modules/dnn/test/test_tf_importer.cpp

   1 // This file is part of OpenCV project.
   2 // It is subject to the license terms in the LICENSE file found in the top-level directory
   3 // of this distribution and at http://opencv.org/license.html.
   4
   5 // Copyright (C) 2016, Intel Corporation, all rights reserved.
   6 // Third party copyrights are property of their respective owners.
   7
   8 /*
   9 Test for Tensorflow models loading
  10 */
  11
  12 #include "test_precomp.hpp"
  13 #include "npy_blob.hpp"
  14
  15 namespace cvtest
  16 {
  17
  18 using namespace cv;
  19 using namespace cv::dnn;
  20
  21 template<typename TString>
  22 static std::string _tf(TString filename)
  23 {
  24     return (getOpenCVExtraDir() + "/dnn/") + filename;
  25 }
  26
  27 TEST(Test_TensorFlow, read_inception)
  28 {
  29     Net net;
  30     {
  31         const string model = findDataFile("dnn/tensorflow_inception_graph.pb", false);
  32         net = readNetFromTensorflow(model);
  33         ASSERT_FALSE(net.empty());
  34     }
  35
  36     Mat sample = imread(_tf("grace_hopper_227.png"));
  37     ASSERT_TRUE(!sample.empty());
  38     Mat input;
  39     resize(sample, input, Size(224, 224));
  40     input -= 128; // mean sub
  41
  42     Mat inputBlob = blobFromImage(input);
  43
  44     net.setInput(inputBlob, "input");
  45     Mat out = net.forward("softmax2");
  46
  47     std::cout << out.dims << std::endl;
  48 }
  49
  50 TEST(Test_TensorFlow, inception_accuracy)
  51 {
  52     Net net;
  53     {
  54         const string model = findDataFile("dnn/tensorflow_inception_graph.pb", false);
  55         net = readNetFromTensorflow(model);
  56         ASSERT_FALSE(net.empty());
  57     }
  58
  59     Mat sample = imread(_tf("grace_hopper_227.png"));
  60     ASSERT_TRUE(!sample.empty());
  61     resize(sample, sample, Size(224, 224));
  62     Mat inputBlob = blobFromImage(sample);
  63
  64     net.setInput(inputBlob, "input");
  65     Mat out = net.forward("softmax2");
  66
  67     Mat ref = blobFromNPY(_tf("tf_inception_prob.npy"));
  68
  69     normAssert(ref, out);
  70 }
  71
  72 static std::string path(const std::string& file)
  73 {
  74     return findDataFile("dnn/tensorflow/" + file, false);
  75 }
  76
  77 static void runTensorFlowNet(const std::string& prefix,
  78                              double l1 = 1e-5, double lInf = 1e-4)
  79 {
  80     std::string netPath = path(prefix + "_net.pb");
  81     std::string inpPath = path(prefix + "_in.npy");
  82     std::string outPath = path(prefix + "_out.npy");
  83
  84     Net net = readNetFromTensorflow(netPath);
  85
  86     cv::Mat input = blobFromNPY(inpPath);
  87     cv::Mat target = blobFromNPY(outPath);
  88
  89     net.setInput(input);
  90     cv::Mat output = net.forward();
  91     normAssert(target, output, "", l1, lInf);
  92 }
  93
  94 TEST(Test_TensorFlow, conv)
  95 {
  96     runTensorFlowNet("single_conv");
  97     runTensorFlowNet("atrous_conv2d_valid");
  98     runTensorFlowNet("atrous_conv2d_same");
  99     runTensorFlowNet("depthwise_conv2d");
 100 }
 101
 102 TEST(Test_TensorFlow, padding)
 103 {
 104     runTensorFlowNet("padding_same");
 105     runTensorFlowNet("padding_valid");
 106 }
 107
 108 TEST(Test_TensorFlow, eltwise_add_mul)
 109 {
 110     runTensorFlowNet("eltwise_add_mul");
 111 }
 112
 113 TEST(Test_TensorFlow, pad_and_concat)
 114 {
 115     runTensorFlowNet("pad_and_concat");
 116 }
 117
 118 TEST(Test_TensorFlow, batch_norm)
 119 {
 120     runTensorFlowNet("batch_norm");
 121     runTensorFlowNet("fused_batch_norm");
 122 }
 123
 124 TEST(Test_TensorFlow, pooling)
 125 {
 126     runTensorFlowNet("max_pool_even");
 127     runTensorFlowNet("max_pool_odd_valid");
 128     runTensorFlowNet("max_pool_odd_same");
 129 }
 130
 131 TEST(Test_TensorFlow, deconvolution)
 132 {
 133     runTensorFlowNet("deconvolution");
 134 }
 135
 136 TEST(Test_TensorFlow, matmul)
 137 {
 138     runTensorFlowNet("matmul");
 139 }
 140
 141 TEST(Test_TensorFlow, fp16)
 142 {
 143     const float l1 = 1e-3;
 144     const float lInf = 1e-2;
 145     runTensorFlowNet("fp16_single_conv", l1, lInf);
 146     runTensorFlowNet("fp16_deconvolution", l1, lInf);
 147     runTensorFlowNet("fp16_max_pool_odd_same", l1, lInf);
 148     runTensorFlowNet("fp16_padding_valid", l1, lInf);
 149     runTensorFlowNet("fp16_eltwise_add_mul", l1, lInf);
 150     runTensorFlowNet("fp16_max_pool_odd_valid", l1, lInf);
 151     runTensorFlowNet("fp16_pad_and_concat", l1, lInf);
 152     runTensorFlowNet("fp16_max_pool_even", l1, lInf);
 153     runTensorFlowNet("fp16_padding_same", l1, lInf);
 154 }
 155
 156 }