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93 lines
1.7 KiB
Markdown
93 lines
1.7 KiB
Markdown
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## ndimage用途
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SciPy的ndimage子模块专用于图像处理。这里，ndimage表示一个n维图像。
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图像处理中一些最常见的任务如下:
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* 输入/输出/显示图像
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* 基本操作:裁剪，翻转，旋转等图像过滤
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* 去噪，锐化等图像分割
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* 标记对应于不同对象的像素
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* 分类
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* 特征提取
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* 注册/配准
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## 示例
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```
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# 导入图像
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from scipy import misc
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f = misc.face()
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misc.imsave('face.png', f) # uses the Image module (PIL)
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import matplotlib.pyplot as plt
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plt.imshow(f)
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plt.show()
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# 基本信息
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from scipy import misc
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f = misc.face()
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misc.imsave('face.png', f) # uses the Image module (PIL)
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face = misc.face(gray = False)
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print (face.mean(), face.max(), face.min())
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## 几何裁剪
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from scipy import misc
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f = misc.face()
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misc.imsave('face.png', f) # uses the Image module (PIL)
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face = misc.face(gray = True)
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lx, ly = face.shape
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crop_face = face[int(lx/4): -int(lx/4), int(ly/4): -int(ly/4)]
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import matplotlib.pyplot as plt
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plt.imshow(crop_face)
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plt.show()
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# 倒置图像
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from scipy import misc
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face = misc.face()
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flip_ud_face = np.flipud(face)
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import matplotlib.pyplot as plt
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plt.imshow(flip_ud_face)
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plt.show()
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# 旋转图像
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# rotation
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from scipy import misc,ndimage
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face = misc.face()
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rotate_face = ndimage.rotate(face, 45)
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import matplotlib.pyplot as plt
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plt.imshow(rotate_face)
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plt.show()
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# 模糊滤镜
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from scipy import misc
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face = misc.face()
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blurred_face = ndimage.gaussian_filter(face, sigma=3)
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import matplotlib.pyplot as plt
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plt.imshow(blurred_face)
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plt.show()
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# 边缘检测
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import scipy.ndimage as nd
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import numpy as np
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im = np.zeros((256, 256))
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im[64:-64, 64:-64] = 1
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im[90:-90,90:-90] = 2
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im = ndimage.gaussian_filter(im, 8)
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import matplotlib.pyplot as plt
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plt.imshow(im)
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plt.show()
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```
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