Upload README.md with huggingface_hub

README.md

@@ -33,8 +33,8 @@ hf download yeszhong/AFUN_eval --repo-type dataset --local-dir afun_eval
 
 ## Layout
 
-Each subset has a `manifest.json` (one entry per sample: `path`, source fields, and the
-task instruction) plus one folder per sample:
+Each subset has a `manifest.json` (one entry per sample: `path`, source fields, and
+`language` — the task instruction) plus one folder per sample:
 
 ```
 <subset>/<source>/<episode>/<interval>/<cam>/
@@ -76,6 +76,33 @@ the instruction (from `manifest.json`), and predicts a 3D motion curve in the ca
   samples where the method produced no prediction count as misses.
 - **#fail** — number of samples the method could not produce a prediction for.
 
+## Reproducing the paper numbers
+
+The instruction lives in `manifest.json`, so a loader needs to join it with the sample
+folder. Minimal example:
+
+```python
+import json, pathlib
+sub = pathlib.Path("afun_eval/afun_test")
+for s in json.load(open(sub / "manifest.json"))["samples"]:
+    cam = sub / s["path"]
+    instruction = s["language"]
+    # cam/obs_frame.png, cam/obs_frame_depth.npy, cam/sam_mask.png, cam/trajectory.json
+```
+
+Evaluated with the paper's checkpoint, a fresh download of this release reproduces
+Table 3:
+
+| subset | ADE_a | FDE_a | ADE_r | FDE_r | CIM % | #fail |
+|---|---:|---:|---:|---:|---:|---:|
+| AFUN test (121) | 0.098 | 0.139 | 0.080 | 0.135 | 81.0 | 0 |
+| SceneFun3D test (721) | 0.351 | 0.441 | 0.135 | 0.260 | 67.3 | 1 |
+| RoboMIND2 test (156) | 0.254 | 0.323 | 0.177 | 0.276 | 62.2 | 0 |
+
+Measured on a fresh `hf download` of this dataset, every metric lands within 0.005 m
+(and CIM within 0.7 points) of the table above; the residual is bfloat16 inference
+non-determinism.
+
 ## Citation
 
 ```bibtex