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This is a project about refining a shaky walking-person video using a Python/OpenCV pipeline into six outputs: a stabilized clip; full-color extracted and binary-mask videos; an alpha-matte composite; a matted result; and a bounding-box–tracked final video—all via a single command.

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video-processing-pipeline

This repository implements a full video-processing pipeline that takes a shaky input clip of a walking person and produces a set of polished outputs through four key stages: 1. Video stabilization — smooths out camera shake to generate a stabilized AVI. 2. Background subtraction & mask extraction — isolates the subject into both a full-color “extracted” video and a binary mask (0 = background, 1 = foreground). 3. Image matting & alpha generation — composites the isolated person onto a new static background and produces an alpha-channel video for soft edges. 4. Object tracking — locates and tracks the subject frame-by-frame, drawing a bounding box in the final output video.

All steps run from a single Python entry point (main.py) and rely on OpenCV-based algorithms. The script outputs six processed videos (stabilized.avi, extracted.avi, binary.avi, alpha.avi, matted.avi, output.avi) plus two JSON files capturing per-video timing and per-frame tracking data .

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This is a project about refining a shaky walking-person video using a Python/OpenCV pipeline into six outputs: a stabilized clip; full-color extracted and binary-mask videos; an alpha-matte composite; a matted result; and a bounding-box–tracked final video—all via a single command.

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