| 知乎专栏 |
自定义宽度和高度，会出现拉伸
image = image.resize((w, h))
放大图像会出现画质损失，设置图像差值可以提高画质
image = image.resize((w, h), Image.ANTIALIAS)
from PIL import Image
img = Image.open('netkiller.jpg')
width, height = img.size
# 默认模式是NEARESET(最近邻插值)
img_NEARESET = img.resize((width//2, height//2))
# BILINEAR 2x2区域的双线性插值
img_BILINEAR = img.resize((width//2, height//2), Image.BILINEAR)
# BICUBIC 4x4区域的双三次插值
img_BICUBIC = img.resize((width//2, height//2), Image.BICUBIC)
# ANTIALIAS 高质量下采样滤波
img_ANTIALIAS = img.resize((width//2, height//2), Image.ANTIALIAS)
width = 800 height = 600 print(width,height) w = 400 ratio = width / w print(ratio) width = w height = height / ratio print(width,height)
self.args.imgsz 是希望修改的长边
from PIL import Image
# 加载图像
image = Image.open('path_to_your_image.jpg')
# 计算缩放因子
width, height = image.size
# print(width, height)
if max(width,height)> self.args.imgsz:
if width > height :
ratio = width / self.args.imgsz
width = self.args.imgsz
height = int(height / ratio)
else:
ratio = height / self.args.imgsz
width = int(width / ratio)
height = self.args.imgsz
# print(ratio)
# print(width, height)
image.resize((width, height))
image = ImageOps.exif_transpose(image)
def resize(self,image):
# from PIL import Image
# 加载图像
# image = Image.open('path_to_your_image.jpg')
# 计算缩放因子
width, height = image.size
# print(width, height)
if max(width,height)> self.args.imgsz:
if width > height :
ratio = width / self.args.imgsz
width = self.args.imgsz
height = int(height / ratio)
else:
ratio = height / self.args.imgsz
width = int(width / ratio)
height = self.args.imgsz
# print(ratio)
# print(width, height)
image = image.resize((width, height))
image = ImageOps.exif_transpose(image)
return image
return image
from PIL import Image
a = Image.new('RGB', (300, 300), (255, 0, 0)) # 生成一张300*300的红色图片
b = Image.new('RGB', (200, 200), (0, 255, 0)) # 生成一张200*200的绿色图片
c = Image.new('RGB', (100, 100), (0, 0, 255)) # 生成一张200*200的红色图片
b.paste(c, (50, 50)) # 将c贴到b的坐标为（50，50）的位置
a.paste(b, (50, 50)) # 将b贴到a的坐标为（50，50）的位置
a.show() # 显示最终实现三个图像叠加效果
超出范围部分会被裁切掉
from PIL import Image
a = Image.new('RGB', (300, 300), (255, 0, 0)) # 生成一张300*300的红色图片
b = Image.new('RGB', (100, 600), (0, 255, 0)) # 生成一张100*600的绿色图片
a.paste(b, (100, 150)) # 将b贴到a的坐标为（100，150）的位置
a.show() # 显示效果表明，超出部分会被裁切掉
负坐标测试，同样也会被裁剪
from PIL import Image
a = Image.new('RGB', (200, 200), (255, 0, 0)) # 生成一张200*200的红色图片
b = Image.new('RGB', (150, 150), (0, 255, 0)) # 生成一张150*150的绿色图片
a.paste(b, (-50, -50)) # 将b贴到a的坐标为（-50，-50）的位置
a.show()
from PIL import Image
img = Image.open('netkiller.png')
width, height = img.size
channel_mode = img.mode
img_full = Image.new(channel_mode, (width*2, height))
img_part = Image.new(channel_mode, (width+100, height))
# 图像水平扩展整个图像
img_full.paste(img, (0, 0, width, height))
img_full.paste(img, (width, 0, width*2, height))
# left, top, width, height
box = (width-100, 0, width, height)
region = img.crop(box)
# 图像水平右侧扩展一个ROI
img_part.paste(img, (0, 0, width, height))
img_part.paste(region, (width, 0, width+100, height))
img_part.show()
img_full.show()
image = image.rotate(90)
import PIL.Image as img
import os
# 图片地址
imgfile = 'Neo.jpg'
# 用PIL打开一个图片
im = img.open(imgfile)
# 剪切图片的位置，格式为:xmin ymin xmax ymax
box = (50, 50, 200, 50)
# 对im进行裁剪
new = im.crop(box)
# 进行向左旋转20度 向右为负数
new = ng.rotate(20)
#保存选取
new.save('copy.jpg')
# 粘贴选取
im.paste(ng, (150, 150))
#保存
im.save('new.jpg')
from PIL import Image
import numpy as np
img = Image.open('netkiller.jpg')
# 宽度，高度
width, height = img.size
# 通道
channel_mode = img.mode
# 平均值
mean_value = np.mean(img)
print(width)
print(height)
print(channel_mode)
print(mean_value)
from PIL import Image
width = 200
height = 100
img_white = Image.new('RGB', (width,height), (255,255,255))
img_black = Image.new('RGB', (width,height), (0,0,0))
img_L = Image.new('L', (width, height), (255))
img_white.show()
img_black.show()
img_L.show()
from PIL import Image
img = Image.open('netkiller.jpg')
width, height = img.size
# 前两个坐标点是左上角坐标，后两个坐标点是右下角坐标（width，height）
box = (100, 100, 600, 800)
region = img.crop(box)
region.save('neo.jpg')
from PIL import Image
img = Image.open('netkiller.jpg')
imgGrey = img.convert('L')
img.show()
imgGrey.show()
img.save('neo.jpg')
imgGrey.save('gray.jpg')
from PIL import Image
img = Image.open('netkiller.jpg')
# 分离通道
R, G, B = img.split()
R.show)
G.show()
B.show()
# 合并通道
img_RGB = Image.merge('RGB', (R, G, B))
img_BGR = Image.merge('RGB', (B, G, R))
# 显示图像
img_RGB.show()
img_BGR.show()
from PIL import Image
img = Image.open('netkiller.jpg')
width, height = img.size
# 获取指定坐标位置像素值
pixel_value = img.getpixel((width/2, height/2))
print(pixel_value)
# 使用load方法获取指定坐标位置像素值
pim = img.load()
pixel_value1 = pim[width/2, height/2]
print(pixel_value1)
# 设置指定坐标位置像素的值
pim[width/2, height/2] = (0, 0, 0)
# 使用putpixel方法设置指定坐标位置像素的值
img.putpixel((w//2, h//2), (255,255,255))
# 设置指定区域像素的值
for w in range(int(width/2) - 50, int(width/2) + 50):
for h in range(int(height/2) - 50, int(height/2) + 50):
pim[w, h] = (255, 0, 0)
# img.putpixel((w, h), (255,255,255))
img.show()
from PIL import Image, ImageDraw, ImageFont
img = Image.open('netkiller.jpg')
# 创建Draw对象:
draw = ImageDraw.Draw(img)
# 字体颜色
fillColor = (255, 0, 0)
text = 'https://www.netkiller.cn'
position = (100,100)
draw.text(position, text, fill=fillColor)
img.show()
from PIL import Image
import numpy as np
img = Image.open('netkiller.jpg')
# PIL.Image 转 numpy
array = np.array(img)
# numpy转 PIL.Image
img1 = Image.fromarray(array)
img1 = Image.fromarray(array.astype('uint8'))
img1.save('from_array.jpg')
from PIL import Image
import numpy as np
im = Image.open("netkiller.jpg")
im.show()
img = np.array(im) # image类 转 numpy
img = img[:,:,0] #第1通道
im=Image.fromarray(img) # numpy 转 image类
im.show()
from PIL import Image
from PIL import ImageChops
def compare_images(one, two, diff):
image_one = Image.open(one)
image_two = Image.open(two)
try:
diff = ImageChops.difference(image_one, image_two)
if diff.getbbox() is None:
print("【+】We are the same!")
else:
diff.save(diff)
except ValueError as e:
text = ("Pastes another image into this image."
"The box argument is either a 2-tuple giving the upper left corner, a 4-tuple defining the left, upper, "
"right, and lower pixel coordinate, or None (same as (0, 0)). If a 4-tuple is given, the size of the pasted "
"image must match the size of the region.")
print("【{0}】{1}".format(e,text))
if __name__ == '__main__':
compare_images('1.png', '2.png', '我们不一样.png')