Use the Image module of the Python-PIL library to restore the RGB matrix to a picture

Use the Image module of the Python-PIL library to restore the RGB matrix to a picture

Recently, I encountered a big problem when using Python to simulate the k-means algorithm. How to restore the RGB matrix after clustering to a picture?

Let's use a small example to record the implementation process.

step

1. Open the image and get its corresponding RGB matrix

#读取图像
from PIL import Image
def getImgData():
    img = Image.open('example.jpg','r')
    print(img.size)
    lst = list(img.getdata())
    return lst

img.size is (500,358)

2. Convert the RGB matrix to a list of n*m; n refers to the number of rows in the picture (500), and m refers to the number of columns in the picture (358)

lst = getImgData()
lst1 = []
for i in range(0,500):
    lst1.append(lst[357*i:357*i+357])

3. Verify if the conversion is successful

for val,i in zip(lst1,range(0,len(lst1))):
    print(val)
    print(len(val))

4. Convert each RGB to pixels, and then save as a new picture

newimg = Image.new('RGB',(500,358))
i=0
for val,i in zip(lst1,range(0,len(lst1))):
    for j in range(0,len(val)):
        newimg.putpixel((i,j),(int(val[j][0]),int(val[j][1]),int(val[j][2])))
newimg.save('flag.jpg')

Complete code

#读取图像
from PIL import Image
def getImgData():
    img = Image.open('example.jpg','r')
    print(img.size)
    lst = list(img.getdata())
    return lst
lst = getImgData()
lst1 = []
for i in range(0,500):
    lst1.append(lst[357*i:357*i+357])
for val,i in zip(lst1,range(0,len(lst1))):
    print(val)
    print(len(val))
print(i)
newimg = Image.new('RGB',(500,358))
i=0
for val,i in zip(lst1,range(0,len(lst1))):
    for j in range(0,len(val)):
        newimg.putpixel((i,j),(int(val[j][0]),int(val[j][1]),int(val[j][2])))
newimg.save('flag.jpg')

 operation result

I am a Python rookie, please criticize and correct me in time.