README.md

---
license: mit
task_categories:
- image-to-image
- text-to-image
language:
- en
pretty_name: Robotic Action Prediction Dataset using RoboTwin
size_categories:
- 10K<n<100K
dataset_info:
  features:
  - name: current_frame
    dtype: image
  - name: instruction
    dtype: string
  - name: future_frame
    dtype: image
  splits:
  - name: train
    num_bytes: 10494869755.67105
    num_examples: 73042
  - name: test
    num_bytes: 2623790321.13095
    num_examples: 18261
  download_size: 13119010103
  dataset_size: 13118660076.801998
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---


# Robotic Action Prediction Dataset

## Dataset Description

This dataset contains triplets of (current observation, action instruction, future observation) for training models to predict future frames of robotic actions.

## Dataset Structure

### Data Fields
- `current_frame`: Input image (RGB) of the current observation
- `instruction`: Textual description of the action to perform
- `future_frame`: Target image (RGB) showing the expected outcome 50 frames later

### Data Splits
The dataset contains:
- Total samples: ~91,303 (300 episodes × 304 frames average per episode)
- Tasks:
  - `block_hammer_beat`: "beat the block with the hammer"
  - `block_handover`: "handover the blocks" 
  - `blocks_stack_easy`: "stack blocks"

### Dataset Statistics
| Task                | Episodes | Frames per Episode |
|---------------------|----------|--------------------|
| block_hammer_beat   | 100      | 200-300            |
| block_handover      | 100      | 400-500            |
| blocks_stack_easy   | 100      | 400-500            |

## Dataset Creation

### Source Data
- **Simulation Environment:** RoboTwin
- **Image Resolution:** At least 128×128 pixels
- **Frame Offset:** 50 frames between input and target