Image Processing Using NumPy - Part 1


NumPy can be used for image processing. Images can be represented as NumPy arrays, and NumPy provides a variety of functions for manipulating and processing these arrays.

Some of the common image processing tasks that can be performed using NumPy include:

  • Image loading and saving: NumPy can be used to load and save images in a variety of formats, such as JPEG, PNG, and TIFF.
  • Image resizing: Resizing an image can be done by changing the dimensions of the NumPy array.
  • Image cropping: Cropping an image can be done by slicing the NumPy array.
  • Image rotation: Rotating an image can be done by applying a rotation transformation to the NumPy array.
  • Image flipping: Flipping an image can be done by reflecting the NumPy array about a specified axis.
  • Image filtering: Image filtering can be done by applying a filter to the NumPy array. Filters can be used to blur, sharpen, or enhance images.
  • Image segmentation: Image segmentation is the process of dividing an image into different regions. This can be done using a variety of techniques, such as thresholding, clustering, and edge detection.
  • Image compression: Image compression is the process of reducing the size of an image file. This can be done using a variety of techniques, such as lossy compression and lossless compression.

Here is an example of how to resize an image using NumPy:


This code first loads the image into a NumPy array. Then, it resizes the image by half its original size. Finally, it saves the resized image to a file.

Here is another example of how to use NumPy to load an image, resize it, and save it:


This code loads the image image.jpg as a NumPy array, resizes it to 200x200 pixels, and saves it as the file resized_image.jpg.

NumPy can be used to rotate images. The numpy.rot90() function can be used to rotate an image by 90 degrees clockwise or counterclockwise. The function takes two arguments: the image array and the number of times to rotate the image. The default number of rotations is 1, so the image will be rotated 90 degrees clockwise.

Here is an example of how to use the numpy.rot90() function to rotate an image by 90 degrees clockwise:


This code loads the image image.jpg as a NumPy array, rotates it by 90 degrees clockwise, and saves it as the file rotated_image.jpg.

The numpy.rot90() function can also be used to rotate images by other angles. For example, to rotate an image by 180 degrees, you would use the following code:

To rotate an image by 270 degrees, you would use the following code:

The numpy.flip() function can be used to flip an image vertically or horizontally. The following code flips an image vertically:





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