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.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+manifests/agibot/train_index.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,65 @@
+---
+license: other
+pretty_name: merlin DMD training data
+task_categories: ["robotics", "other"]
+tags: ["robotics", "world-model", "video-generation", "causal-forcing", "oscar"]
+---
+
+# merlin DMD training data
+
+The data used by the DMD stage (`release/stage_configs/3_dmd_merlin.yaml`, branch `release/merlin-causal-forcing`) that
+produced **merlin**, OSCAR-2B distilled into a 4-step causal robot-video model with Causal Forcing++. The same five
+manifests and text-embedding store were used by every training stage of merlin.
+
+## Contents
+
+| path | what |
+|---|---|
+| `clips/<dataset>/shard-XXXXX.tar` | ~10 GB uncompressed tars; members are `<episode>/<cam>/{rgb.mp4, gripper_scenario.mp4, caption.pickle}` |
+| `manifests/<dataset>/train_index.jsonl` | the training manifests, unchanged except `data_root` is `clips/<dataset>` (relative) |
+| `manifests/shards.json` | which shard holds which dataset, with file counts |
+| `text_cache/reason1_proj1024_T81/` | caption embeddings: `index.json` (sha1 of stripped caption → row), `meta.json`, and `emb.f16.npy` ([104779, 512, 1024] float16) as zstd parts `emb.f16.npy.zst.part-NN` with its sha256 in `emb.f16.npy.sha256` |
+| `prepare.py` | restores the tree, the embedding file, and manifests with absolute paths |
+
+Per clip: `rgb.mp4` is the target video (640×360; DMD uses its first frame as the condition),
+`gripper_scenario.mp4` the control video (arm skeleton and gripper drawn on black, same length and resolution) and
+`caption.pickle` a dict `{"caption": str}`. The loader stretches both videos to 640×384 and uses 81-frame windows;
+rows with `n_frames < 81` are in the manifests but skipped by the loader.
+
+| dataset | manifest rows | rows with ≥ 81 frames |
+|---|---:|---:|
+| agibot | 83,481 | 62,120 |
+| droid | 36,356 | 35,877 |
+| rh20t_cfg5 | 4,447 | 4,438 |
+| rh20t_cfg7 | 1,328 | 1,328 |
+| interndata | 1,006 | 1,006 |
+
+Note: these files are **not** identical to the public [zywu2115/OSCAR_robot](https://huggingface.co/datasets/zywu2115/OSCAR_robot)
+release. Captions match, but control videos differ in resolution/rendering for some subsets (e.g. DROID), and
+OSCAR_robot ships no `rgb.mp4`.
+
+## Usage
+
+```bash
+hf download csusupergear/merlin-dmd-data --repo-type dataset --local-dir merlin_dmd_data
+python merlin_dmd_data/prepare.py --repo_dir merlin_dmd_data      # needs zstd on PATH; prints the config overrides
+```
+
+Then set `data_index_files` and `text_cache_dir` in `3_dmd_merlin.yaml` to the printed values.
+
+## Licenses
+
+Each subset keeps its upstream license; use is **non-commercial** for all but DROID.
+
+| subset | upstream | license |
+|---|---|---|
+| agibot | [AgiBot World](https://huggingface.co/datasets/agibot-world/AgiBotWorld-Beta) | CC-BY-NC-SA-4.0 |
+| droid | [DROID](https://droid-dataset.github.io/) | CC-BY-4.0 |
+| rh20t_cfg5, rh20t_cfg7 | [RH20T](https://rh20t.github.io/) | CC-BY-NC-4.0 |
+| interndata | [InternData-A1](https://huggingface.co/datasets/InternRobotics/InternData-A1) | CC-BY-NC-SA-4.0 |
+
+Control videos and captions are derived from the OSCAR pipeline
+([wuzy2115/oscar-public](https://github.com/wuzy2115/oscar-public), [OSCAR_robot](https://huggingface.co/datasets/zywu2115/OSCAR_robot));
+caption embeddings are from Cosmos-Reason1-7B projected by OSCAR-2B's `crossattn_proj`. Please cite the upstream
+datasets, OSCAR, and Causal Forcing / Causal Forcing++ ([arXiv:2602.02214](https://arxiv.org/abs/2602.02214),
+[arXiv:2605.15141](https://arxiv.org/abs/2605.15141)).

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+}

prepare.py

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+"""Restore the merlin DMD training data from a download of csusupergear/merlin-dmd-data.
+
+  python prepare.py --repo_dir <download dir> [--out <dir>]   # --out defaults to --repo_dir
+
+1. extracts clips/<dataset>/shard-*.tar into <out>/clips/<dataset>/<episode>/<cam>/{rgb.mp4,gripper_scenario.mp4,caption.pickle}
+2. reassembles text_cache/reason1_proj1024_T81/emb.f16.npy from its zstd parts and checks its sha256
+3. writes <out>/manifests_abs/<dataset>/train_index.jsonl with absolute data_root, and prints the config overrides
+"""
+import argparse, hashlib, json, os, subprocess, tarfile
+
+STORE = "text_cache/reason1_proj1024_T81"
+
+
+def sha256(path, bufsize=1 << 24):
+    h = hashlib.sha256()
+    with open(path, "rb") as f:
+        while chunk := f.read(bufsize):
+            h.update(chunk)
+    return h.hexdigest()
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--repo_dir", required=True)
+    ap.add_argument("--out", default=None)
+    ap.add_argument("--skip_text", action="store_true")
+    a = ap.parse_args()
+    repo = os.path.abspath(a.repo_dir)
+    out = os.path.abspath(a.out or repo)
+
+    shards = json.load(open(os.path.join(repo, "manifests", "shards.json")))
+    for ds, items in shards.items():
+        dst = os.path.join(out, "clips", ds)
+        os.makedirs(dst, exist_ok=True)
+        for it in items:
+            done = os.path.join(dst, ".extracted_" + os.path.basename(it["file"]))
+            if os.path.exists(done):
+                continue
+            with tarfile.open(os.path.join(repo, it["file"])) as tf:
+                tf.extractall(dst, filter="data")
+            open(done, "w").close()
+            print("extracted", it["file"], flush=True)
+
+    if not a.skip_text:
+        src = os.path.join(repo, STORE)
+        dst = os.path.join(out, STORE)
+        os.makedirs(dst, exist_ok=True)
+        for f in ("index.json", "meta.json"):
+            if os.path.abspath(os.path.join(src, f)) != os.path.abspath(os.path.join(dst, f)):
+                subprocess.run(["cp", os.path.join(src, f), dst], check=True)
+        emb = os.path.join(dst, "emb.f16.npy")
+        want = open(os.path.join(src, "emb.f16.npy.sha256")).read().split()[0]
+        if not (os.path.exists(emb) and sha256(emb) == want):
+            parts = sorted(p for p in os.listdir(src) if p.startswith("emb.f16.npy.zst.part-"))
+            print(f"reassembling emb.f16.npy from {len(parts)} parts", flush=True)
+            cat = subprocess.Popen(["cat"] + [os.path.join(src, p) for p in parts], stdout=subprocess.PIPE)
+            with open(emb, "wb") as fo:
+                subprocess.run(["zstd", "-d", "--long=27", "-c"], stdin=cat.stdout, stdout=fo, check=True)
+            cat.wait()
+            got = sha256(emb)
+            if got != want:
+                raise SystemExit(f"emb.f16.npy sha256 mismatch: {got} != {want}")
+        print("emb.f16.npy OK", flush=True)
+
+    files = []
+    for ds in shards:
+        p = os.path.join(out, "manifests_abs", ds, "train_index.jsonl")
+        os.makedirs(os.path.dirname(p), exist_ok=True)
+        with open(os.path.join(repo, "manifests", ds, "train_index.jsonl")) as fi, open(p, "w") as fo:
+            for line in fi:
+                if line.strip():
+                    r = json.loads(line)
+                    r["data_root"] = os.path.join(out, "clips", ds)
+                    fo.write(json.dumps(r) + "\n")
+        files.append(p)
+
+    print("\nSet in release/local/stage_configs/3_dmd_merlin.yaml:")
+    print(f"text_cache_dir: {os.path.join(out, STORE)}")
+    print("data_index_files:")
+    for p in files:
+        print(f"- {p}")
+
+
+if __name__ == "__main__":
+    main()

text_cache/reason1_proj1024_T81/emb.f16.npy.sha256

@@ -0,0 +1 @@
+4c1331ff58bdba47b30f8cbd7a1d508c0b78d304948a3b0bf840e245c187ac2c  emb.f16.npy