发布时间:2021-07-27 23:55:06编辑:run阅读(2978)
不同的python库都可以用于基本的图像操作,几乎所有库都以numpy ndarray存储图像
使用numpy数组切片成圆形图
import matplotlib.image as mpimg import matplotlib.pylab as plt import numpy as np # 使用numpy数组切片和掩模在人物图像上创建圆形掩模 # 指定默认字体 plt.rcParams['font.sans-serif'] = ['KaiTi'] # 解决保存图像是负号'-'显示为方块的问题 plt.rcParams['axes.unicode_minus'] = False lena = mpimg.imread(r'D:\image_processing\jpgs\c.jpg') test = mpimg.imread(r'D:\image_processing\jpgs\c.jpg') lx, ly, _ = lena.shape x, y = np.ogrid[0:lx, 0:ly] mask = (x - lx / 2) ** 2 + (y - ly / 2) ** 2 > lx * ly / 4 lena[mask, :] = 0 plt.figure(figsize=(10,10)) plt.subplot(221), plt.imshow(test), plt.title('原图', size=20),plt.axis('off') plt.subplot(222), plt.imshow(lena), plt.title('圆形图', size=20),plt.axis('off') plt.show()
简单的图像合并,将背景图和人物图合并成一张新图
from PIL import Image import matplotlib.pylab as plt # 指定默认字体 plt.rcParams['font.sans-serif'] = ['KaiTi'] # 解决保存图像是负号'-'显示为方块的问题 plt.rcParams['axes.unicode_minus'] = False im1 = Image.open(r'D:\image_processing\jpgs\c.jpg') im2 = Image.open(r'D:\image_processing\jpgs\aa.jpg') w1 = im1.width # 图片的宽 h1 = im1.height # 图片的高 im3 = Image.new('RGB', (w1, h1), 'black') n = 0 for y in range(h1): for x in range(w1): if y % 2 == 0: if n % 2 == 0: im3.putpixel((x, y), im1.load()[x, y]) else: im3.putpixel((x, y), im2.load()[x, y]) n += 1 else: if n % 2 == 0: im3.putpixel((x, y), im2.load()[x, y]) else: im3.putpixel((x, y), im1.load()[x, y]) n += 1 plt.figure(figsize=(10,10)) plt.subplot(221), plt.imshow(im1), plt.title('头像图', size=20),plt.axis('off') plt.subplot(222), plt.imshow(im2), plt.title('背景图', size=20),plt.axis('off') plt.subplot(223), plt.imshow(im3), plt.title('合成图', size=20),plt.axis('off') plt.show()
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