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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "../InferenceTest.hpp"
#include "../ImagePreprocessor.hpp"
#include "armnnOnnxParser/IOnnxParser.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", 208},
{"Cat.jpg", 281},
{"shark.jpg", 2},
};
armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
using DataType = float;
using DatabaseType = ImagePreprocessor<float>;
using ParserType = armnnOnnxParser::IOnnxParser;
using ModelType = InferenceModel<ParserType, DataType>;
// Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
argc, argv,
"mobilenetv2-1.0.onnx", // model name
true, // model is binary
"data", "mobilenetv20_output_flatten0_reshape0", // input and output tensor names
{ 0, 1, 2 }, // test images to test with as above
[&imageSet](const char* dataDir, const ModelType&) {
// This creates create a 1, 3, 224, 224 normalized input with mean and stddev to pass to Armnn
return DatabaseType(
dataDir,
224,
224,
imageSet,
255.0, // scale
{{0.485f, 0.456f, 0.406f}}, // mean
{{0.229f, 0.224f, 0.225f}}, // stddev
DatabaseType::DataFormat::NCHW); // format
},
&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: OnnxMobileNet-Armnn: An error has occurred when running "
"the classifier inference tests: " << e.what() << std::endl;
}
return retVal;
}
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