metadata

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