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使用ccpd训练车牌检测(100k),db模型训练,loss至0.3。 使用 python tools/infer_det.py -c configs/det/det_mv3_db_v1.1_plate.yml -o Global.checkpoints=./output/det_db/best_accuracy 预测结果效果很差,看issue #214 #647 提示是尺寸缩放问题,我把db_process.py中self.resize_type = 1重设为self.resize_type = 0,效果尚可。 问题:为什么训练好的模型,直接进行测试效果差,改代码效果可以。这种训练和推理尺寸不一致的问题,在crnn识别模型里也存在(#1044),是否可以优化掉。
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配置用的icdar2015的reader,里面的参数都是针对icdar2015这个集合的,是为了大家方便对齐我们的icdar2015上的指标,所以换了别的数据后shape不适用,需要调整。也可以用tools/infer/predict_*中的脚本进行预测,这里不存在shape问题。
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使用ccpd训练车牌检测(100k),db模型训练,loss至0.3。
使用
python tools/infer_det.py -c configs/det/det_mv3_db_v1.1_plate.yml -o Global.checkpoints=./output/det_db/best_accuracy
预测结果效果很差,看issue
#214
#647
提示是尺寸缩放问题,我把db_process.py中self.resize_type = 1重设为self.resize_type = 0,效果尚可。
问题:为什么训练好的模型,直接进行测试效果差,改代码效果可以。这种训练和推理尺寸不一致的问题,在crnn识别模型里也存在(#1044),是否可以优化掉。
The text was updated successfully, but these errors were encountered: