MLCE-103: MDK changes for running multiple inferences qasymm8
Change-Id: I34e8e0736e133ffb5f931ce3b5f5bfa4e2c975c2
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
diff --git a/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp b/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp
index 36b1d14..220964d 100644
--- a/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp
+++ b/tests/TfLiteMobilenetQuantized-Armnn/TfLiteMobilenetQuantized-Armnn.cpp
@@ -6,41 +6,88 @@
#include "../ImagePreprocessor.hpp"
#include "armnnTfLiteParser/ITfLiteParser.hpp"
+#include "boost/program_options.hpp"
+#include <fstream>
+
using namespace armnnTfLiteParser;
+std::vector<ImageSet> ParseDataset(const std::string& filename)
+{
+ std::ifstream read(filename);
+ std::vector<ImageSet> imageSet;
+ if (read.is_open())
+ {
+ // Get the images and the correct corresponding label from the given file
+ for (std::string line; std::getline(read, line);)
+ {
+ stringstream ss(line);
+ std::string image_name;
+ std::string label;
+ getline(ss, image_name, ' ');
+ getline(ss, label, ' ');
+ imageSet.push_back(ImageSet(image_name, std::stoi(label)));
+ }
+ }
+ else
+ {
+ // Use the default images
+ imageSet.push_back(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
+ imageSet.push_back(ImageSet("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
+ imageSet.push_back(ImageSet("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
+ };
+ return imageSet;
+}
+
+std::string GetLabelsFilenameFromOptions(int argc, char* argv[])
+{
+ namespace po = boost::program_options;
+ po::options_description desc("Validation Options");
+ std::string fn("");
+ desc.add_options()
+ ("labels", po::value<std::string>(&fn), "Filename of a text file where in each line contains an image "
+ "filename and the correct label the network should predict when fed that image");
+ po::variables_map vm;
+ po::parsed_options parsed = po::command_line_parser(argc, argv).options(desc).allow_unregistered().run();
+ po::store(parsed, vm);
+ if (vm.count("labels"))
+ {
+ fn = vm["labels"].as<std::string>();
+ }
+ return fn;
+}
+
+
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
- };
+ const std::string labels_file = GetLabelsFilenameFromOptions(argc,argv);
+ std::vector<ImageSet> imageSet = ParseDataset(labels_file);
+ std::vector<unsigned int> indices(imageSet.size());
+ std::generate(indices.begin(), indices.end(), [n = 0] () mutable { return n++; });
armnn::TensorShape inputTensorShape({ 1, 224, 224, 3 });
@@ -57,7 +104,7 @@
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
+ indices, // vector of indices to select which images to validate
[&imageSet](const char* dataDir, const ModelType & model) {
// we need to get the input quantization parameters from
// the parsed model