ProPedestrian

Privacy protection based on specific pedestrians

This project can identify specific pedestrians in images or videos, remove them from the images, and restore them. Thus achieving anonymity of specific pedestrians

Download pre-trained model

1. yolov7:
   • The purpose of using YOLOv7 is to detect pedestrians in complex scenes within images or videos
   • Implementation of paper：[2207.02696] YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
   • Download pre-trained model：https://github.com/WongKinYiu/yolov7
   • Place it in the yolov7/weights folder
2. lama
   • The purpose of using lama is to erase pedestrians from images or videos and then restore the images or videos
   • Implementation of paper：[2109.07161] Resolution-robust Large Mask Inpainting with Fourier Convolutions
   • Download pre-trained model: https://github.com/advimman/lama
   • Place it in the lama/big-lama folder
3. HiNet
   • The purpose of using HiNet is to conceal detected individuals in images, allowing for the removal of individuals while still enabling restoration
   • Implementation of paper：ICCV 2021 Open Access Repository
   • Download pre-trained model: https://github.com/TomTomTommi/HiNet
   • Place it in the HiNet/model folder
4. Fast-reid
   • The purpose of using Fast-reid is to match detected individuals with specific individuals that need protection, in order to identify those requiring protection in images or videos
   • Implementation of paper：[2006.02631] FastReID: A Pytorch Toolbox for General Instance Re-identification
   • Download pre-trained model: https://github.com/JDAI-CV/fast-reid/blob/master/MODEL_ZOO.md
   • Place it in the yolov7/fast_reid_master/model folder

test

Profile Path

In the files yolo_fastreid_lama.py、 anony_recory.py and yolov7/yolo_fastreid.py, the.../ replace with one's own actual work path

Encryption process

1. Put the pedestrian images to be protected into /yolov7/fast-reid_master/datasets/query
2. You can place the image in example/input image and modify the corresponding path in yolo_fastreid_lama.py. Then run yolo_fastreid_lama.py

python yolo_fastreid_lama.py

Encryption_process.mp4

Decryption process

python anony_recory.py

Decryption_process.mp4