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59 lines
2.5 KiB
59 lines
2.5 KiB
// |
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// Copyright © 2017 Arm Ltd. All rights reserved. |
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// SPDX-License-Identifier: MIT |
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// |
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#include "../InferenceTest.hpp" |
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#include "../ImagePreprocessor.hpp" |
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#include "armnnOnnxParser/IOnnxParser.hpp" |
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int main(int argc, char* argv[]) |
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{ |
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int retVal = EXIT_FAILURE; |
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try |
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{ |
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// Coverity fix: The following code may throw an exception of type std::length_error. |
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std::vector<ImageSet> imageSet = |
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{ |
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{"Dog.jpg", 208}, |
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{"Cat.jpg", 281}, |
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{"shark.jpg", 2}, |
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}; |
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armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 }); |
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using DataType = float; |
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using DatabaseType = ImagePreprocessor<float>; |
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using ParserType = armnnOnnxParser::IOnnxParser; |
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using ModelType = InferenceModel<ParserType, DataType>; |
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// Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions. |
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retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>( |
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argc, argv, |
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"mobilenetv2-1.0.onnx", // model name |
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true, // model is binary |
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"data", "mobilenetv20_output_flatten0_reshape0", // input and output tensor names |
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{ 0, 1, 2 }, // test images to test with as above |
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[&imageSet](const char* dataDir, const ModelType&) { |
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// This creates create a 1, 3, 224, 224 normalized input with mean and stddev to pass to Armnn |
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return DatabaseType( |
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dataDir, |
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224, |
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224, |
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imageSet, |
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255.0, // scale |
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{{0.485f, 0.456f, 0.406f}}, // mean |
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{{0.229f, 0.224f, 0.225f}}, // stddev |
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DatabaseType::DataFormat::NCHW); // format |
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}, |
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&inputTensorShape); |
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} |
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catch (const std::exception& e) |
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{ |
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// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an |
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// exception of type std::length_error. |
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// Using stderr instead in this context as there is no point in nesting try-catch blocks here. |
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std::cerr << "WARNING: OnnxMobileNet-Armnn: An error has occurred when running " |
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"the classifier inference tests: " << e.what() << std::endl; |
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} |
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return retVal; |
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}
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