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Description
This issue is created to track the progress of YOLO model learning, testing, and scoring evaluation.
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Study YOLO training workflow
- Refer to Camera Team notes and Eurobot2025 repository.
- Understand dataset preparation, annotation format, hyperparameters, augmentation, and training pipeline.
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Test YOLO performance on hazelnut detection
- Collect/prepare dataset for hazelnut classification & detection.
- Train or evaluate existing model.
- Record detection accuracy, inference speed, and failure cases.
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Calculate scoring for each scoring area
- Analyze detection output and classify into scoring zones.
- Compute total score for each area based on detection results.
Please work this task on feat/hazelnut_detect_yolo
If you have any questions or ideas, please feel free to bring them up as soon as possible.
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