Upload trimmed towel folding dataset

README.md

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+---
+license: mit
+task_categories:
+- robotics
+tags:
+- LeRobot
+- SO-100
+- robotics
+- towel-folding
+- imitation-learning
+size_categories:
+- n<1K
+---
+
+# Trimmed Towel Folding Dataset
+
+This dataset contains towel folding demonstrations trimmed to the first fold.
+
+## Dataset Details
+
+- **Original Dataset**: [arsenxeno/record-test](https://huggingface.co/datasets/arsenxeno/record-test)
+- **Task**: Towel folding (first fold only)
+- **Robot**: SO-100 with teleoperation
+- **Episodes**: 4
+- **Detection Method**: CLIP-based similarity to reference fold image
+
+## Statistics
+
+| Metric | Value |
+|--------|-------|
+| Total Episodes | 4 |
+| Average Original Length | 839 frames |
+| Average Trimmed Length | 438 frames |
+| Average Fold Time | 29.1 seconds |
+| Average Fold Similarity | 0.982 |
+
+## File Structure
+
+```
+videos/
+├── observation.images.front/
+│   ├── episode_000000.mp4
+│   ├── episode_000001.mp4
+│   └── ...
+```
+
+## Usage
+
+### Load with Python
+
+```python
+import cv2
+from pathlib import Path
+
+# Download dataset
+dataset_path = "path/to/dataset"
+
+# Load video
+video_path = Path(dataset_path) / "videos/observation.images.front/episode_000000.mp4"
+cap = cv2.VideoCapture(str(video_path))
+```
+
+### With LeRobot (if compatible)
+
+```python
+from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
+dataset = LeRobotDataset(repo_id="xenorobotics/towel-fold-trimmed-v17")
+```
+
+## License
+
+MIT License - Same as original dataset

episodes.json

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+[
+  {
+    "episode_id": "episode_000000",
+    "episode_index": 0,
+    "original_frames": 900,
+    "trimmed_frames": 313,
+    "fold_time": 20.8,
+    "fold_similarity": 0.97314453125
+  },
+  {
+    "episode_id": "episode_000001",
+    "episode_index": 1,
+    "original_frames": 771,
+    "trimmed_frames": 465,
+    "fold_time": 30.933333333333334,
+    "fold_similarity": 0.9873046875
+  },
+  {
+    "episode_id": "episode_000002",
+    "episode_index": 2,
+    "original_frames": 794,
+    "trimmed_frames": 513,
+    "fold_time": 34.13333333333333,
+    "fold_similarity": 0.9814453125
+  },
+  {
+    "episode_id": "episode_000003",
+    "episode_index": 3,
+    "original_frames": 891,
+    "trimmed_frames": 461,
+    "fold_time": 30.666666666666668,
+    "fold_similarity": 0.98486328125
+  }
+]

videos/chunk-000/observation.images.front/episode_000000.mp4

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+oid sha256:e401c11e8fb151898825c001dbfd2390e7672c1495ed147bc100f9ee141294c0
+size 9499545

videos/chunk-000/observation.images.front/episode_000001.mp4

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+oid sha256:0de49e344b1119e82b103ba1d82a1d5d9181c5d67b92f3cf233f1fca9a8ec739
+size 13725943

videos/chunk-000/observation.images.front/episode_000002.mp4

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2b40d1ddf06d0d4893ac2fdf02461b4ce7679fb623441561dd2b180fb0b9c44c
+size 14413512

videos/chunk-000/observation.images.front/episode_000003.mp4

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+version https://git-lfs.github.com/spec/v1
+oid sha256:daaf8abd4b865831080a902aad275d5e0bbee6b6db47bf3c97da4d5174b29d96
+size 13043857