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79 lines
2.5 KiB
C++
79 lines
2.5 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 "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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