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video-and-tracking

Run 3DDFA_V2 video, smoothing, and manual webcam tracking workflows.

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VectorSpaceLab/AREX-Skill
Última actividad en el origen
26 de agosto de 2026 a las 16:31
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SKILL.md
Instrucciones de origen · Vista previa de solo lectura
name
video-and-tracking
description
Run 3DDFA_V2 video, smoothing, and manual webcam tracking workflows.
metadata
{"disco-role":"operating"}
disable-model-invocation
true
license
MIT
# Video and tracking Use this sub-skill for 3DDFA_V2 video-file processing and smoothing. Webcam support exists in the source repo but remains a manual, hardware-dependent workflow. ## When to read Read this sub-skill when the task asks to: - Run `demo_video.py` or `demo_video_smooth.py` on an AVI/MP4 file. - Produce tracked `2d_sparse`, `2d_dense`, or `3d` video outputs. - Tune `n_pre`, `n_next`, `start`, or `end` frame-window settings. - Diagnose `imageio`, `ffmpeg`, tracking drift, or webcam/display issues. ## Before running 1. Build and smoke-test the checkout with `../setup-and-assets/`. 2. Confirm `imageio` and `imageio-ffmpeg` are installed. 3. Start with the sample clip if the user's input format is uncertain. ## Basic video wrapper The basic wrapper preserves the original `demo_video.py` CLI. Put original arguments after `--`: ```bash python <skill-root>/sub-skills/video-and-tracking/scripts/run-video.py \ --repo-root <checkout> -- \ -f <video-path> -o 3d --onnx ``` ## Smoothed video wrapper The smoothed wrapper preserves the original `demo_video_smooth.py` CLI: ```bash python <skill-root>/sub-skills/video-and-tracking/scripts/run-video-smooth.py \ --repo-root <checkout> -- \ -f <video-path> -o 2d_sparse -n_pre 1 -n_next 1 --onnx ``` ## Tracking behavior - The first frame uses detection; later frames track from the previous landmark state. - If the ROI area becomes too small, the demo re-runs face detection. - Motion that is too fast or head pose beyond roughly 90 degrees can make the lightweight tracker fail. - Smoothing uses a simple average over `n_pre + n_next + 1` frames and drops or pads boundary frames. ## Webcam boundary The repo has a webcam script that uses `imageio.get_reader("<video0>")` and `cv2.imshow`. This skill documents the workflow in `references/workflows.md`, but does not provide an automated webcam wrapper because it needs live camera hardware, GUI display access, and manual quit handling. ## Troubleshooting Read `references/troubleshooting.md` for video-specific failure recovery and `../../references/troubleshooting.md` for shared build/import failures.
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