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--- |
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license: cc-by-4.0 |
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task_categories: |
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- object-detection |
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tags: |
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- Autonomous Driving |
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pretty_name: PandaSet |
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size_categories: |
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- 10K<n<100K |
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--- |
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PandaSet aims to promote and advance research and development in autonomous driving and machine learning. |
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The first open-source dataset made available for both academic and commercial use, PandaSet combines Hesai’s best-in-class LiDAR sensors with Scale AI’s high-quality data annotation. |
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PandaSet features data collected using a forward-facing LiDAR with image-like resolution (PandarGT) as well as a mechanical spinning LiDAR (Pandar64). |
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The collected data was annotated with a combination of cuboid and segmentation annotation (Scale 3D Sensor Fusion Segmentation). |
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PandaSet features: |
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- 48,000 camera images |
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- 16,000 LiDAR sweeps |
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- 103 scenes of 8s each |
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- 28 annotation classes |
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- 37 semantic segmentation labels |
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- Full sensor suite: 1x mechanical LiDAR, 1x solid-state LiDAR, 6x cameras, On-board GPS/IMU |
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[Official webpage](https://pandaset.org) | |
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[Dev-kit](https://github.com/scaleapi/pandaset-devkit) |
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**Note**: I am not affiliated with the creators of PandaSet (Scale and Hesai). |
