Comments (5)
补充:
下面这个表述有问题:
(1)导出模型的输出是否就是原始YOLOv3模型的输出?为什么我在测试Paddle-Lite自己写的推理程序时,由于少了一个原始图片输入,导致程序core掉,原始YOLOv3模型需要原始图片信息?
应该是:
(1)导出模型的输出是否就是原始YOLOv3模型的输出?为什么我在测试Paddle-Lite自己写的推理程序时,由于少了一个“原始图片尺寸”的输入,导致程序core掉,原始YOLOv3模型的输入需要原始图片尺寸信息?
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你好:
-
保存的YOLOv3模型的输入是YOLOv3网络要求的输入,即原始图片经过减均值除方差转换为[C, H, W]之后的数据,预处理过程见
PaddleDetection/configs/yolov3_reader.yml
Line 68 in 8a8b279
预处理操作的python实现见
https://github.com/PaddlePaddle/PaddleDetection/blob/master/ppdet/data/transform/operators.py
基于PaddleLite部署的话,输出数据需要是采用上述预处理之后的图片数据,预测部署预处理的c++代码可以参考
https://github.com/PaddlePaddle/PaddleDetection/tree/master/inference/preprocessor -
保存模型的输出是已经解析好并做过NMS之后的box信息,输出是一个shape为[N, 6]的数据,其中N为预测框的个数,6为[class_id, score, x1, y1, x2, y2], 输出格式参考
https://www.paddlepaddle.org.cn/documentation/docs/zh/api_cn/layers_cn/multiclass_nms_cn.html#multiclass-nms
预测部署输出bbox处理C++代码参考
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@zhuyushi 感谢反馈,我们也会同步增强下文档~
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#241 已在docs/advanced_tutorials/inference/EXPORT_MODEL.md处添加详细的导出模型的输入输出介绍,可以参考
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有paddlex的吗
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