How To Get Coordinates Of An Image In Opencv Python

In this tutorial, we will learn how to get the coordinates of an image in OpenCV, a powerful open-source computer vision library, using Python.

We will explore different methods of obtaining the coordinates, which can be useful in various image processing tasks, such as object detection, image recognition, and image transformations.

Step 1: Install OpenCV

Before we start, make sure you have Python installed on your system. Next, install the OpenCV library using the following command:

Step 2: Load an Image

To load an image using OpenCV, we need to import the OpenCV library and use the cv2.imread() function.

Replace ‘robot.jpg’ with the path to your own image file.

Step 3: Display the Image

To display the loaded image, use the cv2.imshow() function.

The cv2.waitKey(0) function waits for any key press indefinitely, and the cv2.destroyAllWindows() function closes all the windows opened by OpenCV.

Step 4: Define a Mouse Callback Function

To get the coordinates of an image, we will use a mouse callback function. This function will be called every time a mouse event occurs in the OpenCV window.

In the above code, we define a function mouse_callback that takes in the mouse event, coordinates, and other necessary parameters. We check if the left mouse button is pressed, and print the coordinates when this event occurs.

Then, we attach the mouse callback function to the OpenCV window with cv2.setMouseCallback().

Step 5: Combine the Code

Now put all the pieces together, and you will get the following code:

When you run this code, the image will be displayed in an OpenCV window. Click on the image with the left mouse button, and the coordinates will be printed in the terminal.

Output

Now you can click anywhere inside the image. Here are some coordinates:

Mouse clicked at: (243, 123)
Mouse clicked at: (355, 202)
Mouse clicked at: (348, 256)

Conclusion

In this tutorial, we learned how to get the coordinates of an image using OpenCV and Python. This skill can be quite useful in various image-processing operations like object detection and recognition.

Although we demonstrated only one method to get the coordinates, you can find more advanced techniques, such as using predefined image libraries or deep learning algorithms, to obtain the desired results.