visioncpp/examples/simple_conv.cpp at License-update · codeplaysoftware/visioncpp · GitHub

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// This file is part of VisionCpp, a lightweight C++ template library

// for computer vision and image processing.

// Contact: visioncpp@codeplay.com

// 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.

/// \file simple_conv.cc

///

/// ---------Example---------

/// Simple Convolution

///

/// \brief This example implements a simple separable convolution using mean

/// filter

///

#ifdef NOT_COMPATIBLE_WITH_COMPUTECPP_050

// include OpenCV for camera display

#include <opencv2/opencv.hpp>

// include VisionCpp

#include <visioncpp.hpp>

// main program

int main(int argc, char** argv) {

// open video or camera

cv::VideoCapture cap;

if (argc == 1) {

cap.open(0);

std::cout << "To use video" << std::endl;

std::cout << "example>: ./example path/to/video.avi" << std::endl;

} else if (argc > 1) {

cap.open(argv[1]);

}

// check if we succeeded

if (!cap.isOpened()) {

std::cout << "Opening Camera/Video Failed." << std::endl;

return -1;

}

// set fixed resolution on the camera

constexpr size_t COLS = 640;

constexpr size_t ROWS = 480;

// where VisionCpp will run?

auto dev = visioncpp::make_device<visioncpp::backend::sycl,

visioncpp::device::cpu>();

std::shared_ptr<unsigned char> vc_buffer(

new unsigned char[COLS * ROWS * 3],

[](unsigned char* dataMem) { delete[] dataMem; });

// creating a 1x9 filter mean filter

float filter_array[9] = {1.0f / 9.0f, 1.0f / 9.0f, 1.0f / 9.0f,

1.0f / 9.0f, 1.0f / 9.0f, 1.0f / 9.0f,

1.0f / 9.0f, 1.0f / 9.0f, 1.0f / 9.0f};

// create opencv mat

cv::Mat frame;

cv::Mat output;

for (;;) {

// read frame

cap.read(frame);

// check if image was loaded

if (!frame.data) {

break;

}

// resize image to the desirable size

cv::resize(frame, frame, cv::Size(COLS, ROWS), 0, 0, cv::INTER_CUBIC);

// column-wise filter for separable convolution

auto filter_col =

visioncpp::terminal<float, 9, 1, visioncpp::memory_type::Buffer2D,

visioncpp::scope::Constant>(filter_array);

// row wise filter for separable convolution

auto filter_row =

visioncpp::terminal<float, 1, 9, visioncpp::memory_type::Buffer2D,

visioncpp::scope::Constant>(filter_array);

// wrap OpenCV frame data in our leaf node

auto data =

visioncpp::terminal<visioncpp::pixel::U8C3, COLS, ROWS,

visioncpp::memory_type::Buffer2D>(frame.data);

auto data_out =

visioncpp::terminal<visioncpp::pixel::U8C3, COLS, ROWS,

visioncpp::memory_type::Buffer2D>(vc_buffer.get());

auto node2 = visioncpp::neighbour_operation<visioncpp::OP_SepFilterCol>(

data, filter_col);

auto node3 = visioncpp::neighbour_operation<visioncpp::OP_SepFilterRow>(

node2, filter_row);

// writing back to Mat

auto k = visioncpp::assign(data_out, node3);

// execute the pipe

visioncpp::execute<visioncpp::policy::Fuse, 32, 32, 16, 16>(k, dev);

// show image

output = cv::Mat(ROWS, COLS, CV_8UC3, vc_buffer.get());

cv::imshow("Reference Image", frame);

cv::imshow("Mean Filter Convolution", output);

// loop

if (cv::waitKey(30) >= 0) break;

}

// release video/camera

cap.release();

return 0;

}

#endif

visioncpp/examples/simple_conv.cpp at License-update · codeplaysoftware/visioncpp · GitHub

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