Download Ctrl-World-Graph/scripts/viz_batch_grid.py from EndeavourDD/gnn_wm2: direct link, hf CLI and curl.
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https://huggingface.co/datasets/EndeavourDD/gnn_wm2/resolve/main/Ctrl-World-Graph/scripts/viz_batch_grid.py
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hf download hf://datasets/EndeavourDD/gnn_wm2/Ctrl-World-Graph/scripts/viz_batch_grid.py
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curl -L -o viz_batch_grid.py https://huggingface.co/datasets/EndeavourDD/gnn_wm2/resolve/main/Ctrl-World-Graph/scripts/viz_batch_grid.py
2.53 kB
| """Batch 1s/3s/6s/10s prefix grid (GT top / PRED bottom) for every window. | |
| Matches the protocol's visualization format (scripts/viz_pred_vs_gt.py grid): | |
| for each saved pred window, render a 2-row x 4-col grid of GT (top) vs PRED | |
| (bottom) at the cumulative-prefix endpoints 1s/3s/6s/10s (frames 5/15/30/50), | |
| labeled with the second and the 5fps frame id. Mirrors preds/<episode>/start<NNNN>. | |
| """ | |
| import argparse | |
| from pathlib import Path | |
| import numpy as np | |
| from PIL import Image, ImageDraw | |
| DATA = Path("/workspace/gnn_data/hanoi_0420_balanced_5fps") | |
| W, H = 320, 192 | |
| PREFIX_IDX = {"1s": 4, "3s": 14, "6s": 29, "10s": 49} # last frame of each prefix (0-based) | |
| PAD = 6 | |
| def load_gt(episode, frame_ids): | |
| return np.stack([ | |
| np.asarray(Image.open(DATA / episode / "side" / "rgb" / f"frame_{int(f):06d}.png").convert("RGB").resize((W, H), Image.BILINEAR), dtype=np.uint8) | |
| for f in frame_ids | |
| ]) | |
| def make_grid(gt, pred, frame_ids, pred_label): | |
| cols = list(PREFIX_IDX.items()) | |
| grid = np.full((2 * H + 3 * PAD + 14, len(cols) * W + (len(cols) + 1) * PAD, 3), 255, np.uint8) | |
| for c, (name, idx) in enumerate(cols): | |
| x = PAD + c * (W + PAD) | |
| grid[14 + PAD:14 + PAD + H, x:x + W] = gt[idx] | |
| grid[14 + 2 * PAD + H:14 + 2 * PAD + 2 * H, x:x + W] = pred[idx] | |
| im = Image.fromarray(grid) | |
| dr = ImageDraw.Draw(im) | |
| for c, (name, idx) in enumerate(cols): | |
| x = PAD + c * (W + PAD) | |
| dr.text((x + 4, 2), f"{name} (frame {int(frame_ids[idx])})", fill=(0, 0, 0)) | |
| dr.text((2, 14 + PAD + H // 2), "GT", fill=(255, 0, 0)) | |
| dr.text((2, 14 + 2 * PAD + H + H // 2), pred_label, fill=(255, 0, 0)) | |
| return im | |
| def main(): | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--preds-dir", type=Path, required=True) | |
| ap.add_argument("--out-dir", type=Path, required=True) | |
| ap.add_argument("--pred-label", default="PRED") | |
| cli = ap.parse_args() | |
| npzs = sorted(cli.preds_dir.glob("*/start*.npz")) | |
| print(f"{len(npzs)} windows -> {cli.out_dir}") | |
| for i, npz in enumerate(npzs, 1): | |
| episode = npz.parent.name | |
| d = np.load(npz) | |
| pred, fids = d["pred"], d["frame_ids"] | |
| gt = load_gt(episode, fids) | |
| od = cli.out_dir / episode | |
| od.mkdir(parents=True, exist_ok=True) | |
| make_grid(gt, pred, fids, cli.pred_label).save(od / f"{npz.stem}.png") | |
| if i % 20 == 0 or i == len(npzs): | |
| print(f" {i}/{len(npzs)}", flush=True) | |
| print("done:", cli.out_dir) | |
| if __name__ == "__main__": | |
| main() | |