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still-image-demo

Run 3DDFA_V2 still-image alignment, rendering, pose, texture, and mesh export workflows.

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VectorSpaceLab/AREX-Skill
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26 de agosto de 2026 às 16:31
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SKILL.md
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name
still-image-demo
description
Run 3DDFA_V2 still-image alignment, rendering, pose, texture, and mesh export workflows.
metadata
{"disco-role":"operating"}
disable-model-invocation
true
license
MIT
# Still-image demo Use this sub-skill for `demo.py` workflows on a single image: sparse or dense landmarks, 3D renderings, depth, PNCC, UV texture, pose boxes, and PLY/OBJ mesh exports. ## When to read Read this sub-skill when the task asks to: - Run 3DDFA_V2 on a still image. - Generate `2d_sparse`, `2d_dense`, `3d`, `depth`, `pncc`, `uv_tex`, `pose`, `ply`, or `obj` outputs. - Use `--onnx` for a single-image demo. - Diagnose `No face detected`, missing result files, headless plotting, or mode-specific failures. ## Before running 1. Use `../setup-and-assets/` if native extensions or checkpoints are not known to be ready. 2. Check `../../references/model-assets.md` when switching configs or missing weight files. 3. In headless environments, keep `--show_flag false`; the bundled wrapper also sets a headless plotting backend. ## Main wrapper The bundled wrapper preserves the original `demo.py` CLI. Put original demo arguments after `--`: ```bash python <skill-root>/sub-skills/still-image-demo/scripts/run-still-image.py \ --repo-root <checkout> -- \ -f <image-path> -o 3d --show_flag false --onnx ``` Use direct repo commands only when you already applied the same compatibility and headless setup the wrapper provides. ## Output selection Read `references/workflows.md` for the full output-mode table. The highest-use choices are: - `2d_sparse` for 68-point landmark overlays. - `2d_dense` for dense landmark visualization. - `3d` for rendered dense mesh overlay. - `depth`, `pncc`, and `uv_tex` for specialized per-pixel visual products. - `pose` for yaw/pitch/roll pose-box visualization. - `ply` and `obj` for mesh serialization. Outputs default to `examples/results/` and use the input basename plus the selected option. ## Decision points - Prefer `--onnx` for CPU latency and when the `.onnx` assets are already present or can be auto-converted. - Use `configs/mb05_120x120.yml` when the task values speed over the default backbone. - Use dense reconstruction for `3d`, `depth`, `pncc`, `uv_tex`, `ply`, and `obj`; sparse mode is enough for `2d_sparse` and `pose`. - If the user needs multi-frame tracking, route to `../video-and-tracking/`. - If the user asks about latency numbers rather than a saved image, route to `../onnx-and-benchmarking/`. ## Troubleshooting Read `references/troubleshooting.md` for still-image-specific failures and `../../references/troubleshooting.md` for shared build/import failures.
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