SO101 Object in Box v0.4 Fixed
Multimodal dataset containing data on the handling of objects placed in a box. It is used for the study and development of models in robotics and vision.
Description
SO101 Object in Box v0.4 Fixed is a multimodal dataset that contains over 22,000 examples related to manipulating objects in a box. It is designed to support research in robotics, computer vision, and machine learning.
What is this dataset for?
- Develop algorithms for manipulating objects in robotics
- Studying the recognition and placement of objects in constrained environments
- Train models for computer vision and physical interaction
Can it be enriched or improved?
This dataset could be improved with finer annotations on object positions, additional videos, or additional data from various sensors.
🔎 In summary
🧠 Recommended for
- Robotic researchers
- Computer vision developers
- ML engineers
🔧 Compatible tools
- ROS
- OpenCV
- PyTorch
- TensorFlow
💡 Tip
Combine this dataset with video footage to improve dynamic modeling.
Frequently Asked Questions
Exactly what types of data does this dataset contain?
Mainly multimodal data related to the manipulation of objects, possibly images, sensors and positions.
Can this dataset be used to train manipulative robots?
Yes, it is designed to train models for manipulating objects in constrained environments.
Is there metadata about the objects manipulated?
The dataset includes basic annotations, enrichment is possible.
