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SmolVLA Top-Down Grasp Evaluation
Eval of yianW/smolvla_mug_grasp_topdown.
How the eval was built
Each episode uses the exact scene parameters (object_euler, object_scale, pedestal_height, xy_offset) from a successful training trajectory (from rerot_jitter_results.json, jitter_from_successes_results.json, and jitter_round2_results.json). Up to 5 diverse configs per (mug, base_rot) case, evenly sampled across the z-rotation range. One subprocess per episode so the Genesis morph is baked with the correct per-episode euler (previous eval reused one scene per mug and applied set_quat, which composes with the baked morph rotation and therefore didn't produce the intended world orientation).
Overall
13/52 = 25.0% success (lift object z > 3 cm within 150 steps).
Per-case results
| Case | Success |
|---|---|
cup_rot000 |
2/5 (40%) |
cup_rot180 |
5/5 (100%) |
mug_2_tripo_rot180 |
2/5 (40%) |
mug_5_tripo_rot090 |
1/5 (20%) |
mug_7_tripo_rot180 |
2/5 (40%) |
mug_9_tripo_rot000 |
0/5 (0%) |
mug_9_tripo_rot270 |
0/5 (0%) |
mug_dowan_rot090 |
0/5 (0%) |
paper_coffee_cup_rot090 |
1/5 (20%) |
paper_coffee_cup_rot270 |
0/2 (0%) |
paper_cup_20_oz_rot270 |
0/5 (0%) |
Layout
Per-trial folders <case>_e<ep_idx>/ each contain episode.mp4 (third-person video, 20 fps) and result.json (scene params + success + z_delta + step count). all_results.json is the concatenated list.
Task
Grasp mug from top and lift
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