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Faster implementation of blobFromImages for cpu nchw output #26127 Faster implementation of blobFromImage and blobFromImages for HWC cv::Mat images -> NCHW cv::Mat case Running time on my pc in ms: **blobFromImage** ``` image size old new speed-up 32x32x3 0.008 0.002 4.0x 64x64x3 0.021 0.009 2.3x 128x128x3 0.164 0.037 4.4x 256x256x3 0.728 0.158 4.6x 512x512x3 3.310 0.628 5.2x 1024x1024x3 14.503 3.124 4.6x 2048x2048x3 61.647 28.049 2.2x ``` **blobFromImages** ``` image size old new speed-up 16x32x32x3 0.122 0.041 3.0x 16x64x64x3 0.790 0.165 4.8x 16x128x128x3 3.313 0.652 5.1x 16x256x256x3 13.495 3.127 4.3x 16x512x512x3 58.795 28.127 2.1x 16x1024x1024x3 251.135 121.955 2.1x 16x2048x2048x3 1023.570 487.188 2.1x ``` ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [x] I agree to contribute to the project under Apache 2 License. - [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [x] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [x] The feature is well documented and sample code can be built with the project CMake
67 lines
2.0 KiB
C++
67 lines
2.0 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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//
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// Copyright (C) 2017, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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#include "perf_precomp.hpp"
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namespace opencv_test {
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using Utils_blobFromImage = TestBaseWithParam<std::vector<int>>;
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PERF_TEST_P_(Utils_blobFromImage, HWC_TO_NCHW) {
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std::vector<int> input_shape = GetParam();
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Mat input(input_shape, CV_32FC3);
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randu(input, -10.0f, 10.f);
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TEST_CYCLE() {
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Mat blob = blobFromImage(input);
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}
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SANITY_CHECK_NOTHING();
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}
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INSTANTIATE_TEST_CASE_P(/**/, Utils_blobFromImage,
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Values(std::vector<int>{ 32, 32},
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std::vector<int>{ 64, 64},
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std::vector<int>{ 128, 128},
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std::vector<int>{ 256, 256},
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std::vector<int>{ 512, 512},
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std::vector<int>{1024, 1024},
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std::vector<int>{2048, 2048})
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);
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using Utils_blobFromImages = TestBaseWithParam<std::vector<int>>;
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PERF_TEST_P_(Utils_blobFromImages, HWC_TO_NCHW) {
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std::vector<int> input_shape = GetParam();
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int batch = input_shape.front();
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std::vector<int> input_shape_no_batch(input_shape.begin()+1, input_shape.end());
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std::vector<Mat> inputs;
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for (int i = 0; i < batch; i++) {
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Mat input(input_shape_no_batch, CV_32FC3);
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randu(input, -10.0f, 10.f);
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inputs.push_back(input);
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}
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TEST_CYCLE() {
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Mat blobs = blobFromImages(inputs);
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}
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SANITY_CHECK_NOTHING();
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}
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INSTANTIATE_TEST_CASE_P(/**/, Utils_blobFromImages,
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Values(std::vector<int>{16, 32, 32},
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std::vector<int>{16, 64, 64},
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std::vector<int>{16, 128, 128},
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std::vector<int>{16, 256, 256},
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std::vector<int>{16, 512, 512},
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std::vector<int>{16, 1024, 1024},
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std::vector<int>{16, 2048, 2048})
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);
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}
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