| |
| """Diagnose why Stack-Can tableHF_ep002.mp4 (a SUCCESS) scored track_max=0.0. |
| |
| Re-runs the EXACT runtime TrackFlowScorer used by compare_robo_trackflow.py |
| on ep002 (and ep000 as a healthy reference), verbose, a few times — SAM3 is |
| non-deterministic so we want to see how often the can/plate detection misses. |
| """ |
| import sys, os, numpy as np |
|
|
| RL = "/home/hongyi/PWM/policy_rl/rl" |
| for p in [RL, f"{RL}/old/online"]: |
| if p not in sys.path: |
| sys.path.insert(0, p) |
| from rewards import TrackFlowScorer |
|
|
| M = "/home/hongyi/PWM/reward_model/3pointr_models" |
| SC = "/home/hongyi/PWM/external/DiffSynth-Studio/data/robot_new/Stack-Can" |
| TF_GPU = os.environ.get("TF_GPU", "0") |
|
|
|
|
| def ckpt(): |
| for c in ("stack_can_canplate_150pts_384_flow_backbone_final.pth", |
| "stack_can_canplate_150pts_384_flow_backbone.pth"): |
| if os.path.exists(f"{M}/{c}"): |
| return f"{M}/{c}" |
| raise FileNotFoundError |
|
|
|
|
| tf = TrackFlowScorer( |
| pointr_ckpt=ckpt(), |
| prompt="red can", prompt_fallbacks=["can", "orange can"], |
| mark_prompt="white round plate", |
| mark_prompt_fallbacks=["white circle", "white disc", "white object on the table"], |
| subprocess_gpu=TF_GPU, verbose=True) |
|
|
| NRUNS = int(os.environ.get("NRUNS", "3")) |
| for ep in ("ep002", "ep000"): |
| v = f"{SC}/tableHF_{ep}.mp4" |
| print(f"\n########## {ep} {v} ##########", flush=True) |
| for i in range(NRUNS): |
| tp = tf.score(v, mode="progress_gated", k_pixel=50.0) |
| tp = np.asarray(tp) |
| print(f">>> {ep} run{i}: track_max={tp.max():.4f} nonzero={int((tp>0).sum())}/{tp.size}", |
| flush=True) |
|
|
