facesaver

A tool to process video files into still for image and video AI training, using yolov11 face detection to find scenes with people in them, within a certain size and position range.

Requirements:

CUDA 12.x A GPU with 6GB or more VRAM Raw video rips, unless you want subtitles in your training data.

Usage:

1. create a conda env

conda env create -n facesaver python=3.12

2. activate the env

conda activate facesaver

3. install the requiremnts

pip3 install -r requirements.txt

4. put your video files into the input directory

5. run the command

python3 main.py -I ./input -O ./output -w 200 -m 200

notes:

You can use -w and -m to specify the minimum bounding box for face detection, to avoid triggering on background faces If you find you're getting too many false positives or not enough faces, adjust the code here:

        # Perform face detection if no face has been detected in this scene
        if not face_detected_in_scene:
            try:
                results = model.predict(frame, classes=[0], conf=0.75, device=device)

by changing conf to somethihng bigger or smaller

You will have to do some cleanup to remove the occasional non-face and faces in credit scenes. If you process something like as 12-episode anime, you should end up with 250-1000 usable stills after manual cleanup.