blob: f08a09a546ab15163d51d28201a1c658dfd9bbac [file] [log] [blame]
/*
* 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);
}
}