+
+![](images/yOAmYSW3WyU-sample.small.processed.gif)
+
+Attribution: [this video](https://www.youtube.com/watch?v=yOAmYSW3WyU).
+
+### Citation
+Please cite these papers in your publications if it helps your research (the face keypoint detector was trained using the procedure described in [Simon et al. 2017] for hands):
+
+```
+@inproceedings{cao2017realtime,
+  author = {Zhe Cao and Tomas Simon and Shih-En Wei and Yaser Sheikh},
+  booktitle = {CVPR},
+  title = {Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields},
+  year = {2017}
+}
+
+@inproceedings{simon2017hand,
+  author = {Tomas Simon and Hanbyul Joo and Iain Matthews and Yaser Sheikh},
+  booktitle = {CVPR},
+  title = {Hand Keypoint Detection in Single Images using Multiview Bootstrapping},
+  year = {2017}
+}
+
+@inproceedings{wei2016cpm,
+  author = {Shih-En Wei and Varun Ramakrishna and Takeo Kanade and Yaser Sheikh},
+  booktitle = {CVPR},
+  title = {Convolutional pose machines},
+  year = {2016}
+}
+```

src/openpose.egg-info/SOURCES.txt

@@ -0,0 +1,12 @@
+README.md
+pyproject.toml
+src/openpose/__init__.py
+src/openpose/body.py
+src/openpose/hand.py
+src/openpose/hand_model_outputsize.py
+src/openpose/model.py
+src/openpose/util.py
+src/openpose.egg-info/PKG-INFO
+src/openpose.egg-info/SOURCES.txt
+src/openpose.egg-info/dependency_links.txt
+src/openpose.egg-info/top_level.txt

src/openpose.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

src/openpose.egg-info/top_level.txt

@@ -0,0 +1 @@
+openpose