name: postprocessing-3d-video-exports
description: "Route DeepLabCut post-processing, video utilities, 3D
calibration/triangulation, and model export requests."
disable-model-invocation: true
metadata:
disco-role: operating
license: LGPL 3.0
Post-processing, 3D, and export router
Use this sub-skill when the request starts from analyzed pose outputs, refined labels, rendered videos, 3D stereo data, or exportable model weights.
Handle here
- Smooth or inspect analyzed predictions with
filterpredictions
- Detect outliers and expand labels with
extract_outlier_frames or find_outliers_in_raw_data
- Merge corrected labels with
merge_datasets
- Render labels, trajectory plots, and skeleton measurements
- Check, crop, downsample, or shorten videos before visualization
- Calibrate stereo cameras, verify undistortion, triangulate, and render 3D videos
- Export portable PyTorch weights with
export_model
Route elsewhere first when
- You still need first-pass training, evaluation, or raw video analysis ->
../pytorch-training-evaluation-inference/SKILL.md
- You need detections-to-tracklets, stitching, or re-identification ->
../multi-animal-tracking/SKILL.md
- You need SuperAnimal or pretrained-model inference/adaptation ->
../model-zoo-superanimal/SKILL.md
- You need project setup, frame labeling, or training-dataset creation ->
../install-and-project-setup/SKILL.md or ../data-labeling-and-training-datasets/SKILL.md
Default decision order
- Confirm the analysis folder, shuffle, trainingsetindex, and track method that produced the outputs.
- Decide whether the task is 2D cleanup, refinement, video prep, 3D, or export.
- Use the smallest API that touches only the needed files.
- Keep
destfolder and filename pairing consistent across filter, label, plot, and triangulation steps.
Common outputs
- Analyzed predictions:
.h5 and optional .csv
- Filtered predictions:
*_filtered.h5 and optional *_filtered.csv
- Refined frames: corrected labels plus
MachineLabelsRefine.h5 during refinement
- Labeled videos and trajectory plots
- Skeleton summaries:
*_skeleton.h5 and optional .csv
- 3D triangulation outputs and metadata
- Exported model bundles under
exported-models-pytorch/
Bundled helper
scripts/collect_video_inventory.py prints a JSON inventory of candidate video files, extensions, and exclusion results without modifying anything.
Details
- API-level notes live in
references/api-reference.md
- Workflow ordering and filename expectations live in
references/workflows.md
- Failure modes and recovery cues live in
references/troubleshooting.md