Скачать или смотреть Extracting and Reconstructing Image Patches with skimage in Python

Learn how to use `skimage`'s `view_as_windows` for extracting and reconstructing image patches from a color image in Python.
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Extracting and Reconstructing Image Patches with skimage in Python

When working with digital images, you may often need to process smaller sections, or "patches", of an image. This is particularly useful in machine learning and image processing where local features are important. In this guide, we’ll explore how to extract color image patches from a 512x512 color image, save them as individual files, and then reconstruct the original image from those patches using the view_as_windows function from the skimage library in Python.

The Problem

You have a 512x512 color image and wish to divide it into smaller patches of size 128x128 pixels. After saving these patches individually, you want to be able to reconstruct the original image back from these patches. You noticed that after saving, the shape of your patches changes, causing confusion when attempting to reconstruct the image.

The Solution

Let’s break down the solution into organized steps so you can follow along easily. We will cover how to extract the patches, save them, and finally reconstruct the image.

Step 1: Extracting Patches

You will begin by importing the necessary libraries and loading your image:

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

Use the view_as_windows function to create patches:

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

Here, patch_img would have a shape of (7, 7, 1, 128, 128, 3). This means there are overlapping patches extracted from the original image.

Step 2: Saving Patches

You can save each patch as an image file. Below is a snippet to do this:

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

Step 3: Fixing Shapes After Loading

When you load the saved image patches using OpenCV, you may notice a shape transformation which is not yet suitable for reconstruction. To remedy this, you can reshape your loaded images as needed:

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

Step 4: Reconstructing the Image

Now we focus on how to reconstruct the original image using the patches. We will create an empty array for reconstruction and iterate through the patches.

Initialize the Empty Array:
Start with a blank 512x512 array initialized to zeros.

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

Place Patches Back:
Loop through the patches, using their positions to fill in the original array.

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

Verify Reconstruction:
Finally, compare the reconstructed image to the original to ensure they are the same.

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

This ensures that your reconstruction is accurate, confirming that every pixel matches the original image.

Conclusion

You’ve now successfully learned how to extract image patches using skimage's view_as_windows, save them individually, and reconstruct the original image from those patches. This technique opens up new avenues for image processing and analysis, providing a deeper understanding of how local features interact within an image.

By breaking the process into manageable steps and providing clear code examples, you can confidently implement these techniques in your own image processing tasks.

Happy coding!