Python PIL

The PIL (Python Image Library) library is a third-party library of the Python language. The PIL library supports image storage, display, and processing, and can handle images in almost all formats.

Introduction to PIL library
The PIL library has two main functions:

(1) Image filing: batch processing of images, production image preview, image format conversion, etc.

(2) Image processing: basic image processing, pixel processing, color processing, etc.

PIL has multiple classes. Here is a brief introduction to the Image class, ImageFilter class, and ImageEnhance class.

Second, install library functions

Three, use the library function Image class-basic image processing

Call the Image class

from PIL import Image

Image class about image reading and creation

Method	Description
Image.open(filename)	Load image file
Image.new(mode,size,color)	Create a new image according to the given parameters
Image.open(StringIO.StringIO(buffer))	Get image from string
Image.frombytes(mode,size,color)	Create a new image based on pixels
Image.verify()	Check the integrity of the image and return an exception

Common attributes of the Image class

Method	Description
Image.format	Image format or source, if the image is not read from a file, return None
Image.mode	The color mode of the image,'L' is grayscale mode,'RGB' is true color image,'C (cyan) M (magenta) Y (yellow) K (black)' is the published image
Image.size	The width and height of the image, in pixels (px), the return value is a tuple type
Image.palette	Palette property, return ImagePalette type

Sequence image operation method of Image class

Method	Description
Image.seek(frame)	Jump and return to the specified frame in the image
Image.tell()	Returns the serial number of the current frame

Image rotation and scaling methods of the Image class

Method	Description
Image.resize(size)	return a copy of the image resized by size
Image.rotate(angle)	Returns a copy of the image rotated by angle

Image conversion and saving method of Image class

Method	Description
Image.save(filename,format)	Save the image as filename, format format
Image.convert(mode)	Convert the image to mode mode
Image.thumbnail(size)	Create a thumbnail of the image, size is a tuple of thumbnail size

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''' Change the color --- color inversion'''
from PIL import Image
nest = Image.open("D:\nest.jpg")
r,g,b = nest.split() #Get the color value of the RGB channel of the original image
newb = b.point(lambda i:i*1.1) #Enhance the color value of the B channel
nest1 = Image.merge(nest.mode,(b,g,r))
nest1.thumbnail((400,254)) #Create thumbnail
nest1.save("D:\nest_2.jpg")

Image pixel and channel processing method of Image class

Method	Description
Image.point(func)	Calculate each element according to the function of the function func, and return a copy of the image
Image.split()	According to each color channel of the GRB image, return a copy of the image
Image.merge(mode,bands)	composite channel, where mode is color, bands is the new color channel
Image.blend(im1,im2,alpha)	Interpolate the two pictures im1 and im2 according to the formula to generate a new image formula: im1(1.0-alpha) + im2alpha

Fourth, use the library function ImageFilter class-image filtering

Call the ImageFilter class

from PIL import ImageFilter

ImageFilter class predefined image filtering method

Method	Description
ImageFilter.BLUR	Image blur effect
ImageFilter.CONTOUR	Image contour effect
ImageFilter.DETAIL	Image detail effect
ImageFilter.EDGE_ENHANCE	Image boundary enhancement effect
ImageFilter.EDGE_ENHANCE_MORE	Image threshold boundary enhancement effect
ImageFilter.EMBOSS	Image relief effect
ImageFilter.FIND_EDGES	Image border effect
ImageFilter.SMOOTH	Image smoothing effect
ImageFilter.SMOOTH_MORE	Image threshold smoothing effect
ImageFilter.SHARPEN	Image sharpening effect

# - *- encoding:utf-8-*-'''Contour effect---sketch'''from PIL import Image
from PIL import ImageFilter
square = Image.open("D:\\square.jpg")
square1 = square.filter(ImageFilter.CONTOUR)  #Select contour effect
square1.save("D:\\square0.jpg")

Python on image processing PIL

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