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README.md

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+# Robot Data Processing
+
+Utilities for turning raw robot HDF5 recordings into a synchronized dataset and then into the [LeRobot v2.1](https://github.com/huggingface/lerobot) format for training.
+
+Pipeline:
+
+```
+raw image + low-dim HDF5
+        │  sync_image_low_dim.py
+        ▼
+    synced HDF5  ──►  visualize_synced_data.py  (per-demo MP4 previews)
+        │
+        │  convert_synced_h5_to_lerobot.py
+        ▼
+    LeRobot v2.1 dataset folder
+```
+
+## Environment setup
+
+Create and activate a conda env, then install the dependencies:
+
+```
+conda create -n robotdata python=3.10 -y
+conda activate robotdata
+pip install h5py numpy opencv-python datasets
+pip install lerobot
+```
+
+Notes:
+- Python 3.10 is the most broadly compatible with LeRobot; 3.11 also works.
+- `lerobot` pulls in `torch`, `huggingface_hub`, and other heavy deps. If the resolver is slow, install `lerobot` first and add the smaller packages after.
+- If you need a specific CUDA build of `torch`, install it before `lerobot` using the selector on pytorch.org.
+
+Quick sanity check:
+
+```
+python -c "import h5py, numpy, cv2, datasets, lerobot; print('ok')"
+```
+
+## Scripts
+
+### 1. `sync_image_low_dim.py` — align two HDF5 streams
+
+Merges an image HDF5 and a low-dimensional HDF5 into a single synced file. Image timestamps are the master timeline; low-dim samples are aligned by nearest timestamp. Handles zero-valued timestamps, sudden timestamp jumps, and non-overlapping intervals by skipping affected demos. Demos excluded or skipped are **renamed to be consecutive** (`demo_0`, `demo_1`, …) in the output so there are no gaps.
+
+**Inputs (per HDF5):** `data/<demo>/obs/<timestamp_key>` plus any number of per-demo datasets.
+
+**Output:** `data/<demo>/obs/{timestamp, <image_keys…>, <lowdim_keys…>}` and optional `data/<demo>/actions`.
+
+**Example:**
+
+```
+python sync_image_low_dim.py --image-h5 /path/raw_images.hdf5 --lowdim-h5 /path/raw_lowdim.hdf5 --output-h5 /path/synced.h5 --allow-missing
+```
+
+**Useful flags:**
+- `--image-keys`, `--lowdim-keys` — restrict which obs datasets to copy (defaults to all except timestamp).
+- `--exclude-demo demo_4 demo_5` — drop specific demos. Remaining demos are reindexed.
+- `--skip-n N` — keep every `(N+1)`-th frame after syncing (e.g. `--skip-n 2` → keep 0, 3, 6, …).
+- `--allow-missing` — log and skip demos with missing keys instead of failing.
+
+### 2. `visualize_synced_data.py` — render per-demo MP4 previews
+
+Renders each demo to an MP4 with selected camera views side-by-side and optional lowdim overlays as on-frame text. Useful to sanity-check a sync before running the LeRobot conversion.
+
+**Example:**
+
+```
+python visualize_synced_data.py /path/synced.h5 --out-dir ./vis --fps 10 --image-keys agentview_image oak_image --overlay-keys robot0_eef_pos robot0_gripper_qpos
+```
+
+Outputs `./vis/<demo>.mp4` for each demo.
+
+### 3. `convert_synced_h5_to_lerobot.py` — synced HDF5 → LeRobot v2.1
+
+Produces a LeRobot dataset directly in `--output-dir`. The folder must not already exist.
+
+**Example (30 Hz → 10 Hz, 2 cameras, 8-dim state):**
+
+```
+python convert_synced_h5_to_lerobot.py --synced-h5 /path/synced.h5 --output-dir /path/lerobot_dataset --fps 10 --source-fps 30 --task "pass the knife by the sharp side" --image-map agentview_image:base_rgb oak_image:wrist_rgb --state-keys robot0_joint_pos robot0_gripper_qpos --action-source next_state --image-size 256 256
+```
+
+**Key flags:**
+- `--output-dir PATH` — final dataset folder (must not exist; parent is created if needed).
+- `--fps N` / `--source-fps M` — target and source frame rates. `M` must be divisible by `N`; the script subsamples by stride `M/N`. If `--source-fps` is omitted, it is estimated from the first demo's timestamps.
+- `--image-map src:dst [...]` — rename HDF5 image keys to LeRobot feature names.
+- `--state-keys k1 k2 [...]` — concatenate these lowdim datasets into a single `state` vector (order matters).
+- `--action-source {next_state, hdf5_actions}` — use the next state as the action when the HDF5 has no `actions` dataset.
+- `--image-size H W` — resize images. Omit to keep native resolution.
+- `--task "..."` — language instruction stored with every frame.
+- `--repo-id user/name` + `--push-to-hub` — optional, pushes to HuggingFace.
+
+**Output layout** (LeRobot v2.1):
+
+```
+<output-dir>/
+  meta/    info.json, episodes.jsonl, tasks.jsonl, episodes_stats.jsonl
+  data/    chunk-000/episode_<6digit>.parquet
+```
+
+## Typical workflow
+
+```
+# 1. sync raw HDF5s
+python sync_image_low_dim.py --image-h5 raw_images.hdf5 --lowdim-h5 raw_lowdim.hdf5 --output-h5 synced.h5 --allow-missing
+
+# 2. eyeball the result
+python visualize_synced_data.py synced.h5 --out-dir vis --fps 10 --image-keys agentview_image oak_image --overlay-keys robot0_eef_pos robot0_gripper_qpos
+
+# 3. convert to LeRobot
+python convert_synced_h5_to_lerobot.py --synced-h5 synced.h5 --output-dir ./lerobot_dataset --fps 10 --source-fps 30 --task "your instruction" --image-map agentview_image:base_rgb oak_image:wrist_rgb --state-keys robot0_joint_pos robot0_gripper_qpos --action-source next_state --image-size 256 256
+```