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20cfecb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 | #!/usr/bin/env python3
"""
批量可视化 contact / force 并拼成 combined 三联视频。
对 --root 下每个含 modalities/ 的 episode:
1) 渲染 contact_vis.mp4 / force_vis.mp4 (黑底, 对齐原视频)
2) 横向拼接 original + contact + force -> combined_vis.mp4
一遍 pass 同时写出三个 vis 文件 + combined, 不重复解码。
多进程并行, 已有 combined 默认跳过, 单 episode 失败不中断整批。
用法:
python batch_visualize.py --root .../all_episodes
python batch_visualize.py --root .../all_episodes --workers 8 --overwrite
python batch_visualize.py --root .../all_episodes --glob "00*" # 只跑匹配的
"""
import os
import json
import argparse
import traceback
import numpy as np
import cv2
from pathlib import Path
from concurrent.futures import ProcessPoolExecutor, as_completed
LABELS = ["original", "contact", "force"]
def load_norm(modalities_dir):
with open(modalities_dir / "norm_params.json") as f:
n = json.load(f)
return n["max_contact"], n["max_force"]
def render_contact(contact, max_contact):
"""黑底白斑: 亮度 = 归一化接触强度"""
c = np.clip(contact / max_contact, 0, 1)
gray = (c * 255).astype(np.uint8)
return cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
def render_force(force, max_force):
"""黑底彩斑: 亮度 = |force|, 色相 = xyz 方向"""
mag = np.sqrt((force ** 2).sum(-1))
brightness = np.clip(mag / max_force, 0, 1)
norm = mag.copy()
norm[norm < 1e-8] = 1.0
direction = force / norm[..., None] # 单位向量 [-1,1]
color = (direction + 1.0) / 2.0 # -> [0,1] 当 RGB
rgb = color * brightness[..., None]
bgr = (rgb[..., ::-1] * 255).astype(np.uint8)
return bgr
def _fit(img, W, H):
"""模态分辨率万一和原视频不一致, resize 回去避免 hstack 崩"""
if img.shape[1] != W or img.shape[0] != H:
img = cv2.resize(img, (W, H), interpolation=cv2.INTER_NEAREST)
return img
def process_episode(ep, video_name, overwrite):
ep = Path(ep)
mod = ep / "modalities"
combined_path = ep / "combined_vis.mp4"
if not mod.is_dir():
return ep.name, "skip (no modalities/)"
if combined_path.exists() and not overwrite:
return ep.name, "skip (exists)"
max_contact, max_force = load_norm(mod)
cap = cv2.VideoCapture(str(ep / video_name))
if not cap.isOpened():
cap.release()
return ep.name, f"skip (cannot open {video_name})"
fps = cap.get(cv2.CAP_PROP_FPS) or 30.0
W = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
H = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fourcc = cv2.VideoWriter_fourcc(*"mp4v")
c_out = cv2.VideoWriter(str(mod / "contact" / "contact_vis.mp4"), fourcc, fps, (W, H))
f_out = cv2.VideoWriter(str(mod / "force" / "force_vis.mp4"), fourcc, fps, (W, H))
comb = cv2.VideoWriter(str(combined_path), fourcc, fps, (W * 3, H))
frame_idx = 0
while True:
ret, orig = cap.read()
if not ret:
break
cp = mod / "contact" / f"{frame_idx:06d}.npy"
c_vis = render_contact(np.load(cp), max_contact) if cp.exists() \
else np.zeros((H, W, 3), np.uint8)
c_vis = _fit(c_vis, W, H)
fp = mod / "force" / f"{frame_idx:06d}.npy"
f_vis = render_force(np.load(fp), max_force) if fp.exists() \
else np.zeros((H, W, 3), np.uint8)
f_vis = _fit(f_vis, W, H)
c_out.write(c_vis)
f_out.write(f_vis)
trio = [orig.copy(), c_vis.copy(), f_vis.copy()]
for img, label in zip(trio, LABELS):
cv2.putText(img, label, (10, 25),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 0), 2)
comb.write(np.hstack(trio))
frame_idx += 1
cap.release()
c_out.release()
f_out.release()
comb.release()
return ep.name, f"ok ({frame_idx} frames)"
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--root", type=str, required=True,
help="包含多个 episode 子目录的父目录")
parser.add_argument("--glob", type=str, default="*",
help="episode 目录名匹配模式 (相对 root)")
parser.add_argument("--video_name", type=str, default="camera2.mp4")
parser.add_argument("--workers", type=int,
default=min(8, os.cpu_count() or 1))
parser.add_argument("--overwrite", action="store_true",
help="重新生成已存在的 combined_vis.mp4")
args = parser.parse_args()
root = Path(args.root)
ep_dirs = [p for p in sorted(root.glob(args.glob))
if (p / "modalities").is_dir()]
print(f"Found {len(ep_dirs)} episodes under {root} (workers={args.workers})")
ok = skip = fail = 0
with ProcessPoolExecutor(max_workers=args.workers) as ex:
futs = {ex.submit(process_episode, str(ep), args.video_name, args.overwrite): ep
for ep in ep_dirs}
for fut in as_completed(futs):
ep = futs[fut]
try:
name, status = fut.result()
print(f"[{name}] {status}")
if status.startswith("ok"):
ok += 1
else:
skip += 1
except Exception:
fail += 1
print(f"[{ep.name}] FAILED\n{traceback.format_exc()}")
print(f"\nDone. ok={ok} skip={skip} fail={fail}")
if __name__ == "__main__":
main() |