1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 #include "../InferenceTest.hpp"
6 #include "../ImagePreprocessor.hpp"
7 #include "armnnOnnxParser/IOnnxParser.hpp"
8
main(int argc,char * argv[])9 int main(int argc, char* argv[])
10 {
11 int retVal = EXIT_FAILURE;
12 try
13 {
14 // Coverity fix: The following code may throw an exception of type std::length_error.
15 std::vector<ImageSet> imageSet =
16 {
17 {"Dog.jpg", 208},
18 {"Cat.jpg", 281},
19 {"shark.jpg", 2},
20 };
21
22 armnn::TensorShape inputTensorShape({ 1, 3, 224, 224 });
23
24 using DataType = float;
25 using DatabaseType = ImagePreprocessor<float>;
26 using ParserType = armnnOnnxParser::IOnnxParser;
27 using ModelType = InferenceModel<ParserType, DataType>;
28
29 // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
30 retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType, ParserType>(
31 argc, argv,
32 "mobilenetv2-1.0.onnx", // model name
33 true, // model is binary
34 "data", "mobilenetv20_output_flatten0_reshape0", // input and output tensor names
35 { 0, 1, 2 }, // test images to test with as above
36 [&imageSet](const char* dataDir, const ModelType&) {
37 // This creates create a 1, 3, 224, 224 normalized input with mean and stddev to pass to Armnn
38 return DatabaseType(
39 dataDir,
40 224,
41 224,
42 imageSet,
43 255.0, // scale
44 {{0.485f, 0.456f, 0.406f}}, // mean
45 {{0.229f, 0.224f, 0.225f}}, // stddev
46 DatabaseType::DataFormat::NCHW); // format
47 },
48 &inputTensorShape);
49 }
50 catch (const std::exception& e)
51 {
52 // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
53 // exception of type std::length_error.
54 // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
55 std::cerr << "WARNING: OnnxMobileNet-Armnn: An error has occurred when running "
56 "the classifier inference tests: " << e.what() << std::endl;
57 }
58 return retVal;
59 }
60