Hussain223/franka-episodes-v1

Franka Episodes Dataset (Cube & Ball)

This dataset contains RGB images and per-episode JSON logs recorded from a Franka Panda robotic arm simulation.
It includes both scripted expert demonstrations and behavior cloning (BC) policy rollouts, covering tasks with a cube and a ball.

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📂 Contents

• episodes/ — JSON logs per episode.
  • Each file (e.g., episode_000.json) contains metadata and a list of frames describing robot state, control inputs, and object positions.
  • Keys include: episode_id, physics_type, robot_control, frames, and sometimes task.
• images/ — RGB frames associated with episodes (PNG).
  • Organized in subfolders like images/ep_001/ep001_step000.png.
• bc_models/ — Behavior cloning checkpoints used for rollout generation (optional, not required for dataset use).

Example structure

franka-episodes-v1/
├─ episodes/
│  ├─ episode_000.json
│  ├─ episode_001.json
│  └─ ...
├─ images/
│  ├─ ep_0001/
│  │  ├─ ep001_step000.png
│  │  ├─ ep001_step001.png
│  │  └─ ...
│  └─ ep_0002/...
└─ bc_models/

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📊 Dataset Statistics

• Total size: ~7.58 GB
• Episodes (JSON): 61
• Episodes with images: 60
• Total images: ~70,000
• Frames per episode: ~695 to ~2104
• Image resolution: 640×480 RGB

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⚠️ Note on Data

Some episodes were perturbed or modified for robustness experiments.
This makes the dataset useful for research on adversarial robustness, poisoned data handling, and imitation learning under noisy conditions.

If you just need clean demonstrations, you can filter or manually check episodes.

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🔧 Dataset Generation

• Environment: Genesis Simulator with Franka Panda arm.
• Episode types:
  • Scripted expert motions (pick, place, throw).
  • Behavior cloning (BC) rollouts trained from demonstrations.

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🚀 Usage

Load with 🤗 Datasets

from datasets import load_dataset

dataset = load_dataset("Hussain223/franka-episodes-v1")

# Example access
episode = dataset["train"][0]
print(episode.keys())

Parse a JSON log

import json

with open("episodes/episode_000.json", "r") as f:
    ep = json.load(f)

print("Episode ID:", ep["episode_id"])
print("Number of frames:", len(ep["frames"]))

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💡 Applications

• Imitation learning — train BC or DAGGER policies.
• Robustness research — benchmark algorithms under poisoned/noisy data.
• Perception tasks — object recognition, pose estimation from frames.
• Policy evaluation — compare scripted vs. learned rollouts.

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📜 License

Released under the MIT License.

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📌 Versioning

• v1.0 (current): 61 episodes, ~70k images, 7.58 GB.
• Future versions may include more tasks, objects, or real-world data.

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✍️ Citation

If you use this dataset, please cite:

@misc{franka_episodes_hussain223,
  title  = {Franka Episodes (Cube & Ball)},
  author = {Hussain Alibrahim},
  year   = {2025},
  url    = {https://huggingface.co/datasets/Hussain223/franka-episodes-v1}
}

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📬 Contact

• Open a discussion on the dataset page.
• Or reach out via Hugging Face profile contact.