Скачать или смотреть Fixing Flickering Text in OpenCV's cv2.putText

Learn how to eliminate flickering text when using OpenCV's cv2.putText function while displaying frames with cv2.imshow. Improve your Python projects seamlessly!
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Fixing Flickering Text in OpenCV's cv2.putText: A Beginner's Guide

If you have ever tried to display frames using OpenCV’s cv2.imshow while overlaying text using cv2.putText, you might have encountered the frustrating issue of flickering text. This problem can obscure the visual data you are trying to present, leading to a less than ideal user experience. In this guide, we will explore why this flickering occurs and how to resolve it effectively.

Understanding the Problem

When continuously displaying frames in a window, it’s essential to manage the drawing of text and graphics in a way that prevents rendering artifacts like flickering. Flickering typically happens when you’ve made mistakes in the loop structure of your code, especially regarding when and how the frame is updated.

Common Signs of Flickering

Rapidly changing text color (like switching between black and white)

Unstable display where the text appears and disappears

In the given scenario, flickering occurs because the text drawn in different iterations of a nested loop leads to conflicting visual states being displayed. Let's dive into the solution.

Step-by-Step Solution

1. Identifying the Code Structure

Looking at the original code shared, the issue arose due to the indentation issue regarding cv.imshow and cv.waitKey. These function calls were placed in the inner loop that handled the thickness of the text, resulting in displaying both black and white texts in rapid succession.

2. Correcting the Indentation

To correct the flickering, we need to ensure that cv.imshow is called only once per frame, after all text has been drawn. This involves moving these function calls outside of the inner loop.

Here's how the corrected code looks:

[[See Video to Reveal this Text or Code Snippet]]

3. Key Changes Made

Moved cv.imshow and cv.waitKey calls: These are now located after the inner loop that handles text drawing. Thus, the image is shown only once after all modifications to it are completed.

Ensured uniform drawing: The text will be drawn with the final state rather than being updated several times within the inner loop.

Conclusion

By ensuring your code properly manages when and how functions like cv.imshow are called, you can eliminate flickering text issues in OpenCV. This not only makes your application look more polished but also enhances the overall user interaction. We hope that this guide helps you achieve smoother visual outputs in your Python projects using OpenCV.

Feel free to experiment with your own projects and file any further questions in the comments below!