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提供了一个街景字符编码识别方案以供参考

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分别用ResNet50(1)和YOLOv8(2)实现了字符编码识别任务,题目源自阿里天池竞赛https://tianchi.aliyun.com/competition/entrance/531795 即使运用了较多数据增强技术和参数调优技巧,前者的准确率仍然较低,仅为60%左右 而yolov8的准确率可以接近90%。一定程度上说明了yolo的强大性能。😊

(1)的运行需要安装pytorh即可。具体见https://pytorch.org/

(2)的运行需要安装ultralytics,具体可以在对应环境内终端输入pip install ultralytics

具体可以参考https://docs.ultralytics.com/zh/quickstart/#install-ultralytics 获得更多说明

YOLO在验证集第二个小批量上(8张照片)的预测结果如下:

预测结果

其中一次的结果曲线:

result

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