MatAnyone's standard workflow includes the following key steps:
- material preparation: Place the video to be processed (e.g. input_video.mp4) into the
data/Folder, format support MP4/AVI - First frame mask creation: Create the first frame PNG format split image with tools such as Photoshop, with white as the target area, and save it as
mask_frame1.png - Execute the keying command::
python inference.py --video data/input_video.mp4 --mask data/masks/mask_frame1.png --output output/ - Results View: the output folder will contain video sequences or composite videos with transparent backgrounds
Advanced Function Operation:
- Resolution Adjustment: Add
--resolution 1080Parameters enhance edge quality - Memory Fusion Optimization: Modification
config.yamlhit the nail on the headmemory_fusion_rateParameters to cope with sudden light changes - Batch support: Automated multi-video processing can be achieved by writing shell scripts
Note: The precision of the first frame mask directly affects the final effect, and it is recommended to pay special attention to the drawing precision of the target edge area.
This answer comes from the articleMatAnyone: Extract video to specify the target portrait of the open-source tool to generate the target portrait videoThe
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