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Mihail
MishaGGG
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VDC-team/README
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π Excited to open-source the **UAVid Semantic Segmentation Model Zoo** on Hugging Face. This release includes: * π¦ A **YOLO-compatible mirror** of the UAVid semantic segmentation dataset, preserving the original train/val/test splits while reorganizing the directory structure for plug-and-play use with modern training pipelines. * π€ Multiple **YOLO26 semantic segmentation models** trained on UAVid, spanning Nano through Medium variants. * π Detailed model cards with evaluation metrics, per-class IoU, confusion matrices, qualitative results, and training configurations for reproducibility. The goal is to make benchmarking and experimenting with aerial semantic segmentation easier by providing ready-to-use datasets and pretrained models in a consistent format. If you're working on UAV perception, autonomous drones, robotics, remote sensing, or real-time semantic segmentation, I hope these resources are useful. **π¦ Dataset:** https://huggingface.co/datasets/dronefreak/UAVid-2020 **π€ Model Collection:** https://huggingface.co/collections/dronefreak/uavid-semantic-segmentation-model-zoo Feedback, bug reports, and contributions are always welcome.
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SupraLabs/Supra-Router-51M:
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