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Open Source Computer Vision Library
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78 lines
2.5 KiB
78 lines
2.5 KiB
// 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 "test_precomp.hpp" |
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namespace opencv_test { namespace { |
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TEST(blobFromImage_4ch, Regression) |
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{ |
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Mat ch[4]; |
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for(int i = 0; i < 4; i++) |
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ch[i] = Mat::ones(10, 10, CV_8U)*i; |
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Mat img; |
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merge(ch, 4, img); |
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Mat blob = dnn::blobFromImage(img, 1., Size(), Scalar(), false, false); |
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for(int i = 0; i < 4; i++) |
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{ |
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ch[i] = Mat(img.rows, img.cols, CV_32F, blob.ptr(0, i)); |
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ASSERT_DOUBLE_EQ(cvtest::norm(ch[i], cv::NORM_INF), i); |
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} |
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} |
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TEST(blobFromImage, allocated) |
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{ |
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int size[] = {1, 3, 4, 5}; |
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Mat img(size[2], size[3], CV_32FC(size[1])); |
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Mat blob(4, size, CV_32F); |
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void* blobData = blob.data; |
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dnn::blobFromImage(img, blob, 1.0 / 255, Size(), Scalar(), false, false); |
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ASSERT_EQ(blobData, blob.data); |
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} |
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TEST(imagesFromBlob, Regression) |
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{ |
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int nbOfImages = 8; |
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std::vector<cv::Mat> inputImgs(nbOfImages); |
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for (int i = 0; i < nbOfImages; i++) |
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{ |
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inputImgs[i] = cv::Mat::ones(100, 100, CV_32FC3); |
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cv::randu(inputImgs[i], cv::Scalar::all(0), cv::Scalar::all(1)); |
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} |
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cv::Mat blob = cv::dnn::blobFromImages(inputImgs, 1., cv::Size(), cv::Scalar(), false, false); |
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std::vector<cv::Mat> outputImgs; |
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cv::dnn::imagesFromBlob(blob, outputImgs); |
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for (int i = 0; i < nbOfImages; i++) |
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{ |
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ASSERT_EQ(cv::countNonZero(inputImgs[i] != outputImgs[i]), 0); |
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} |
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} |
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TEST(readNet, Regression) |
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{ |
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Net net = readNet(findDataFile("dnn/squeezenet_v1.1.prototxt", false), |
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findDataFile("dnn/squeezenet_v1.1.caffemodel", false)); |
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EXPECT_FALSE(net.empty()); |
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net = readNet(findDataFile("dnn/opencv_face_detector.caffemodel", false), |
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findDataFile("dnn/opencv_face_detector.prototxt", false)); |
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EXPECT_FALSE(net.empty()); |
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net = readNet(findDataFile("dnn/openface_nn4.small2.v1.t7", false)); |
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EXPECT_FALSE(net.empty()); |
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net = readNet(findDataFile("dnn/tiny-yolo-voc.cfg", false), |
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findDataFile("dnn/tiny-yolo-voc.weights", false)); |
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EXPECT_FALSE(net.empty()); |
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net = readNet(findDataFile("dnn/ssd_mobilenet_v1_coco.pbtxt", false), |
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findDataFile("dnn/ssd_mobilenet_v1_coco.pb", false)); |
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EXPECT_FALSE(net.empty()); |
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} |
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}} // namespace
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