https://github.com/mazen-daghari/systemc-opencv-project
systemc opencv guide
https://github.com/mazen-daghari/systemc-opencv-project
c-code opencv systemc visual-studio windows
Last synced: 2 months ago
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systemc opencv guide
- Host: GitHub
- URL: https://github.com/mazen-daghari/systemc-opencv-project
- Owner: mazen-daghari
- License: mit
- Created: 2024-11-07T17:12:09.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-12-13T19:04:34.000Z (6 months ago)
- Last Synced: 2025-02-12T17:58:04.842Z (4 months ago)
- Topics: c-code, opencv, systemc, visual-studio, windows
- Language: C++
- Homepage:
- Size: 5.11 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# systemc-opencv-project
systemc opencv guide
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Let's walk through the entire process of creating a SystemC project that reads an image, applies a black and white filter, applies a custom filter, and displays both the original and processed images using OpenCV. This tutorial will cover everything from setting up your environment to writing and running the code.
Step 1: Setting Up Your Environment
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Install SystemC:
Download SystemC from the Accellera website.
Follow the installation instructions provided in the SystemC documentation.
Install OpenCV:
Download OpenCV from the OpenCV website.
Follow the installation instructions provided in the OpenCV documentation.
Set Up Your Project Directory:
Create a directory for your project. For example, systemc_opencv_project.
Inside this directory, create two subdirectories: src for source files and include for header files.
Step 2: Writing the Code
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Image Processor Module (image_processor.cpp)
Create a file named image_processor.cpp in the src directory and add the following code:
cpp
#include
#include
SC_MODULE(ImageProcessor) {
sc_in clk;
sc_in reset;
void process() {
while (true) {
wait(); // Wait for clock edge
if (reset.read() == true) {
std::cout << "Reset signal received" << std::endl;
continue;
}
cv::Mat image = cv::imread("image.jpg", cv::IMREAD_COLOR); // Load the image in color
if (!image.empty()) { // Check if the image was loaded correctly
cv::imshow("Original Image", image); // Display the original image
cv::Mat gray_image;
cv::cvtColor(image, gray_image, cv::COLOR_BGR2GRAY); // Convert to black and white
// Apply custom filter
cv::Mat custom_filtered_image;
cv::Mat kernel = (cv::Mat_(1, 2) << -1, 0);
cv::filter2D(gray_image, custom_filtered_image, -1, kernel);
// Display the processed images
cv::imshow("Black and White Image", gray_image);
cv::imshow("Custom Filtered Image", custom_filtered_image);
cv::waitKey(0); // Wait for a key press to close the windows
} else {
std::cerr << "Error loading the image." << std::endl;
}
}
}
SC_CTOR(ImageProcessor) {
SC_THREAD(process);
sensitive << clk.pos();
}
};
Main File (main.cpp)
Create a file named main.cpp in the src directory and add the following code:
cpp
#include
#include "image_processor.cpp" // Include the ImageProcessor module
int sc_main(int argc, char* argv[]) { sc_clock clk("clk", 10, SC_NS);
sc_signal reset;
ImageProcessor image_processor("image_processor");
image_processor.clk(clk);
image_processor.reset(reset);
// Simulation
sc_start(0, SC_NS);
reset.write(false);
sc_start(10, SC_NS);
reset.write(true);
sc_start(10, SC_NS);
reset.write(false);
sc_start(100, SC_NS);
return 0;}
Step 3: Creating the Makefile
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Create a file named Makefile in the root directory of your project and add the following code:
makefile
CXX = g++
CXXFLAGS = -I/usr/local/include/opencv4 -I$(SYSTEMC_HOME)/include -Wno-unused-variable -Wno-sign-compare -Wno-maybe-uninitialized
LDFLAGS = -L/usr/local/lib -lopencv_core -lopencv_imgcodecs -lopencv_imgproc -lopencv_highgui -L$(SYSTEMC_HOME)/lib-linux64 -lsystemc
all: main
main: main.o image_processor.o
$(CXX) -o main main.o image_processor.o $(LDFLAGS)
main.o: src/main.cpp
$(CXX) $(CXXFLAGS) -c src/main.cpp
image_processor.o: src/image_processor.cpp
$(CXX) $(CXXFLAGS) -c src/image_processor.cpp
clean:
rm -f *.o main
Step 4: Compiling and Running the Project
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Compile the Project:
Open a terminal and navigate to your project directory.
Run the following command to compile the project:
sh
make
Run the Executable:
Ensure that the image file image.jpg is in the same directory as your executable.
Run the executable:
sh
./main
Step 5: Observing the Output
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The program will display three windows:
Original Image: Shows the original image.
Black and White Image: Shows the image after applying the black and white filter.
Custom Filtered Image: Shows the image after applying the custom filter with the kernel [-1, 0].
Press any key to close the windows.
You've successfully created a SystemC project that integrates with OpenCV to read, process, and display images. This tutorial covered setting up the environment, writing the code, creating a Makefile, and running the project.
feel free to mail me on :
full installation guide (read installation_tutorial.pdf on repository)
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