This tool combines two algorithms to accurately detect people who are violating the social distancing protocol:

• Facebook/Detectron2 (Faster RCNN implementation)https://github.com/facebookresearch/detectron2
• "Digging into Self-Supervised Monocular Depth Prediction" https://github.com/nianticlabs/monodepth2

Starter code taken from an excellent tutorial from Aravind Pai: https://www.analyticsvidhya.com/blog/2020/05/social-distancing-detection-tool-deep-learning/

Use:

Social-Distance-Tool-with-Depth.ipynb

Libraries needed:

• Detectron2 = 0.13
• OpenCV >= 3
• Matplotlib
• tqdm
• pytorch = 1.4
• torchvision = 0.4

Input:

• A video sequence

Output:

• bounding boxes on all persons detected in the video
• highlighing people who are in close proximity
• depth map for accurate calculations

This code is for non-commercial use.

This work is licensed under a Creative Commons Attribution 4.0 International License.