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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "../InferenceTest.hpp"
#include "../ImagePreprocessor.hpp"
#include "armnnTfParser/ITfParser.hpp"
int main(int argc, char* argv[])
{
int retVal = EXIT_FAILURE;
try
{
// Coverity fix: The following code may throw an exception of type std::length_error.
std::vector<ImageSet> imageSet =
{
{"Dog.jpg", 209},
// Top five predictions in tensorflow:
// -----------------------------------
// 209:Labrador retriever 0.46392533
// 160:Rhodesian ridgeback 0.29911423
// 208:golden retriever 0.108059585
// 169:redbone 0.033753652
// 274:dingo, warrigal, warragal, ... 0.01232666
{"Cat.jpg", 283},
// Top five predictions in tensorflow:
// -----------------------------------
// 283:tiger cat 0.6508582
// 286:Egyptian cat 0.2604343
// 282:tabby, tabby cat 0.028786005
// 288:lynx, catamount 0.020673484
// 40:common iguana, iguana, ... 0.0080499435
{"shark.jpg", 3},
// Top five predictions in tensorflow:
// -----------------------------------
// 3:great white shark, white shark, ... 0.96672016
// 4:tiger shark, Galeocerdo cuvieri 0.028302953
// 149:killer whale, killer, orca, ... 0.0020228163
// 5:hammerhead, hammerhead shark 0.0017547971
// 150:dugong, Dugong dugon 0.0003968083
};
armnn::TensorShape inputTensorShape({ 1, 224, 224, 3 });
using DataType = float;
using DatabaseType = ImagePreprocessor<float>;
using ParserType = armnnTfParser::ITfParser;
using ModelType = InferenceModel<ParserType, DataType>;
// Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
argc, argv,
"mobilenet_v1_1.0_224_frozen.pb", // model name
true, // model is binary
"input", "MobilenetV1/Predictions/Reshape_1", // input and output tensor names
{ 0, 1, 2 }, // test images to test with as above
[&imageSet](const char* dataDir, const ModelType&) {
// This creates a 224x224x3 NHWC float tensor to pass to Armnn
return DatabaseType(
dataDir,
224,
224,
imageSet);
},
&inputTensorShape);
}
catch (const std::exception& e)
{
// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
// exception of type std::length_error.
// Using stderr instead in this context as there is no point in nesting try-catch blocks here.
std::cerr << "WARNING: TfMobileNet-Armnn: An error has occurred when running "
"the classifier inference tests: " << e.what() << std::endl;
}
return retVal;
}
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