demo1
# Open the picture, add some salt and pepper and random noise from PIL Import Image Import numpy AS NP Import matplotlib.pyplot AS plt img = np.array (Image.open ( ' /home/keysen/caffe/examples/images/cat.jpg ' )) # open the image into a digital matrix and # 5000 randomly generated pepper rows, cols, DIMS = img.shape for I in Range ( 5000 ): X = np.random.randint ( 0 , rows) Y = np.random .randint ( 0 , cols) IMG [X, Y ,:] = 255 plt.figure ( " cat_salt ") plt.imshow(img) plt.axis('off') plt.show()
demo2
# Binarized image, the pixel value becomes greater than 128 to 1, otherwise becomes 0 from the PIL Import Image Import numpy AS NP Import matplotlib.pyplot AS PLT IMG = np.array (Image.open ( ' / Home / keysen / Caffe / examples / images / cat.jpg ' ) .convert ( ' L ' )) and # opens into a digital image matrix rows, cols = img.shape for I in Range (rows): for J in Range (cols): IF (IMG [I, J] <= 128 ): IMG [I, J] = 0 the else : IMG [I, J]=1 plt.figure("cat_black&white") plt.imshow(img,cmap='gray') plt.axis('off') plt.show()
Reference:
https://blog.csdn.net/Hanging_Gardens/article/details/79014160