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VyoJ/BridgeData-V2-Scripted-Images

BridgeData V2 Image Triplets Dataset This dataset contains image triplets from BridgeData V2 trajectories in ImageFolder format. Derived From This dataset is a derivative of the 30 GB scripted subset of BridgeData V2 from RAIL-Berkeley. All rights and original licensing apply. Dataset Structure initial_images/: Contains first frame images (initial state) intermediate_images/: Contains intermediate frame images (frame 38) final_images/: Contains… See the full description on the dataset page: https://huggingface.co/datasets/VyoJ/BridgeData-V2-Scripted-Images.

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BridgeData V2 Image Triplets Dataset

This dataset contains image triplets from BridgeData V2 trajectories in ImageFolder format.

Derived From

This dataset is a derivative of the 30 GB scripted subset of BridgeData V2 from RAIL-Berkeley. All rights and original licensing apply.

Dataset Structure

  • initial_images/: Contains first frame images (initial state)
  • intermediate_images/: Contains intermediate frame images (frame 38)
  • final_images/: Contains final frame images (frame 43)
  • metadata.jsonl: Contains metadata for each trajectory with image file paths

Format

Each trajectory contributes one entry with:

  • First image (frame 0) - Initial state
  • Intermediate image (frame 38) - Intermediate edited state
  • Frame 43 image (frame 43) - Final edited state
  • Trajectory metadata (campaign, session, trajectory names, etc.)

All images have a consistent resolution of 640 x 480 pixels.

Statistics

  • Total trajectories: 8802
  • Total images: 26406
  • Image triplets per trajectory: 1
  • Image resolution: 640 x 480 pixels

Loading the Dataset

python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("imagefolder", data_dir="path/to/dataset")

# Access image triplets
example = dataset[0]
initial_image = example["first_image_file_name"]  # PIL Image - frame 0 (in initial_images/)
intermediate_image = example["intermediate_image_file_name"]  # PIL Image - frame 38 (in intermediate_images/)
final_image = example["frame_43_image_file_name"]  # PIL Image - frame 43 (in final_images/)
metadata = {k: v for k, v in example.items() if not k.endswith("_file_name") and k != "intermediate_image_file_name"}

Citation

If you use this dataset, please cite the original BridgeData V2 paper:

bibtex
@inproceedings{walke2023bridgedata,
    title={BridgeData V2: A Dataset for Robot Learning at Scale},
    author={Walke, Homer and Black, Kevin and Lee, Abraham and Kim, Moo Jin and Du, Max and Zheng, Chongyi and Zhao, Tony and Hansen-Estruch, Philippe and Vuong, Quan and He, Andre and Myers, Vivek and Fang, Kuan and Finn, Chelsea and Levine, Sergey},
    booktitle={Conference on Robot Learning (CoRL)},
    year={2023}
} 

Generated on: 2025-09-07

VyoJ/BridgeData-V2-Scripted-Images · CoolFace