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@shukur-alom shukur-alom released this 30 Apr 06:04
· 9 commits to master since this release

Develop a deep learning model using the YOLOv8 architecture to accurately detect cars in aerial imagery captured by drones. This model will be trained on the VisDrone dataset, which offers a rich collection of drone-captured images with diverse scenarios and object annotations.

Benefits:

  • Enhanced Car Detection: The custom YOLOv8 model will be specifically tailored to identify cars in drone footage, potentially surpassing the performance of generic object detection models on this task.

  • Improved Performance in Drone-Specific Conditions: Training on the VisDrone dataset, which includes variations in lighting, weather, and object density, will help the model generalize better to real-world drone footage.