OpenCV: High Memory Usage When Processing Large Images with GaussianBlur
I'm performance testing and I'm dealing with I can't seem to get I'm having trouble with I'm currently working on an image processing project using OpenCV (version 4.5.1), and I've encountered an scenario with excessive memory usage when applying the `GaussianBlur` function to large images... For instance, when I attempt to blur a 4000x3000 pixel image, the memory consumption spikes dramatically, leading to a crash with an behavior that states, "Out of memory: unable to allocate 16 bytes". I have tried optimizing the kernel size by using a 5x5 Gaussian kernel instead of 11x11, but this did not resolve the scenario. Here's the relevant code snippet: ```python import cv2 import numpy as np # Load a large image image = cv2.imread('large_image.jpg') # Attempt to apply GaussianBlur blurred_image = cv2.GaussianBlur(image, (5, 5), 0) ``` I also attempted to resize the image before applying the blur, but this negatively impacted the quality of the final output. I've checked my system's memory usage during the process and confirmed that it maxes out, which is causing the crash. Is there a more memory-efficient way to apply Gaussian blur on large images without significantly compromising quality? Any insights on potential workarounds or best practices would be greatly appreciated. Is there a better approach? I'm developing on Linux with Python. I'm working on a mobile app that needs to handle this. Any advice would be much appreciated. I've been using Python for about a year now. I'd really appreciate any guidance on this.