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79 lines
3.3 KiB
79 lines
3.3 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 "armnnTfParser/ITfParser.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", 209},
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// Top five predictions in tensorflow:
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// -----------------------------------
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// 209:Labrador retriever 0.46392533
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// 160:Rhodesian ridgeback 0.29911423
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// 208:golden retriever 0.108059585
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// 169:redbone 0.033753652
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// 274:dingo, warrigal, warragal, ... 0.01232666
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{"Cat.jpg", 283},
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// Top five predictions in tensorflow:
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// -----------------------------------
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// 283:tiger cat 0.6508582
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// 286:Egyptian cat 0.2604343
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// 282:tabby, tabby cat 0.028786005
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// 288:lynx, catamount 0.020673484
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// 40:common iguana, iguana, ... 0.0080499435
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{"shark.jpg", 3},
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// Top five predictions in tensorflow:
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// -----------------------------------
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// 3:great white shark, white shark, ... 0.96672016
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// 4:tiger shark, Galeocerdo cuvieri 0.028302953
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// 149:killer whale, killer, orca, ... 0.0020228163
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// 5:hammerhead, hammerhead shark 0.0017547971
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// 150:dugong, Dugong dugon 0.0003968083
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};
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armnn::TensorShape inputTensorShape({ 1, 224, 224, 3 });
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using DataType = float;
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using DatabaseType = ImagePreprocessor<float>;
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using ParserType = armnnTfParser::ITfParser;
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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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"mobilenet_v1_1.0_224_frozen.pb", // model name
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true, // model is binary
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"input", "MobilenetV1/Predictions/Reshape_1", // 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 a 224x224x3 NHWC float tensor 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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},
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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: TfMobileNet-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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