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README.md
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pretty_name: Robotic Action Prediction Dataset using RoboTwin
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- 10K<n<100K
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pretty_name: Robotic Action Prediction Dataset using RoboTwin
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size_categories:
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- 10K<n<100K
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# Robotic Action Prediction Dataset
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## Dataset Description
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This dataset contains triplets of (current observation, action instruction, future observation) for training models to predict future frames of robotic actions.
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## Dataset Structure
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### Data Fields
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- `current_frame`: Input image (RGB) of the current observation
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- `instruction`: Textual description of the action to perform
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- `future_frame`: Target image (RGB) showing the expected outcome 50 frames later
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### Data Splits
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The dataset contains:
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- Total samples: ~91,303 (300 episodes × 304 frames average per episode)
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- Tasks:
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- `block_hammer_beat`: "beat the block with the hammer"
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- `block_handover`: "handover the blocks"
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- `blocks_stack_easy`: "stack blocks"
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### Dataset Statistics
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| Task | Episodes | Frames per Episode |
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|---------------------|----------|--------------------|
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| block_hammer_beat | 100 | 200-300 |
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| block_handover | 100 | 400-500 |
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| blocks_stack_easy | 100 | 400-500 |
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## Dataset Creation
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### Source Data
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- **Simulation Environment:** RoboTwin
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- **Image Resolution:** At least 128×128 pixels
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- **Frame Offset:** 50 frames between input and target
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