Basic Image Manipulation

img = cv2.readim("image.png",0)

Accessing Individual Pixels

  • print(img[0][0]) = print(img[0, 0])
  • print(img[:, 6]) = print(img[:][6])

Modifying Image Pixels

img_cp = img.copy()
img_cp[2, 3] = 200
img_cp[3, 3] = 500

Cropping Images

  • selecting a specific (pixel) region of the image 
    img_cropped = img[200:400, 300:600]
# or
img_cropped = img[200:400, 300:600, :]
  • selects rows from 200 to 399 and columns from 300 to 599.

Resizing images

  • resizes the image src down to or up to the specified size. The size and type are derived from the src, dsize, fx, and fy.
  • dst = resize( src, dsize[, dst[, fx[, fy[, interpolation]]]] )
    • dst : ouput image
    • 2 required arguments
      • src : imput image
      • dsize : output image size
    • optional arguments
      • fx : scales along the horizontal axis
      • fy : scales along the vertical axis

Methods to resize :

  1. Specifying Scaling Factor using fx and fy
    • resized_img-2x = cv2.resize(img, None, fx=2, fy=2)
  2. Specifying exact size of the output image ```python desired_width = 100 desired_height = 200 dim = (desired_width, desired_height)

img_resized = cv2.resize(img, dsize=dim, interpolation=cv2.INTER_AREA) ```

  • interpolation=cv2.INTER_AREA : used to downsize / shrink an image

Flipping Images

  • dst = cv.flip( src, flipCode )
    • dst : output array of the same size and type as src
    • src : input image
    • filpCode : a flag to specify how to flip the array
      • 0 means flipping around the x-axis
      • positive value (for example, 1) means flipping around y-axis
      • Negative value (for example, -1) means flipping around both axes.
  • img_flip = cv2.flip(img, 1)

Collab Notebook here