| // |
| // 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; |
| } |