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README.md
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## Training
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The model was trained using standard binary cross-entropy loss and an Adam optimizer. It was trained on grayscale images resized to 128x128 pixels.
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## Model Performance
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The model performs well in scenarios where images need to be automatically detected for correct orientation. However, the performance can vary based on the image quality, input resolution, and types of rotations present in the dataset.
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## Training
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The model was trained using standard binary cross-entropy loss and an Adam optimizer. It was trained on grayscale images resized to 128x128 pixels.
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## GitHub Repository
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Training scripts and evaluation scripts are available at https://github.com/fcrescio/rotdet
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## Model Performance
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The model performs well in scenarios where images need to be automatically detected for correct orientation. However, the performance can vary based on the image quality, input resolution, and types of rotations present in the dataset.
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