MLECO-929 Add Object Detection sample application using the public ArmNN C++ API

Change-Id: I14aa1b4b726212cffbefd6687203f93f936fa872
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>

1 files changed, 60 insertions, 0 deletions

diff --git a/samples/ObjectDetection/test/PipelineTest.cpp b/samples/ObjectDetection/test/PipelineTest.cpp
new file mode 100644
index 0000000000..289f44f5e9
--- /dev/null
+++ b/samples/ObjectDetection/test/PipelineTest.cpp
@@ -0,0 +1,60 @@
+//
+// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#include <catch.hpp>
+#include <opencv2/opencv.hpp>
+#include <NetworkPipeline.hpp>
+#include "Types.hpp"
+
+static std::string GetResourceFilePath(const std::string& filename)
+{
+    std::string testResources = TEST_RESOURCE_DIR;
+    if (0 == testResources.size())
+    {
+        throw "Invalid test resources directory provided";
+    }
+    else
+    {
+        if(testResources.back() != '/')
+        {
+            return testResources + "/" + filename;
+        }
+        else
+        {
+            return testResources + filename;
+        }
+    }
+}
+
+TEST_CASE("Test Network Execution SSD_MOBILE")
+{
+    std::string testResources = TEST_RESOURCE_DIR;
+    REQUIRE(testResources != "");
+    // Create the network options
+    od::ODPipelineOptions options;
+    options.m_ModelFilePath = GetResourceFilePath("detect.tflite");
+    options.m_ModelName = "SSD_MOBILE";
+    options.m_backends = {"CpuAcc", "CpuRef"};
+
+    od::IPipelinePtr objectDetectionPipeline = od::CreatePipeline(options);
+
+    od::InferenceResults results;
+    cv::Mat processed;
+    cv::Mat inputFrame = cv::imread(GetResourceFilePath("basketball1.png"), cv::IMREAD_COLOR);
+    cv::cvtColor(inputFrame, inputFrame, cv::COLOR_BGR2RGB);
+
+    objectDetectionPipeline->PreProcessing(inputFrame, processed);
+
+    CHECK(processed.type() == CV_8UC3);
+    CHECK(processed.cols == 300);
+    CHECK(processed.rows == 300);
+
+    objectDetectionPipeline->Inference(processed, results);
+    objectDetectionPipeline->PostProcessing(results,
+                                            [](od::DetectedObjects detects) -> void {
+                                                CHECK(detects.size() == 2);
+                                                CHECK(detects[0].GetLabel() == "0");
+                                            });
+
+}