chore: 添加测试文件

- check_all_episodes.py：检查各个episode是否有重复帧。
- check_specific_frames.py：检查前几帧是否位于正确初始位置。
- generate_dataset_videos.py：根据hdf5生成视频

check_all_episodes.py

@@ -0,0 +1,91 @@
+#!/usr/bin/env python3
+"""
+检查所有 episode 的重复帧情况
+
+找出哪些 episode 有问题，需要删除或重新收集
+"""
+import os
+import h5py
+import glob
+import numpy as np
+
+
+def check_all_episodes():
+    """检查所有 episode 的质量"""
+
+    dataset_dir = "roboimi/demos/dataset/sim_transfer"
+    episode_files = sorted(glob.glob(os.path.join(dataset_dir, "episode_*.hdf5")))
+    episode_files = sorted(episode_files, key=lambda x: int(x.split('_')[-1].replace('.hdf5', '')))
+
+    print("="*80)
+    print("所有 Episode 质量检查")
+    print("="*80)
+
+    good_episodes = []
+    bad_episodes = []
+
+    for ep_idx, ep_file in enumerate(episode_files):
+        ep_name = os.path.basename(ep_file).replace('.hdf5', '')
+
+        try:
+            with h5py.File(ep_file, 'r') as f:
+                img_path = '/observations/images/top'
+                if img_path not in f:
+                    continue
+
+                images = f[img_path][:]
+
+                # 检查前 50 帧的重复情况
+                check_frames = min(50, len(images))
+                duplicate_count = 0
+
+                for i in range(check_frames - 1):
+                    img1 = images[i]
+                    img2 = images[i + 1]
+                    diff = np.mean(np.abs(img1.astype(float) - img2.astype(float)))
+
+                    if diff < 1.0:  # 重复
+                        duplicate_count += 1
+
+                duplicate_rate = duplicate_count / check_frames * 100
+
+                # 判断质量
+                if duplicate_rate > 10:  # 超过10%重复
+                    bad_episodes.append((ep_idx, ep_name, duplicate_rate, duplicate_count))
+                    status = "❌"
+                else:
+                    good_episodes.append((ep_idx, ep_name, duplicate_rate, duplicate_count))
+                    status = "✅"
+
+                print(f"{status} Episode {ep_idx:2d}: {duplicate_rate:5.1f}% 重复 ({duplicate_count:2d}/{check_frames}) - {ep_name}")
+
+        except Exception as e:
+            print(f"❌ Episode {ep_idx}: 错误 - {e}")
+
+    # 总结
+    print("\n" + "="*80)
+    print("总结")
+    print("="*80)
+    print(f"总共检查: {len(episode_files)} 个 episodes")
+    print(f"正常的: {len(good_episodes)} 个 ✅")
+    print(f"有问题的: {len(bad_episodes)} 个 ❌")
+
+    if bad_episodes:
+        print(f"\n有问题的 episodes:")
+        for ep_idx, ep_name, rate, count in bad_episodes:
+            print(f"  - episode_{ep_idx}.hdf5: {rate:.1f}% 重复")
+
+        print(f"\n删除命令:")
+        ep_names = [name for _, name, _, _ in bad_episodes]
+        print(f"  rm " + " ".join([f"{dataset_dir}/{name}.hdf5" for name in ep_names]))
+
+    print(f"\n建议:")
+    if len(bad_episodes) > 0:
+        print(f"  1. 删除有问题的 {len(bad_episodes)} 个 episodes")
+        print(f"  2. 重新收集数据，或使用剩余的 {len(good_episodes)} 个正常 episodes")
+    else:
+        print(f"  ✅ 所有 episodes 都正常，可以直接使用！")
+
+
+if __name__ == "__main__":
+    check_all_episodes()