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/*
* Copyright (c) 2018 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 "ImageClassifier.h"
#include <iostream>
#include <boost/filesystem.hpp>
#include <opencv2/opencv.hpp>
namespace fs = boost::filesystem;
int main(const int argc, char **argv)
{
const std::string MODEL_FILE = "tensorflow_inception_graph.tflite";
const std::string LABEL_FILE = "imagenet_comp_graph_label_strings.txt";
const std::string INPUT_NAME = "input";
const std::string OUTPUT_NAME = "output";
const int INPUT_SIZE = 224;
const int IMAGE_MEAN = 117;
const int IMAGE_STD = 1;
const int OUTPUT_SIZE = 1008;
const int FRAME_WIDTH = 640;
const int FRAME_HEIGHT = 480;
bool use_nnapi = false;
bool debug_mode = false;
if (std::getenv("USE_NNAPI") != nullptr)
{
use_nnapi = true;
}
if (std::getenv("DEBUG_MODE") != nullptr)
{
debug_mode = true;
}
std::cout << "USE_NNAPI : " << use_nnapi << std::endl;
std::cout << "DEBUG_MODE : " << debug_mode << std::endl;
std::cout << "Model : " << MODEL_FILE << std::endl;
std::cout << "Label : " << LABEL_FILE << std::endl;
if (!fs::exists(MODEL_FILE))
{
std::cerr << "model file not found: " << MODEL_FILE << std::endl;
exit(1);
}
if (!fs::exists(LABEL_FILE))
{
std::cerr << "label file not found: " << LABEL_FILE << std::endl;
exit(1);
}
// Create ImageClassifier
std::unique_ptr<ImageClassifier> classifier(
new ImageClassifier(MODEL_FILE, LABEL_FILE, INPUT_SIZE, IMAGE_MEAN, IMAGE_STD, INPUT_NAME,
OUTPUT_NAME, use_nnapi));
// Cam setting
cv::VideoCapture cap(0);
cv::Mat frame;
// Initialize camera
cap.set(CV_CAP_PROP_FRAME_WIDTH, FRAME_WIDTH);
cap.set(CV_CAP_PROP_FRAME_HEIGHT, FRAME_HEIGHT);
cap.set(CV_CAP_PROP_FPS, 5);
std::vector<Recognition> results;
clock_t begin, end;
while (cap.isOpened())
{
// Get image data
if (!cap.read(frame))
{
std::cout << "Frame is null..." << std::endl;
break;
}
if (debug_mode)
{
begin = clock();
}
// Recognize image
results = classifier->recognizeImage(frame);
if (debug_mode)
{
end = clock();
}
// Show result data
std::cout << std::endl;
if (results.size() > 0)
{
for (int i = 0; i < results.size(); ++i)
{
std::cout << results[i].title << ": " << results[i].confidence << std::endl;
}
}
else
{
std::cout << "." << std::endl;
}
if (debug_mode)
{
std::cout << "Frame: " << FRAME_WIDTH << "x" << FRAME_HEIGHT << std::endl;
std::cout << "Crop: " << INPUT_SIZE << "x" << INPUT_SIZE << std::endl;
std::cout << "Inference time(ms): " << ((end - begin) / (CLOCKS_PER_SEC / 1000)) << std::endl;
}
}
cap.release();
return 0;
}
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