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README.md

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+---
+license: mit
+task_categories:
+- robotics
+- computer-vision
+language:
+- en
+tags:
+- robotics
+- manipulation
+- vision
+- imitation-learning
+- lerobot
+- so101
+- strawberries
+- tic-tac-toe
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files: "data/**/*.parquet"
+  default: true
+---
+# SO101 Merged Strawberries & Tic-Tac-Toe Dataset
+
+## Dataset Description
+
+This dataset contains robot manipulation episodes combining two distinct tasks using SO101 robot. The dataset includes 27 episodes of robot manipulation with multi-view camera observations.
+
+## Tasks
+
+**Task 0**: Pick up strawberries and put them in a tray
+**Task 1**: Pick up an X piece and place it on the tic-tac-toe board to complete the winning line
+
+**Robot**: SO101 Follower robot with 6 degrees of freedom
+
+## Dataset Structure
+
+This dataset follows the LeRobot format and contains:
+
+- **Data**: Parquet files containing robot states, actions, and metadata
+- **Videos**: MP4 files with camera observations (front and wrist views)
+- **Metadata**: JSON files with episode information and statistics
+
+### Task Distribution
+
+| Task | Description | Episodes | Frames |
+|------|-------------|----------|--------|
+| 0 | Pick up the strawberries and put it in the tray | 19 | 32641 |
+| 1 | Pick up an X piece and place it on the tic-tac-toe board to complete the winning line | 8 | 13734 |
+
+### Features
+
+- **Action**: 6-dimensional robot joint positions
+  - `shoulder_pan.pos`: Shoulder pan joint position
+  - `shoulder_lift.pos`: Shoulder lift joint position  
+  - `elbow_flex.pos`: Elbow flex joint position
+  - `wrist_flex.pos`: Wrist flex joint position
+  - `wrist_roll.pos`: Wrist roll joint position
+  - `gripper.pos`: Gripper position
+
+- **Observation State**: 6-dimensional robot joint states (same as action)
+
+- **Images**: Multi-view camera observations
+  - `observation.images.front`: Front camera view (256x256x3 RGB)
+  - `observation.images.wrist`: Wrist camera view (256x256x3 RGB)
+
+- **Metadata**:
+  - `timestamp`: Frame timestamps in seconds
+  - `frame_index`: Frame index within episode
+  - `episode_index`: Episode index
+  - `task_index`: Task index (0 for strawberry picking, 1 for tic-tac-toe)
+
+## Usage
+
+### Using LeRobot
+
+```python
+from lerobot import load_dataset
+# Load the dataset
+dataset = load_dataset("kinam0252/merged_strawberries_tictactoe")
+# Access episodes by task
+strawberry_episodes = dataset.filter(lambda x: x["task_index"] == 0)
+tic_tac_toe_episodes = dataset.filter(lambda x: x["task_index"] == 1)
+# Access episodes
+for episode in dataset:
+    print(f"Episode {episode['episode_index']}: {len(episode)} frames")
+    print(f"Task: {episode['task_index']}")
+    print(f"Actions shape: {episode['action'].shape}")
+    print(f"Images keys: {list(episode['observation.images'].keys())}")
+```
+
+### Direct Loading
+
+```python
+import pandas as pd
+import json
+# Load episode data
+df = pd.read_parquet("data/chunk-000/episode_000000.parquet")
+# Load metadata
+with open("meta/info.json", "r") as f:
+    info = json.load(f)
+# Access robot actions and states
+actions = df["action"].values
+states = df["observation.state"].values
+# Filter by task
+strawberry_data = df[df["task_index"] == 0]
+tic_tac_toe_data = df[df["task_index"] == 1]
+```
+
+## Dataset Statistics
+
+- **Total Episodes**: 27
+- **Total Frames**: 46375
+- **Total Tasks**: 2
+- **FPS**: 30
+- **Average Episode Length**: ~1717 frames (~57 seconds)
+- **Robot DOF**: 6 (shoulder_pan, shoulder_lift, elbow_flex, wrist_flex, wrist_roll, gripper)
+- **Video Resolution**: 256x256x3 RGB
+- **Video Codec**: AV1
+
+## Citation
+If you use this dataset, please cite:
+```bibtex
+@dataset{merged_strawberries_tictactoe_2024,
+  title={SO101 Merged Strawberries & Tic-Tac-Toe Dataset},
+  author={Your Name},
+  year={2024},
+  publisher={Hugging Face},
+  url={https://huggingface.co/datasets/kinam0252/merged_strawberries_tictactoe}
+}
+```
+
+## License
+This dataset is licensed under the MIT license.
+
+## Acknowledgments
+
+- Built using the LeRobot framework
+- Robot demonstrations performed with SO101 robot arm
+- Video encoding optimized with AV1 codec for efficient storage
+- Merged from two distinct manipulation tasks for multi-task learning

meta/episodes_stats.jsonl

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