MatAnyone2/USAGE.md

MatAnyone2 Usage

Environment

Activate the CUDA env:

conda activate matanyone2-cu132

If the matanyone2 command is not on your PATH, run it through the env Python:

/home/zero/.conda/envs/matanyone2-cu132/bin/python -m matanyone2.cli --help

Input Format

MatAnyone2 takes:

1. A video file such as .mp4, .mov, or .avi, or a folder of extracted frames
2. A first-frame segmentation mask image

The mask should match the first frame of the input.

Basic Commands

Process a folder of frames:

matanyone2 -i inputs/video/test-sample1 -m inputs/mask/test-sample1.png

Process a video file:

matanyone2 -i inputs/video/test-sample2.mp4 -m inputs/mask/test-sample2.png

Use the Python entrypoint directly:

python inference_matanyone2.py -i inputs/video/test-sample2.mp4 -m inputs/mask/test-sample2.png

Output

The default output directory is results/.

You will get:

• *_fgr.mp4 for the foreground composite
• *_pha.mp4 for the alpha matte video

If --save-image is enabled, per-frame PNGs are also written under:

results/<video_name>/fgr/
results/<video_name>/pha/

Common Settings

matanyone2 \
  -i inputs/video/test-sample2.mp4 \
  -m inputs/mask/test-sample2.png \
  -o results/ \
  -c pretrained_models/matanyone2.pth \
  -w 10 \
  -e 10 \
  -d 10 \
  --max-size 1080 \
  --save-image

Flags:

• -o, --output-path: where results are written
• -c, --ckpt-path: model checkpoint path
• -w, --warmup: number of warmup frames before saving output
• -e, --erode-kernel: erosion kernel size for the mask
• -d, --dilate-kernel: dilation kernel size for the mask
• --suffix: appended to the output name
• --save-image: also save per-frame PNGs
• --max-size: downsample when the smaller side exceeds this value

Practical Notes

• The repo will auto-download the checkpoint the first time it runs if pretrained_models/matanyone2.pth is missing.
• This is not a single-image matting tool. A still image needs to be treated as a one-frame video/folder input.
• For your GPU, use the matanyone2-cu132 environment.

Local Demo

To launch the Gradio app:

cd hugging_face
python app.py

If you are missing demo dependencies, install them with:

conda activate matanyone2-cu132
python -m pip install -r hugging_face/requirements.txt