Human hands detection and segmentation

Project for the course Computer Vision, UniPD 2022.

Usage

Model

Download our custom Dataset (link) and upload it saved as custom_dataset.zip file on your Google Drive, in the main folder MyDrive.
Upload also the custom_data.yaml file in Google Drive as done before. It will be useful for YOLOv5 configuration.
Open the Jupyter Notebook handdetection.ipynb on Google Colaboratory and connect your drive in order to run the code properly.
At the end of the notebook, run the cell to download the model in .onnx format as best.onnx and place it in the directory Model/. It will be used for the C++ code.

References

YOLOv5: object detection architecture and pretrained models use in this project for fine-tuning

Code:

Python Hand Detection/Segmentation: https://github.com/BlueDi/Hand-Detection
Tensorflow: https://medium.com/nerd-for-tech/building-an-object-detector-in-tensorflow-using-bounding-box-regression-2bc13992973f

Paper:

Hand recognition structure: https://www.researchgate.net/publication/282956557_Real_time_finger_tracking_and_contour_detection_for_gesture_recognition_using_OpenCV

Datasets:

Hand Dataset: https://www.robots.ox.ac.uk/~vgg/data/hands/
EgoHands: http://vision.soic.indiana.edu/projects/egohands/
Kaggle Dataset: https://www.kaggle.com/datasets/armannikkhah/hand-dataset
SynthHands Dataset: https://handtracker.mpi-inf.mpg.de/projects/OccludedHands/SynthHands.htm