| """Grab the middle-frame of every *_pred_handobject.mp4 and tile into a single |
| image for quick visual QA of object-track placements across all episodes.""" |
| import argparse, glob, os, math |
| import cv2 |
| import numpy as np |
| import imageio.v2 as imageio |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--src_glob", required=True) |
| ap.add_argument("--out_path", required=True) |
| ap.add_argument("--cell_w", type=int, default=256) |
| ap.add_argument("--cell_h", type=int, default=144) |
| ap.add_argument("--cols", type=int, default=8) |
| args = ap.parse_args() |
|
|
| files = sorted(glob.glob(args.src_glob)) |
| n = len(files) |
| rows = math.ceil(n / args.cols) |
| print(f"{n} videos -> {rows}x{args.cols} grid") |
|
|
| canvas = np.full((rows * args.cell_h, args.cols * args.cell_w, 3), 255, dtype=np.uint8) |
| for i, p in enumerate(files): |
| c = cv2.VideoCapture(p) |
| nf = int(c.get(cv2.CAP_PROP_FRAME_COUNT)) |
| c.set(cv2.CAP_PROP_POS_FRAMES, nf // 2) |
| r, frame = c.read() |
| c.release() |
| if not r: |
| continue |
| frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) |
| cell = cv2.resize(frame, (args.cell_w, args.cell_h), interpolation=cv2.INTER_AREA) |
| |
| name = os.path.basename(p).replace("_pred_handobject.mp4", "").replace("table2_", "") |
| cv2.putText(cell, name, (4, 14), |
| cv2.FONT_HERSHEY_SIMPLEX, 0.4, (0, 0, 0), 1, cv2.LINE_AA) |
| rr, cc = divmod(i, args.cols) |
| canvas[rr * args.cell_h:(rr + 1) * args.cell_h, |
| cc * args.cell_w:(cc + 1) * args.cell_w] = cell |
|
|
| imageio.imwrite(args.out_path, canvas) |
| print(f"saved {args.out_path} ({canvas.shape[1]}x{canvas.shape[0]})") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
