Comments (6)
@beizhengren 其实sample_detector的time是包括pre-process和post process,inference time是比detect time短;darknet是inference time 不包括pre process和post process。
而且,darknet的计算复杂度和fp32下的复杂度本身就是接近的,只是trt降低了显存的使用
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@enazoe
按照您说的, 我试了下只对doinference做测试, 帧率在20fps.
是的,我测试darknet显存大概占用1.5G, 而您的工程在1G左右.
- 请问, configs/calibration_images.txt 这个文件我看都是图片的路径,这个是给INT8用的吗?
如果是的话, 这些图片的作用是啥(我对INT8不是很了解,不好意思) - 另外,CMakeLists.txt中
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++14 -Wno-write-strings")
我在编译的时候改成了c++14, 否则会有bug.
谢谢
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@beizhengren
1.是的,无标签图片是用于int8校准的,就是因为int8序列化时候可表示的位数变少,需要训练的图片做校准
2.改为c++14不确定会不会有问题,不过你可以试试。
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@enazoe
感谢!
1.那这些图片是从训练集中随机选取就可以吗?对数量有没有要求呢?
2.c++11会报找不到make_unique().可能是我本地的环境吧.
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@beizhengren
没有要求,100张左右吧,记得好像是在官网看到过,但是记不太清了,越多校准时间越长
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@enazoe
好! 我明白了,等有其他问题再向您请教
感谢!
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Related Issues (20)
- run engine error HOT 2
- Does this project have minimum CPU requirements? HOT 1
- 使用自己训练yolov5l模型,生成engine后检测锚框不准,在tensorrtx工程上可以正常运行,请问有可能是那部分的问题 HOT 1
- 关于dynamic input size
- where is attempt_download
- 关于yolov5s6减少类别至8的推理结果差异问题
- update yolov7 HOT 1
- 检测结果中id和真实目标的映射
- Are there any mirrors for the weight instead of "MEGA" host?
- 前处理和后处理的时间是不是太长了?
- how to find the corresponding version of yolov5?
- Explicit batch
- trt8 is not supply leaky? HOT 3
- trt8 maxpool的問題 HOT 3
- 检测结果解码时间长 HOT 8
- 有没有留一个专门函数,weights 转 engine 文件的
- 能够支持yolov3-tiny吗?
- yolo7 tiny? HOT 3
- YOLO v8
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