ALPR CPU/GPU
Thanh Tùng
Though i set "CONFIG_GPGPU_ENABLED = true", but it did not work on GPU, so now who can help me to solve this problem to work on GPU
Kamal Chhirang
Mamadou DIOP
Yesterday you showed me the C# code you're using. If you check it again you'll see that there is a comment saying that the first time you run the inference code it'll be slow because we load the deep learning models: https://github.com/DoubangoTelecom/ultimateALPR-SDK/blob/master/samples/csharp/recognizer/Program.cs#L254.
What you're reporting is 20 to 130 times slower that what's expected.
It's easy to check the average inference time:
1/ Make the first inference outside the loop to force initialization or call UltAlprSdkEngine::warmup function
2/ Call the processing function 100 to 1000 times within a loop. Do not include your image decoding or any other code in the loop.
3/ Get the time before entering the loop then after and compute the difference to get the duration
Also, in the C# sample we don't use parallel mode (https://www.doubango.org/SDKs/anpr/docs/Parallel_versus_sequential_processing.html).
It should be slightly slower but not that much. You can check
the C++ samples for how to use this option. For now you don't
need it, focus on your dev.
There is a sample application doing what I explained above: https://github.com/DoubangoTelecom/ultimateALPR-SDK/tree/master/samples/c%2B%2B/benchmark.
Edit "benchmark.bat"
to use rate equal to 0 then 1 and share both logs (dump in
files) with us. This will provide information about the decoder
and recogner speed on your machine.
On Windows it's very easy to use: https://github.com/DoubangoTelecom/ultimateALPR-SDK/tree/master/samples/c%2B%2B/benchmark#pre-built-binaries
To enable full GPU acceleration you have to replace
tensorflow.dll as explained at https://github.com/DoubangoTelecom/ultimateALPR-SDK/blob/master/samples/c%2B%2B/README.md#gpu-acceleration.
You need a computer with NVIDIA card + CUDA support.
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