from PIL import Image
import numpy as np

# Location of the image
img = Image.open("koko.jpg")
# size of the image
print(img.size)
# format of the image
print(img.format)
# mode of the image
xpixel = img.size[0]
ypixel = img.size[1]
#turn into editable list of colors
data = np.asarray(img, dtype=np.uint8)
data_new = np.zeros([ypixel, xpixel, 3], dtype=np.uint8)
#apply sharpen convolution as SIMD/Vector instruction

for y in range(data.shape[1]-1):
    #process all colors and the column convolution as vector operation
    #factors needed for type conversion to np.float64 to prevent integer overflow
    new_value = -1.0*data[:, y+1, :] + 2.5*data[:, y, :] - 1.0*data[:, y-1, :]
    new_value[new_value > 255] = 255
    new_value[new_value < 0] = 0
    data_new[:, y, :] = new_value

for x in range(data.shape[0]-1):
    new_value = 1.0*data_new[x, :, :] - 1.0*data[x+1,:, :] + 2.5*data[x,:, :] - 1.0*data[x-1,:, :]
    new_value[new_value > 255] = 255
    new_value[new_value < 0] = 0
    data_new[x, :, :] = new_value

#convert our new data into an image
img_new = Image.fromarray(data_new)
#the data and new image is 8-Bit unsigned integer per color -> PILLOW mode "RGB"
img_new.convert("RGB")
img_new.show()