Opensource ML embedded evaluation kit
Change-Id: I12e807f19f5cacad7cef82572b6dd48252fd61fd
diff --git a/tests/common/ClassifierTests.cc b/tests/common/ClassifierTests.cc
new file mode 100644
index 0000000..f08a09a
--- /dev/null
+++ b/tests/common/ClassifierTests.cc
@@ -0,0 +1,76 @@
+/*
+ * Copyright (c) 2021 Arm Limited. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "Classifier.hpp"
+
+#include <catch.hpp>
+
+TEST_CASE("Common classifier")
+{
+ SECTION("Test invalid classifier")
+ {
+ TfLiteTensor* outputTens = nullptr;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::Classifier classifier;
+ REQUIRE(!classifier.GetClassificationResults(outputTens, resultVec, {}, 5));
+ }
+
+ SECTION("Test valid classifier UINT8")
+ {
+ const int dimArray[] = {1, 1001};
+ std::vector <std::string> labels(1001);
+ std::vector <uint8_t> outputVec(1001);
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+ std::vector <arm::app::ClassificationResult> resultVec;
+ arm::app::Classifier classifier;
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 5));
+ REQUIRE(5 == resultVec.size());
+ }
+
+ SECTION("Get classification results")
+ {
+ const int dimArray[] = {1, 1001};
+ std::vector <std::string> labels(1001);
+ std::vector<uint8_t> outputVec(1001, static_cast<uint8_t>(5));
+ TfLiteIntArray* dims= tflite::testing::IntArrayFromInts(dimArray);
+ TfLiteTensor tfTensor = tflite::testing::CreateQuantizedTensor(
+ outputVec.data(), dims, 1, 0, "test");
+ TfLiteTensor* outputTensor = &tfTensor;
+
+ std::vector <arm::app::ClassificationResult> resultVec;
+
+ /* Set the top five results. */
+ std::vector<std::pair<uint32_t, uint8_t>> selectedResults {
+ {0, 8}, {20, 7}, {10, 7}, {15, 9}, {1000, 10}};
+
+ for (size_t i = 0; i < selectedResults.size(); ++i) {
+ outputVec[selectedResults[i].first] = selectedResults[i].second;
+ }
+
+ arm::app::Classifier classifier;
+ REQUIRE(classifier.GetClassificationResults(outputTensor, resultVec, labels, 5));
+ REQUIRE(5 == resultVec.size());
+
+ REQUIRE(resultVec[0].m_labelIdx == 1000);
+ REQUIRE(resultVec[1].m_labelIdx == 15);
+ REQUIRE(resultVec[2].m_labelIdx == 0);
+ REQUIRE(resultVec[3].m_labelIdx == 20);
+ REQUIRE(resultVec[4].m_labelIdx == 10);
+ }
+}