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/**
* Copyright (c) 2022 Samsung Electronics Co., Ltd All Rights Reserved
*
* 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 <gtest/gtest.h>
#include <string>
#include <ImageHelper.h>
#include "test_inference_helper.hpp"
#define FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH \
TEST_RES_PATH \
"/open_model_zoo/models/FD/tflite/fd_mobilenet_v1_ssd_postop_300x300.tflite"
#define FD_TFLITE_WEIGHT_BLAZEFACE_128_PATH \
TEST_RES_PATH \
"/open_model_zoo/models/FD/tflite/fd_blazeface_front_128x128.tflite"
#define IMG_FACE \
TEST_RES_PATH \
"/res/inference/images/faceDetection.jpg"
void _face_detected_cb(mv_source_h source, const int number_of_faces, const float *confidences,
const mv_rectangle_s *locations, void *user_data)
{
EXPECT_GT(number_of_faces, 0);
}
class TestFaceDetectionTflite : public TestInference
{
public:
void inferenceFace()
{
TestInference::ConfigureInference();
ASSERT_EQ(MediaVision::Common::ImageHelper::loadImageToSource(IMG_FACE, mv_source), MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_inference_face_detect(mv_source, infer, _face_detected_cb, NULL), MEDIA_VISION_ERROR_NONE);
}
};
TEST_P(TestFaceDetectionTflite, MobilenetV1_SSD)
{
engine_config_hosted_tflite_model(engine_cfg, FD_TFLITE_WEIGHT_MOBILENET_V1_SSD_300_PATH, NULL, _use_json_parser,
_target_device_type);
if (!_use_json_parser) {
const char *inputNodeName = "normalized_input_image_tensor";
const char *outputNodeName[] = { "TFLite_Detection_PostProcess", "TFLite_Detection_PostProcess:1",
"TFLite_Detection_PostProcess:2", "TFLite_Detection_PostProcess:3" };
ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_MEAN_VALUE, 127.5),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_MODEL_STD_VALUE, 127.5),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_double_attribute(engine_cfg, MV_INFERENCE_CONFIDENCE_THRESHOLD, 0.3),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_WIDTH, 300),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_HEIGHT, 300),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_int_attribute(engine_cfg, MV_INFERENCE_INPUT_TENSOR_CHANNELS, 3),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_string_attribute(engine_cfg, MV_INFERENCE_INPUT_NODE_NAME, inputNodeName),
MEDIA_VISION_ERROR_NONE);
ASSERT_EQ(mv_engine_config_set_array_string_attribute(engine_cfg, MV_INFERENCE_OUTPUT_NODE_NAMES,
outputNodeName, 4),
MEDIA_VISION_ERROR_NONE);
}
inferenceFace();
}
INSTANTIATE_TEST_CASE_P(Prefix, TestFaceDetectionTflite,
::testing::Values(ParamTypes(false, MV_INFERENCE_TARGET_DEVICE_CPU),
ParamTypes(true, MV_INFERENCE_TARGET_DEVICE_CPU)));
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