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 "armnnTfLiteParser/ITfLiteParser.hpp"
8
9 using namespace armnnTfLiteParser;
10
main(int argc,char * argv[])11 int main(int argc, char* argv[])
12 {
13 int retVal = EXIT_FAILURE;
14 try
15 {
16 // Coverity fix: The following code may throw an exception of type std::length_error.
17 // The model we are using incorrectly classifies the images
18 // But can still be used for benchmarking the layers.
19 std::vector<ImageSet> imageSet =
20 {
21 {"Dog.jpg", 789},
22 {"Cat.jpg", 592},
23 {"shark.jpg", 755},
24 };
25
26 armnn::TensorShape inputTensorShape({ 1, 128, 128, 3 });
27
28 using DataType = uint8_t;
29 using DatabaseType = ImagePreprocessor<DataType>;
30 using ParserType = armnnTfLiteParser::ITfLiteParser;
31 using ModelType = InferenceModel<ParserType, DataType>;
32
33 // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
34 retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType,
35 ParserType>(
36 argc, argv,
37 "mobilenet_v1_0.25_128_quant.tflite", // model name
38 true, // model is binary
39 "input", // input tensor name
40 "MobilenetV1/Predictions/Reshape_1", // output tensor name
41 { 0, 1, 2 }, // test images to test with as above
42 [&imageSet](const char* dataDir, const ModelType &) {
43 // we need to get the input quantization parameters from
44 // the parsed model
45 return DatabaseType(
46 dataDir,
47 128,
48 128,
49 imageSet,
50 1,
51 {{0, 0, 0}},
52 {{1, 1, 1}},
53 DatabaseType::DataFormat::NCHW,
54 1);
55 },
56 &inputTensorShape);
57 }
58 catch (const std::exception& e)
59 {
60 // Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
61 // exception of type std::length_error.
62 // Using stderr instead in this context as there is no point in nesting try-catch blocks here.
63 std::cerr << "WARNING: " << *argv << ": An error has occurred when running "
64 "the classifier inference tests: " << e.what() << std::endl;
65 }
66 return retVal;
67 }
68