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description: Detailed guide on using YOLO with DOTA dataset for object detection, including dataset preparation, image splitting, and label handling. |
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keywords: Ultralytics, YOLO, DOTA dataset, object detection, image processing, python, dataset preparation, image splitting, label handling, YOLO with DOTA, computer vision, AI, machine learning |
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# Reference for `ultralytics/data/split_dota.py` |
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!!! Note |
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This file is available at [https://github.com/ultralytics/ultralytics/blob/main/ultralytics/data/split_dota.py](https://github.com/ultralytics/ultralytics/blob/main/ultralytics/data/split_dota.py). If you spot a problem please help fix it by [contributing](https://docs.ultralytics.com/help/contributing/) a [Pull Request](https://github.com/ultralytics/ultralytics/edit/main/ultralytics/data/split_dota.py) 🛠️. Thank you 🙏! |
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<br><br> |
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## ::: ultralytics.data.split_dota.bbox_iof |
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## ::: ultralytics.data.split_dota.load_yolo_dota |
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## ::: ultralytics.data.split_dota.get_windows |
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## ::: ultralytics.data.split_dota.get_window_obj |
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<br><br> |
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## ::: ultralytics.data.split_dota.crop_and_save |
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## ::: ultralytics.data.split_dota.split_images_and_labels |
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## ::: ultralytics.data.split_dota.split_trainval |
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<br><br> |
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## ::: ultralytics.data.split_dota.split_test |
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<br><br>
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