uavid-yolo26m-sem is an open-source semantic segmentation model based on YOLO, designed for processing aerial imagery such as drone footage. It is compatible with PyTorch and can be used via Python libraries or CLI for research and development in computer vision. Ideal for researchers working with UAVid datasets.
In the Other AI space, Uavid Yolo26m Sem takes a focused approach. It focuses on automating semantic segmentation of aerial imagery for computer vision tasks. Uavid Yolo26m Sem is an open-source project aimed at computer vision researchers. The project is open source (Apache-2.0). Uavid Yolo26m Sem is available on the command line.
dronefreak builds and maintains Uavid Yolo26m Sem, and the product first shipped in 2021. The project is developed in the open on GitHub with 24 stars and 17 commits in the last 90 days. Among its 5 catalogued features are semantic segmentation, aerial imagery support, and YOLO integration.
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