Datasets:

HuggingFaceVLA
/

community_dataset_v2

@@ -1,109 +1,129 @@
 ---
 license: apache-2.0
-task_categories:
-- robotics
-- computer-vision
-- reinforcement-learning
 tags:
 - robotics
 - community
 - so100
 - manipulation
-- multi-user
-- collection
 - smolvla
 - lerobot
 - vision-language-action
-size_categories:
-- 100K<n<1M
 language:
 - en
-pretty_name: "LeRobot Community Dataset v2"
-viewer: false
 ---
-# LeRobot Community Dataset v2
-A large-scale collection of robotic manipulation datasets contributed by the LeRobot community. This dataset represents the second major release of community-contributed robotics data, featuring high-quality episodic demonstrations across diverse manipulation tasks.
-## 🤖 Overview
-This dataset is a curated collection of robotics demonstrations from multiple contributors, primarily focused on manipulation tasks using SO-100 robotic arms. The data was collected and processed using the [LeRobot](https://github.com/huggingface/lerobot) framework, ensuring consistency and compatibility across all datasets.
-**Key Features:**
-- **Multi-contributor**: Data from 59 different contributors
-- **Diverse tasks**: Wide variety of manipulation scenarios and objects
-- **Standardized format**: All data in LeRobot v2.0/v2.1 format
-- **Quality filtered**: Automated processing and validation pipeline
-- **Ready for training**: Compatible with [SmolVLA](https://huggingface.co/blog/smolvla) and other VLA models
 ## 📊 Dataset Statistics
 | Metric | Value |
 |--------|-------|
-| Total Datasets | 170 |
-| Total Episodes | N/A |
-| Total Frames | N/A |
-| Contributors | 59 |
-| Robot Types | SO-100 (various colors) |
-| Data Format | LeRobot v2.0 and v2.1 dataset format |
-| Total Size | ~5032.889999999998 GB |
-| Success Rate | 87% (170/196 from input list) |
-## 🏗️ Dataset Structure
-The dataset maintains the original contributor-based organization:
 ```
 community_dataset_v2/
-├── user1/
-│   ├── dataset1/
-│   │   ├── data/
-│   │   ├── meta/
-│   │   └── videos/
-│   └── dataset2/
-│       ├── data/
-│       ├── meta/
-│       └── videos/
-├── user2/
-│   └── dataset3/
 └── ...
 ```
-Each individual dataset follows the standard LeRobot format with:
-- `data/`: Contains the episode data (observations, actions, rewards)
-- `meta/`: Metadata files including episode information
-- `videos/`: MP4 video files for visual observations
-## 🔧 Prerequisites
-Before using this dataset, install LeRobot and authenticate with Hugging Face:
-### Install LeRobot
 ```bash
-# Install conda if not available
-# conda install -c conda-forge ffmpeg  # Required for video processing
-# Install LeRobot from source
 git clone https://github.com/huggingface/lerobot.git
 cd lerobot
 pip install -e .
 ```
-### Authenticate with Hugging Face
 ```bash
 huggingface-cli login
 ```
-## 📥 Usage
 ### Download the Dataset
 ```python
 from huggingface_hub import snapshot_download
-# Download the entire dataset (requires authentication)
-local_dir = snapshot_download(
     repo_id="HuggingFaceVLA/community_dataset_v2",
     repo_type="dataset",
     local_dir="./community_dataset_v2"
@@ -116,95 +136,99 @@ local_dir = snapshot_download(
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
 import os
-# List all available datasets
-dataset_root = "./community_dataset_v2"
-for user_name in os.listdir(dataset_root):
-    user_path = os.path.join(dataset_root, user_name)
-    if os.path.isdir(user_path):
-        for dataset_name in os.listdir(user_path):
-            dataset_path = os.path.join(user_path, dataset_name)
-            if os.path.isdir(dataset_path):
-                print(f"{user_name}/{dataset_name}")
-# Load a specific dataset
-dataset = LeRobotDataset("./community_dataset_v2/user_name/dataset_name")
-# Access episodes
-for episode_idx in range(len(dataset.episode_indices)):
-    episode = dataset[episode_idx]
-    # Process episode data...
 ```
-### Integration with SmolVLA (COMING SOON)
 ```python
-# Example usage with SmolVLA - needs testing
-from transformers import AutoProcessor, AutoModelForVision2Seq
-processor = AutoProcessor.from_pretrained("HuggingFaceTB/SmolVLM-Instruct")
-model = AutoModelForVision2Seq.from_pretrained("HuggingFaceTB/SmolVLM-Instruct")
-# Process robotics episodes for VLA training
-# Implementation details coming soon...
 ```
-## 📋 Data Collection
-The data was primarily collected using [LeRobot](https://github.com/huggingface/lerobot) software with SO-100 robotic arms, ensuring consistency in data format and quality across contributors. The collection process involved:
-1. **Community Contribution**: Multiple researchers and practitioners contributed datasets
-2. **Standardization**: All data converted to LeRobot standard format
-3. **Quality Control**: Automated validation and filtering pipeline
-4. **Processing**: Consistent preprocessing and format normalization
-## 🔄 Processing Pipeline
-This dataset was processed using an automated pipeline that:
-- ✅ Validates dataset format compatibility
-- ✅ Removes corrupted or incomplete episodes
-- ✅ Standardizes video formats and resolutions
-- ✅ Generates comprehensive metadata
-- ✅ Ensures LeRobot v2.0/v2.1 compatibility
-**Processing Results:**
-- Input datasets: 196
-- Successfully processed: 170
-- Success rate: 87%
-- Failed datasets: 26 (mainly due to format incompatibility)
-## 🤝 Contributing
-This dataset represents community contributions. If you'd like to contribute additional datasets:
-1. Ensure your data follows the [LeRobot dataset format](https://github.com/huggingface/lerobot)
-2. Contact the maintainers for inclusion in future releases
-3. Follow the quality guidelines and formatting standards
-## 📚 Related Work
-- [SmolVLA Model](https://huggingface.co/HuggingFaceTB/SmolVLM-Instruct) - Vision-Language-Action model
-- [SmolVLA Blog Post](https://huggingface.co/blog/smolvla) - Detailed overview and applications
-- [SmolVLA Paper](https://arxiv.org/abs/2501.00403) - Technical details and benchmarks
-- [LeRobot Datasets Blog](https://huggingface.co/blog/lerobot-datasets) - Overview of robotics datasets
-## 📄 License
-This dataset is released under the Apache 2.0 license. Please cite appropriately if used in research.
-## 🔗 Citation
-If you use this dataset in your research, please cite:
-```bibtex
-@dataset{community_dataset_v2,
-  title={LeRobot Community Dataset v2},
-  author={LeRobot Community},
-  year={2024},
-  publisher={Hugging Face},
-  url={https://huggingface.co/datasets/HuggingFaceVLA/community_dataset_v2}
-}
-```
 ---
-Built with ❤️ by the SmolVLA team and LeRobot Community

 ---
 license: apache-2.0
 tags:
 - robotics
 - community
 - so100
 - manipulation
 - smolvla
 - lerobot
 - vision-language-action
+- embodied-ai
+task_categories:
+- robotics
 language:
 - en
+size_categories:
+- 100K<n<1M
+pretty_name: Community Dataset v2
 ---
+# Community Dataset v2
+A large-scale community-contributed robotics dataset for vision-language-action learning, featuring **170 datasets** from **59 contributors** worldwide.
+This dataset represents the second major release of community-contributed robotics data, expanding upon the success of Community Dataset v1. The data was collected and processed using the [LeRobot](https://github.com/huggingface/lerobot) framework with automated processing and validation pipelines to ensure high quality and compatibility.
+## 🌟 Overview
+This dataset represents a collaborative effort from the robotics and AI community to build comprehensive training data for embodied AI systems. Each contribution contains demonstrations of robotic manipulation tasks with the SO100 arm, recorded using [LeRobot tools](https://github.com/huggingface/lerobot), primarily focused on tabletop scenarios and everyday object interactions.
 ## 📊 Dataset Statistics
 | Metric | Value |
 |--------|-------|
+| **Total Datasets** | 170 |
+| **Total Episodes** | 6,325 |
+| **Total Frames** | 5,033,418 |
+| **Total Videos** | 12,650 |
+| **Contributors** | 59 |
+| **Weighted Average FPS** | 30.0 |
+| **Average Episodes per Dataset** | 38.1 |
+| **Total Duration** | 46.6 hours |
+| **Average Hours per Dataset** | 0.28 |
+| **Primary Tasks** | Manipulation, Pick & Place, Sorting |
+| **Robot Types** | SO-100 (various colors) |
+| **Data Format** | LeRobot v2.0 and v2.1 dataset format |
+| **Total Size** | 59 GB |
+## 🗂️ Structure
+The dataset maintains a clear hierarchical structure:
 ```
 community_dataset_v2/
+├── contributor1/
+│   ├── dataset_name_1/
+│   │   ├── data/           # Parquet files with observations
+│   │   ├── videos/         # MP4 recordings
+│   │   └── meta/           # Metadata and info
+│   └── dataset_name_2/
+├── contributor2/
+│   └── dataset_name_3/
 └── ...
 ```
+Each dataset follows the LeRobot format standard, ensuring compatibility with existing frameworks and easy integration.
+## 🏆 Top Contributors
+| Contributor | Datasets Quantity |
+|-------------|----------|
+| kantine | 26 |
+| duthvik | 17 |
+| abokinala | 9 |
+| danaaubakirova | 8 |
+| roboticshack | 7 |
+| 1g0rrr | 6 |
+| sihyun77 | 6 |
+| Congying1112 | 5 |
+| sixpigs1 | 5 |
+| nguyen-v | 4 |
+## 🚀 Usage
+### Prerequisites
+**1. Install LeRobot**
+Follow the [official LeRobot installation guide](https://huggingface.co/docs/lerobot/installation):
 ```bash
+# Create conda environment with Python 3.10
+conda create -y -n lerobot python=3.10
+conda activate lerobot
+# Install ffmpeg (required for video processing)
+conda install ffmpeg -c conda-forge
 git clone https://github.com/huggingface/lerobot.git
 cd lerobot
+# Install LeRobot from Source
 pip install -e .
 ```
+**2. Authenticate with Hugging Face**
+You need to be logged in to access the dataset:
 ```bash
+# Login to Hugging Face
 huggingface-cli login
+# Or alternatively, set your token as an environment variable
+# export HF_TOKEN=your_token_here
 ```
+Get your token from [https://huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
 ### Download the Dataset
 ```python
 from huggingface_hub import snapshot_download
+# Download entire collection (requires authentication)
+dataset_path = snapshot_download(
     repo_id="HuggingFaceVLA/community_dataset_v2",
     repo_type="dataset",
     local_dir="./community_dataset_v2"
 from lerobot.datasets.lerobot_dataset import LeRobotDataset
 import os
+# Browse available datasets
+for contributor in os.listdir("./community_dataset_v2"):
+    contributor_path = f"./community_dataset_v2/{contributor}"
+    if os.path.isdir(contributor_path):
+        for dataset in os.listdir(contributor_path):
+            print(f"📁 {contributor}/{dataset}")
+# Load a specific dataset (requires authentication)
+dataset = LeRobotDataset(
+    repo_id="local",
+    root="./community_dataset_v2/contributor_name/dataset_name"
+)
+# Access episodes and observations
+print(f"Episodes: {len(dataset.episode_indices)}")
+print(f"Total frames: {len(dataset)}")
 ```
+### Integration with SmolVLA
 ```python
+COMING SOON
+# This dataset is designed for training VLA models
+# Compatible with SmolVLA training pipelines
+# needs testing
 ```
+## 🔧 Dataset Format
+Each dataset contains:
+- **`data/`**: Parquet files with timestamped observations
+  - Robot states (joint positions, velocities)
+  - Action sequences
+  - Camera observations (multiple views)
+  - Language instructions
+- **`videos/`**: Synchronized video recordings
+  - Multiple camera angles
+  - High-resolution capture
+  - Timestamp alignment
+- **`meta/`**: Metadata and configuration
+  - Dataset info (fps, episode count)
+  - Robot configuration
+  - Task descriptions
+## 🎯 Intended Use
+This dataset is designed for:
+- **Vision-Language-Action (VLA) model training**
+- **Robotic manipulation research**
+- **Imitation learning experiments**
+- **Multi-task policy development**
+- **Embodied AI research**
+## 📈 Revisions
+- **v2.0**: Expanded community collection
+  - 170 datasets from 59 contributors
+  - Standardized LeRobot v2.0/v2.1 format
+  - Advanced quality filtering and validation
+  - Comprehensive automated processing pipeline
+## 🤝 Community Contributions
+This dataset exists thanks to the generous contributions from researchers, hobbyists, and institutions worldwide. Each dataset represents hours of careful data collection and curation.
+### Contributing Guidelines
+Future contributions should follow:
+- LeRobot dataset format
+- Consistent naming conventions for the features, camera views etc.
+- Quality validation checks
+- Proper task descriptions, describing the actions precisely.
+Check the [blogpost](https://huggingface.co/blog/lerobot-datasets) for more information
+## 📄 License
+Released under Apache 2.0 license. Individual datasets may have additional attribution requirements - please check contributor documentation.
+## 🔗 Related Work
+- [LeRobot Framework](https://github.com/huggingface/lerobot)
+- [SmolVLA model](https://huggingface.co/lerobot/smolvla_base)
+- [SmolVLA Blogpost](https://huggingface.co/blog/smolvla)
+- [SmolVLA Paper](https://huggingface.co/papers/2506.01844)
+- [Docs](https://huggingface.co/docs/lerobot/smolvla)
+- [How to Build a successful Robotics dataset with Lerobot?](https://huggingface.co/blog/lerobot-datasets)
 ---
+*Built with ❤️ by the SmolVLA team and LeRobot Community*