Comments (8)
使用命令sudo python test.py / home / zjs / Desktop /车牌测试/ --no_yolo --beam --gpu
其中/ home / zjs / Desktop /车牌测试/是一个目录,目录中包含了11张图片,有些图片中不含有车牌,
运行结果:
sudo python test.py /home/zjs/Desktop/车牌测试/ --no_yolo --beam --gpu
[17:10:29] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
粤BD01940 0.9999887 /home/zjs/Desktop/车牌测试/0004.jpg
[17:10:36] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
鲁H0A025 0.9999391 /home/zjs/Desktop/车牌测试/0006.jpeg
苏A2396V 0.99999845 /home/zjs/Desktop/车牌测试/1.jpg
[17:10:46] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
吉AF16666 0.99992096 /home/zjs/Desktop/车牌测试/0002.jpeg
京HF5427 0.9999348 /home/zjs/Desktop/车牌测试/1.jpeg
湘DD08808 0.9999857 /home/zjs/Desktop/车牌测试/0001.jpeg
鲁鲁HC999 0.9943006 /home/zjs/Desktop/车牌测试/200.jpeg
[17:10:56] src/operator/nn/./cudnn/./cudnn_algoreg-inl.h:97: Running performance tests to find the best convolution algorithm, this can take a while... (set the environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT to 0 to disable)
耗时 30 s
这个警告应该如何解决呢?并且在使用GPU的情况下,为什么耗时对比CPU更大了呢?我应该如何修改?
from alpr_utils.
这个并不是警告,那是mxnet自动选择卷积算法的提示,这是一个比较费时的操作,如果需要屏蔽按提示设置环境变量即可
from alpr_utils.
另外,因为模型规模本身不算大,单张图片使用GPU并不能有很好的加速效果。
from alpr_utils.
对于车牌检测的图片大小有什么要求吗?比如640×480
from alpr_utils.
我修改了环境变量,添加了export MXNET_CUDNN_AUTOTUNE_DEFAULT=0
设置,但是在使用GPU时,依然会报警告。这个需要怎么屏蔽掉呢?
from alpr_utils.
对于车牌检测的图片大小有什么要求吗?比如 640×480
from alpr_utils.
我这边设置好环境变量过后就可以了,耗时就会大幅度降低。或者你试试这样:
MXNET_CUDNN_AUTOTUNE_DEFAULT=0 python3 test.py --beam --gpu /path/to/image
模型是全卷积网络,理论上对图片大小没有要求。只是过大的图片对提高准确率并没有太大的帮助,所以你自己根据情况找一个效率和准确率的平衡点就好。
from alpr_utils.
好的,我试一下,感谢您的回答
from alpr_utils.
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from alpr_utils.