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Merge pull request #9313 from dkurt:dnn_perf_test
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@@ -8,20 +8,7 @@ according to specific device and evaluate it with a quite good efficiency.
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An official website of the Halide project: http://halide-lang.org/.
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## Efficiency comparison
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Measured on Intel® Core™ i7-6700K CPU @ 4.00GHz x 8.
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Single image forward pass (in milliseconds):
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| Architecture | MKL backend | Halide backend | Speed Up ratio |
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|-----------------:|------------:|---------------:|---------------:|
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| AlexNet | 16.55 | 22.38 | x0.73 |
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| ResNet-50 | 63.69 | 73.91 | x0.86 |
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| SqueezeNet v1.1 | 10.11 | 8.21 | x1.23 |
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| Inception-5h | 35.38 | 37.06 | x0.95 |
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| ENet @ 3x512x256 | 82.26 | 41.21 | x1.99 |
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Scheduling directives might be found @ [opencv_extra/testdata/dnn](https://github.com/opencv/opencv_extra/tree/master/testdata/dnn).
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An up to date efficiency comparison: https://github.com/opencv/opencv/wiki/DNN-Efficiency
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## Requirements
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### LLVM compiler
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@@ -81,6 +68,8 @@ MSBuild.exe /m:4 /t:Build /p:Configuration=Release .\\ALL_BUILD.vcxproj
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## Build OpenCV with Halide backend
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When you build OpenCV add the following configuration flags:
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- `ENABLE_CXX11` - enable C++11 standard
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- `WITH_HALIDE` - enable Halide linkage
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- `HALIDE_ROOT_DIR` - path to Halide build directory
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