Release 18.08
diff --git a/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp b/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp
new file mode 100644
index 0000000..7383ab3
--- /dev/null
+++ b/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp
@@ -0,0 +1,84 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// See LICENSE file in the project root for full license information.
+//
+#include "../InferenceTest.hpp"
+#include "../ImagePreprocessor.hpp"
+#include "armnnTfLiteParser/ITfLiteParser.hpp"
+
+using namespace armnnTfLiteParser;
+
+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", 209},
+ // top five predictions in tensorflow:
+ // -----------------------------------
+ // 209:Labrador retriever 0.949995
+ // 160:Rhodesian ridgeback 0.0270182
+ // 208:golden retriever 0.0192866
+ // 853:tennis ball 0.000470382
+ // 239:Greater Swiss Mountain dog 0.000464451
+ {"Cat.jpg", 283},
+ // top five predictions in tensorflow:
+ // -----------------------------------
+ // 283:tiger cat 0.579016
+ // 286:Egyptian cat 0.319676
+ // 282:tabby, tabby cat 0.0873346
+ // 288:lynx, catamount 0.011163
+ // 289:leopard, Panthera pardus 0.000856755
+ {"shark.jpg", 3},
+ // top five predictions in tensorflow:
+ // -----------------------------------
+ // 3:great white shark, white shark, ... 0.996926
+ // 4:tiger shark, Galeocerdo cuvieri 0.00270528
+ // 149:killer whale, killer, orca, ... 0.000121848
+ // 395:sturgeon 7.78977e-05
+ // 5:hammerhead, hammerhead shark 6.44127e-055
+ };
+
+ armnn::TensorShape inputTensorShape({ 1, 224, 224, 3 });
+
+ using DataType = uint8_t;
+ using DatabaseType = ImagePreprocessor<DataType>;
+ using ParserType = armnnTfLiteParser::ITfLiteParser;
+ using ModelType = InferenceModel<ParserType, DataType>;
+
+ // Coverity fix: ClassifierInferenceTestMain() may throw uncaught exceptions.
+ retVal = armnn::test::ClassifierInferenceTestMain<DatabaseType,
+ ParserType>(
+ argc, argv,
+ "mobilenet_v1_1.0_224_quant.tflite", // model name
+ true, // model is binary
+ "input", // input tensor name
+ "MobilenetV1/Predictions/Reshape_1", // output tensor name
+ { 0, 1, 2 }, // test images to test with as above
+ [&imageSet](const char* dataDir, const ModelType & model) {
+ // we need to get the input quantization parameters from
+ // the parsed model
+ auto inputBinding = model.GetInputBindingInfo();
+ return DatabaseType(
+ dataDir,
+ 224,
+ 224,
+ imageSet,
+ inputBinding.second.GetQuantizationScale(),
+ inputBinding.second.GetQuantizationOffset());
+ },
+ &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: " << *argv << ": An error has occurred when running "
+ "the classifier inference tests: " << e.what() << std::endl;
+ }
+ return retVal;
+}