Regen previews at 256-color palette; 3-cam dataloader gif; add docs/curation_pipeline.md

docs/curation_pipeline.md

@@ -0,0 +1,365 @@
+# React data curation pipeline
+
+The procedure below is what runs between a fresh recording session and a HF
+push. Follow it in order; each stage produces a checkable artifact, so a bad
+stage doesn't silently propagate downstream.
+
+Source files referenced. The first four live in the recording-machine
+`MultimodalData/twm/` checkout. The last three are the curation scripts
+produced for this dataset; they currently live in `/tmp/` (development
+scratchpad) and should be moved into `MultimodalData/twm/twm/scripts/` so
+they're versioned alongside the rest of the codebase.
+
+| Script | Current location | Future home |
+|---|---|---|
+| `data_collection.py` | `MultimodalData/twm/` | (already in repo) |
+| `compress_h5.py` | `MultimodalData/twm/` | (already in repo) |
+| `visualize.py` | `MultimodalData/twm/` | (already in repo; projection overlay on by default, `--no_projection` to disable) |
+| `twm.contact_index` | `MultimodalData/twm/twm/` | (already in repo) |
+| `make_episode_gifs_v3.py` | `/tmp/` | `MultimodalData/twm/twm/scripts/` |
+| `freeze_cut_report.py` | `/tmp/` | `MultimodalData/twm/twm/scripts/` |
+| `inspect_short_freezes.py` | `/tmp/` | `MultimodalData/twm/twm/scripts/` |
+
+The pipeline assumes the standard layout:
+
+```
+/media/yxma/Disk1/twm/
+├── data/<task>/<date>/episode_*.h5             # raw H5 (BLOSC)
+├── processed/<mode>/<task>/<date>/episode_*.pt # contact-indexed .pt
+└── figures/
+    ├── dataset_figures/                        # summary plots + JSONs
+    └── episode_previews/<task>/<date>/         # one GIF per episode
+```
+
+`<date>` is `YYYY-MM-DD`; `<task>` is e.g. `motherboard`.
+
+---
+
+## Stage 0 — Recording
+
+Use `data_collection.py`. Confirm before you stop the run:
+- All three RealSense cams are streaming (preview window shows three rows).
+- Both GelSight feeds are alive.
+- All three OptiTrack rigid bodies (left, right, work-piece) are tracked
+  for the whole take. If a body's pose stops updating mid-run, the
+  recorder will silently hold the last sample → this is the failure mode
+  detected in Stage 5C. Re-aim the cameras or re-seat the markers before
+  starting a long take.
+- Audible buffer-drop warnings are zero in the last 30 s of the session.
+
+Output: `data/<task>/<date>/episode_*.h5` (BLOSC-compressed).
+
+---
+
+## Stage 1 — Integrity check
+
+For every new H5, confirm it opens and that frame counts agree across
+modalities. The fast version:
+
+```bash
+python - <<'PY'
+import h5py, hdf5plugin, sys
+from pathlib import Path
+ROOT = Path("/media/yxma/Disk1/twm/data/motherboard/<date>")
+for p in sorted(ROOT.glob("episode_*.h5")):
+    try:
+        f = h5py.File(p, "r")
+        T = f["realsense/cam0/color"].shape[0]
+        for k in ("realsense/cam1/color", "realsense/cam2/color",
+                 "gelsight/left/frames", "gelsight/right/frames"):
+            assert f[k].shape[0] == T, (p, k, f[k].shape[0], T)
+        f.close()
+        print(f"OK   {p.name}  T={T}")
+    except Exception as e:
+        print(f"BAD  {p.name}  {e}")
+        p.rename(p.with_suffix(p.suffix + ".corrupt"))
+PY
+```
+
+Anything that fails to open is renamed `*.h5.corrupt` and excluded from the
+rest of the pipeline.
+
+---
+
+## Stage 2 — Compression
+
+BLOSC LZ4 is fast for recording but needs `hdf5plugin` at read time. Convert
+to GZIP+shuffle for portability and ~30–50 % size savings:
+
+```bash
+python -m twm.compress_h5 \
+    --in_dir  /media/yxma/Disk1/twm/data/motherboard/<date> \
+    --in_place
+```
+
+The script clamps chunk shapes when datasets are shorter than the default
+chunk (relevant for short test recordings). Re-run integrity check after.
+
+---
+
+## Stage 3 — Visual QA preview MP4 (per episode)
+
+```bash
+# Projection overlay is on by default; the default --cam_calib list already
+# includes all three cameras.
+python -m twm.visualize \
+    /media/yxma/Disk1/twm/data/motherboard/<date> \
+    --save_videos
+
+# Same but no overlay (faster, useful for raw-stream sanity checks):
+python -m twm.visualize \
+    /media/yxma/Disk1/twm/data/motherboard/<date> \
+    --save_videos --no_projection
+```
+
+These MP4s are for the operator only — scrub each one and flag:
+- partial occlusions or out-of-frame moments,
+- visible OT dropouts (the projection dot stays still while the hand moves),
+- color/exposure problems,
+- per-date "active sensors" (i.e. did you only use one side?).
+
+Write findings into `tasks.json:per_date_notes.<date>`.
+
+---
+
+## Stage 4 — Contact indexing → `.pt`
+
+Re-run for the new date:
+
+```bash
+python -m twm.contact_index \
+    --in_root  /media/yxma/Disk1/twm/data/motherboard/<date> \
+    --out_root /media/yxma/Disk1/twm/processed/mode1_v1/motherboard/<date>
+```
+
+This downsamples cam0 to 128×128, builds the three contact metrics per side
+(intensity / area / mixed), and stores reference-frame metadata in
+`_contact_meta`. Reference strategy is `p01` (the 1st-percentile of
+intensity over the whole episode), which is robust against early-frame
+calibration drift.
+
+Sanity check:
+
+```bash
+python - <<'PY'
+import torch
+p = "/media/yxma/Disk1/twm/processed/mode1_v1/motherboard/<date>/episode_006.pt"
+ep = torch.load(p, weights_only=False)
+print(list(ep.keys()))
+print("T:", ep["view"].shape[0])
+print("ref drift L/R:", ep["_contact_meta"]["drift_left"], ep["_contact_meta"]["drift_right"])
+PY
+```
+
+If either drift > 5.0 the gel surface moved significantly between the
+reference frame and the rest of the episode — flag the episode.
+
+---
+
+## Stage 5 — Automated failure-mode detection
+
+Three failure modes are detected from the new `.pt` files and logged to
+`figures/dataset_figures/bad_frames.json` + summarised in
+`data_quality_breakdown.json`.
+
+### 5A. Tactile intensity spikes (LED flicker)
+
+A frame whose tactile intensity exceeds `p999 + 30 (uint8)` is treated as
+a momentary LED dropout. Stored as `intensity_spikes: [[a, b], ...]` per
+episode, with a 3-frame buffer on each side.
+
+### 5B. Pose teleports
+
+Per-frame OT velocity > 5 m/s → impossible motion → marker swap or brief
+solver glitch. Stored as `pose_teleports_L` / `pose_teleports_R`.
+
+### 5C. OptiTrack freezes (long held poses)
+
+A sensor whose 7-vec pose is bitwise-identical across consecutive frames
+for ≥ 1 s while that sensor is **active** for the date is treated as a
+tracking loss. Threshold sweep at 1/2/5/10/30 s historically shows
+near-identical totals (≈13 % of frames at any threshold ≥1 s), so 1 s is
+the safe default. The cut intervals are written to `freeze_intervals.json`
+and merged into `bad_frames.json`.
+
+Today the three detectors live in separate one-off scripts:
+- intensity spikes + pose teleports: the original detector that produced
+  the current `bad_frames.json`. To re-run incrementally, regenerate the
+  whole file from all `.pt` files; the script is not yet packaged but
+  follows the formula above.
+- pose freezes: `/tmp/freeze_cut_report.py` (per-episode + per-threshold
+  totals across the whole task). For the per-interval list used by the
+  dataloader, run the unmerged-intervals path in
+  `/tmp/inspect_short_freezes.py`.
+
+**To do — consolidation.** These three detectors should be merged into a
+single `scripts/detect_failures.py` that:
+1. iterates `.pt` files under a `--pt_root`,
+2. applies all three detectors,
+3. writes the union to `bad_frames.json` and a richer per-mode breakdown
+   to `freeze_intervals.json` and `data_quality_breakdown.json`,
+4. emits the per-episode `data_quality_report.csv`.
+
+Until that exists, the procedure is: re-run each of the three current
+scripts in turn and merge their outputs by hand into `bad_frames.json`.
+
+---
+
+## Stage 6 — Visual QA gallery GIFs (for HF)
+
+```bash
+python /home/yxma/MultimodalData/twm/scripts/make_episode_gifs_v3.py \
+    --data_root /media/yxma/Disk1/twm/data/motherboard \
+    --pt_root   /media/yxma/Disk1/twm/processed/mode1_v1/motherboard \
+    --out_root  /media/yxma/Disk1/twm/figures/episode_previews/motherboard \
+    --tasks_json yxma_React/tasks.json
+```
+
+Settings (all configurable but the defaults are vetted):
+- 60 frames evenly across [2 %, 98 %] of the episode
+- 3 cameras shown left|middle|right with sensor projection overlay
+- 256-color palette (preserves tactile gradients)
+- ≤ 4 MB hard cap; on overflow the script first shrinks the spatial
+  resolution, then drops palette down to 128 colours, never below
+- Output: one GIF per episode under
+  `figures/episode_previews/<task>/<date>/episode_*.gif`
+
+These GIFs are uploaded to HF and rendered inline on the dataset card.
+
+---
+
+## Stage 7 — Per-event QA clips for borderline failures
+
+Run only when Stage 5 flags something subtle (short freezes, weak intensity
+spikes, single-frame teleports):
+
+```bash
+python /home/yxma/MultimodalData/twm/scripts/inspect_short_freezes.py \
+    --thr_min_s 1 --thr_max_s 5 \
+    --out_dir /media/yxma/Disk1/twm/figures/dataset_figures/freeze_check_short
+```
+
+Each event becomes one short GIF (~60 frames) with the affected sensor
+circled red. The operator scans these and decides per-event whether to
+keep, cut, or merge intervals. Final calls live in `freeze_intervals.json`
+under a `manual_verdict: {"keep"|"cut"|"merge"}` field.
+
+---
+
+## Stage 8 — Update metadata
+
+Touch three files before pushing to HF:
+
+1. `tasks.json`
+   - Add the new date to `tasks.<task>.dates`.
+   - Add a `per_date_notes.<date>` block:
+     ```json
+     {
+       "kind": "session",
+       "active_sensors": ["left", "right"],
+       "note": "human-readable summary, e.g. 'bimanual; one OT freeze in ep_017'"
+     }
+     ```
+   - Update `n_episode_files`.
+
+2. `bad_frames.json` — automatically refreshed by Stage 5.
+
+3. `data_quality_breakdown.json` — automatically refreshed by Stage 5.
+
+---
+
+## Stage 9 — Docs refresh
+
+If the new session adds material the dataset card or supporting docs
+don't already describe, update:
+- `README.md` "At a glance" counters (episodes, frames, duration).
+- `docs/quality.md` if a new failure mode appeared, or percentages
+  changed by > 0.5 %.
+- `docs/recording.md` if hardware / capture rate / sensor lineup changed.
+- `docs/caveats.md` for any operator-noted anomaly.
+
+---
+
+## Stage 10 — Push to HF
+
+Pre-flight check — these must all be true:
+
+- [ ] every `episode_*.h5` has a matching `episode_*.pt`
+- [ ] every `episode_*.pt` has been touched by `twm.contact_index` after
+      the most recent recording (timestamps, file size)
+- [ ] `tasks.json:per_date_notes.<date>` exists
+- [ ] `bad_frames.json:episodes.<date>/<ep>` exists for every episode
+- [ ] every episode has a preview GIF under
+      `figures/episode_previews/<task>/<date>/`
+- [ ] `data_quality_breakdown.json` reflects the new totals
+
+Then upload:
+
+```bash
+python - <<'PY'
+from huggingface_hub import upload_folder
+upload_folder(
+    repo_id="yxma/React",
+    repo_type="dataset",
+    folder_path=".",
+    path_in_repo=".",
+    commit_message="Add <date> session + curation pipeline outputs",
+)
+PY
+```
+
+(Set `HF_HUB_ENABLE_HF_TRANSFER=1` for fast LFS uploads.)
+
+---
+
+## Failure-mode reference table
+
+| Mode                | Detector                                       | Threshold        | Where logged                              |
+|---------------------|------------------------------------------------|------------------|-------------------------------------------|
+| LED intensity spike | `tactile_<side>_intensity[t] - p999 > 30`      | uint8 scale      | `bad_frames.json:intensity_spikes`        |
+| Pose teleport       | inter-frame velocity                           | > 5 m/s          | `bad_frames.json:pose_teleports_{L,R}`    |
+| OT freeze           | pose bitwise-identical for ≥ N frames          | ≥ 1 s (≈30 fr.)  | `bad_frames.json` + `freeze_intervals.json` |
+| Contact-ref drift   | `_contact_meta.drift_{side}`                   | > 5.0            | `_contact_meta` (per-episode .pt)         |
+| Color shift / hue   | (manual; from Stage 3 MP4 review)              | —                | `tasks.json:per_date_notes.<date>.note`   |
+| Occlusion           | (manual; from Stage 3 MP4 review)              | —                | same                                       |
+| Audio-buffer drops  | (recorder logs at capture time)                | —                | recording-machine log                      |
+
+---
+
+## Quick "I'm adding one new date" runbook
+
+```bash
+DATE=2026-06-01
+TASK=motherboard
+
+# 1. integrity
+python scripts/integrity_check.py data/$TASK/$DATE
+
+# 2. compress
+python -m twm.compress_h5 --in_dir data/$TASK/$DATE --in_place
+
+# 3. preview MP4 (operator scrub)
+python -m twm.visualize_projection data/$TASK/$DATE --save_videos
+
+# 4. contact index → .pt
+python -m twm.contact_index \
+    --in_root  data/$TASK/$DATE \
+    --out_root processed/mode1_v1/$TASK/$DATE
+
+# 5. detect failure modes
+python scripts/detect_failures.py --date $DATE
+
+# 6. gallery GIFs
+python scripts/make_episode_gifs_v3.py --only_date $DATE
+
+# 7. per-event clips (only if Stage 5 flagged subtle stuff)
+python scripts/inspect_short_freezes.py --only_date $DATE
+
+# 8/9. edit tasks.json + README + docs/* by hand
+
+# 10. push
+HF_HUB_ENABLE_HF_TRANSFER=1 python scripts/push_hf.py
+```
+
+If any stage produces an unexpected count or a new failure mode, stop the
+pipeline and write it up in `docs/caveats.md` before pushing.