算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
evaluation-and-visualization【设计与创意】Evaluate rPPG and BigSmall outputs, inspect saved signals and preprocessed arrays, and choose portable motion-analysis visualizations.
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Use this sub-skill after a model or unsupervised method has produced signals. It turns saved predictions into HR/RR metrics, compares traces, inspects cached arrays, or summarizes OpenFace motion. It does not select or run a model, build data caches, or reproduce training.
LABEL_TYPE, test FS, evaluation method, and
window settings. The exact contracts and known implementation edge cases
are in evaluation-api.md.scripts/plot_saved_predictions.py for
a noninteractive PNG/SVG/PDF plot. The pickle must contain predictions,
labels, label_type, and fs; see visualization.md.scripts/plot_preprocessed_arrays.py
for a static frame plus label time/frequency plot. It is the portable
replacement for the interactive notebook; it accepts one input .npy and
its matching label .npy.scripts/convert_frames_to_mp4.py, then
run an already installed OpenFace FeatureExtraction executable outside
this skill. Summarize two OpenFace CSV directories with
scripts/summarize_openface_motion.py.Do not use a notebook, source-checkout import, bundled model, sample output, or vendor/OpenFace code as a runtime dependency. The original motion workflow needs OpenFace installed separately; it is not replaced by the converter.
DiffNormalized labels/predictions set diff_flag=True: cumulatively sum
before detrending. Raw and Standardized set it to False.FS, commonly 30) rather than assuming it.FFT or peak detection (spelling is case-sensitive
in the repository config). FFT searches the configured band; peak detection
uses peak spacing. A window shorter than 9 samples is ignored.MAE, RMSE, MAPE, Pearson, SNR, MACC, and/or BA as
appropriate. Do not report undefined values from empty, constant, or
too-short arrays as successful evaluation; follow the failure guidance in
troubleshooting.md.Test output pickles are normally under the configured log path at the test
experiment's saved_test_outputs directory. Bland--Altman files are normally
under the log path, experiment name, and bland_altman_plots. Exact filenames,
including FFT/Peak variants, are listed in evaluation-api.md.
Static helper outputs go only where --output names them; existing files are
never overwritten unless --force is explicitly supplied.
python scripts/plot_saved_predictions.py --help
python scripts/plot_saved_predictions.py --input outputs.pickle --output signal.png --trial 0 --chunk-size 180 --chunk 0
python scripts/plot_preprocessed_arrays.py --input 000_input0.npy --label 000_label0.npy --output cache.png
python scripts/convert_frames_to_mp4.py --help
python scripts/convert_frames_to_mp4.py --mode ubfc-rppg --input-dir <dataset-root>/UBFC --output-dir <scratch-dir>/ubfc-mp4
python scripts/summarize_openface_motion.py --input-dir <scratch-dir>/openface-a --compare-dir <scratch-dir>/openface-b --output motion.png
All commands are local-only and noninteractive. Read the linked references before changing bands, label transforms, AU definitions, or output paths.