Ready-to-use Google Colab file: https://colab.research.google.com/drive/1QWI94mivkWGZLvrB4cUoaw3dH6Cf45mw?usp=sharing

Yolov7-cigarette-censor-and-smokers-face-recorder

• Censoring and counting all cigarettes on the screen and saving smoker's faces in the folder or any database
• Useful for public non-smoking areas
• Code can run on Both (CPU & GPU)
• Video/WebCam/External Camera/IP Stream Supported

yolo_cigarette.mp4

It is super easy to run

• We are going to copy my repo and just download "traced_model.pt" which is already given by me in the code, and we are good to go!

Steps to run Code

• clone the repository:
• git clone https://github.com/muratali016/Yolov7-cigarette-censor-and-smokers-face-recorder.git
• Download traced_model.pt by link:https://drive.google.com/file/d/1ovsR0biNCnOZ9174bSkNS-5IMtYGa52b/view?usp=sharing and move this model to your directory

Upgrade pip with the mentioned command below.

pip install --upgrade pip

Install requirements with the mentioned command below.

pip install -r requirements.txt

Using counter

• %cd /content/Yolov7-cigarette-censor-and-smokers-face-recorder
• %!python detect.py --weights best_cigarette.pt --conf 0.1 --source /content/Yolov7-cigarette-censor-and-smokers-face-recorder/example_img.jpg --cigarette_blurrate 50 --shape_detector /content/Yolov7-cigarette-censor-and-smokers-face-recorder/shape_predictor_68_face_landmarks.dat

Results!

Inference on a video:

https://www.youtube.com/watch?v=ld9nP8-ZsQw

References

• https://github.com/WongKinYiu/yolov7