File size: 2,229 Bytes
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Side-by-side comparison:
[replay (collected actions)] | [original *_pred.mp4] | [DP-predicted actions]
All clipped to first 16 frames at 1280x720.
"""
import argparse
from pathlib import Path
import cv2
import numpy as np
def load_n(video, n):
cap = cv2.VideoCapture(video)
frames = []
for _ in range(n):
ret, f = cap.read()
if not ret:
break
frames.append(f)
cap.release()
return frames
def label(img, text):
out = img.copy()
h = out.shape[0]
cv2.rectangle(out, (0, 0), (out.shape[1], 60), (0, 0, 0), -1)
cv2.putText(out, text, (20, 42), cv2.FONT_HERSHEY_SIMPLEX, 1.2, (255, 255, 255), 2)
return out
def main():
p = argparse.ArgumentParser()
p.add_argument("--replay_video", required=True)
p.add_argument("--reference_video", required=True)
p.add_argument("--dp_video", required=True)
p.add_argument("--n", type=int, default=16)
p.add_argument("--out", required=True)
p.add_argument("--scale", type=float, default=0.5,
help="Scale factor per panel.")
args = p.parse_args()
rep = load_n(args.replay_video, args.n)
ref = load_n(args.reference_video, args.n)
dp = load_n(args.dp_video, args.n)
n = min(len(rep), len(ref), len(dp))
print(f"Loaded: replay={len(rep)} ref={len(ref)} dp={len(dp)} -> using n={n}")
panels = []
for i in range(n):
r = label(rep[i], "replay (collected actions)")
f = label(ref[i], "original _pred.mp4")
d = label(dp[i], "DP-predicted actions")
# Resize all to same height
scale = args.scale
new_w = int(r.shape[1] * scale)
new_h = int(r.shape[0] * scale)
r = cv2.resize(r, (new_w, new_h))
f = cv2.resize(f, (new_w, new_h))
d = cv2.resize(d, (new_w, new_h))
panels.append(np.concatenate([r, f, d], axis=1))
h, w = panels[0].shape[:2]
Path(args.out).parent.mkdir(parents=True, exist_ok=True)
out = cv2.VideoWriter(args.out, cv2.VideoWriter_fourcc(*"mp4v"), 5, (w, h))
for p_ in panels:
out.write(p_)
out.release()
print(f"Saved: {args.out} ({w}x{h}, {n} frames @ 5fps)")
if __name__ == "__main__":
main()
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