图片处理

使用scipy.misc.face(gray=True)获取图片使用ndimage移动坐标，旋转图片，切割图片，缩放图片。

导包，读取显示图片

In [13]:

 
#scipy自带的一张图
face=misc.face()
plt.imshow(face)
plt.show()

In [14]:

 
from  scipy import ndimage

shift移动坐标

In [15]:

 
face1=ndimage.shift(face,shift=[200,0,0],cval=255)#高，宽，颜色,cval(常量)=255白色，0（黑色）
plt.imshow(face1)
plt.show()

In [16]:

 
'''
mode : str, optional
    Points outside the boundaries of the input are filled according
    to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap').
    Default is 'constant'.'''
face1=ndimage.shift(face,shift=[0,-500,1],mode='mirror')#mode对无图像的地方操作，可变像看作补全
plt.imshow(face1)
plt.show()

In [17]:

 
face2=ndimage.shift(face,shift=[0,-500,0],mode='wrap')
plt.imshow(face2)
plt.show()

rotate旋转图片

In [18]:

 
#mode对无图像的地方操作，可变像看作补全,这里的旋转相较于前面的不会有图片的边角消失
face3=ndimage.rotate(face,angle=60,mode='mirror')
plt.imshow(face3)
plt.show()

zoom缩放

In [49]:

 
face4=ndimage.zoom(face,zoom=[0.5,0.5,0.9]) #高，宽，颜色
plt.imshow(face4)
plt.show()
# face4     #当颜色小于0.9，arrag怎么会没东西？？ (384, 512, 0)   TypeError: Invalid dimensions for image data

/Users/helong/anaconda3/envs/Machine_learning/lib/python3.6/site-packages/scipy/ndimage/interpolation.py:600: UserWarning: From scipy 0.13.0, the output shape of zoom() is calculated with round() instead of int() - for these inputs the size of the returned array has changed.
  "the returned array has changed.", UserWarning)

In [61]:

 
face5=ndimage.zoom(face,zoom=[0.5,0.5,1/3]) #高，宽，颜色
# 形状出现问题TypeError: Invalid dimensions for image data (384, 512, 9),要reshape来解决
#cmap=plt.cm.gray灰度显示黑白，要求是二维（降一下维度）
plt.imshow(face5.reshape(384, 512),cmap=plt.cm.gray)  
plt.show()

In [64]:

face5.shape

Out[64]:

(384, 512, 1)

In [66]:

 
face6=ndimage.zoom(face,zoom=[0.5,0.5,4/3]) #高，宽，颜色， 4/3透明效果 四维，rgb+1
plt.imshow(face6)
plt.show()

In [71]:

 
face6[:,:,2]=190
plt.imshow(face6)
plt.show()

In [80]:

face6[:,:,3]

Out[80]:

array([[131, 165, 167, ...,  78,  74,  90],
       [ 84, 126, 140, ...,  59,  71,  98],
       [114, 136, 157, ...,  72,  70,  64],
       ..., 
       [ 98,  77,  95, ..., 102,  98,  96],
       [ 76,  92, 107, ..., 102,  97,  95],
       [ 74,  97, 103, ..., 100,  95,  92]], dtype=uint8)

切片操作

图片进行过滤，

添加噪声，对噪声图片使用ndimage中的高斯滤波，中值滤波，sigg1al中维纳滤波处理使图片变得更清楚

加载图片，使灰色图片misc.face()添加噪声

In [ ]:

ndimaged.

高斯滤波sigma：高斯喝的标准偏差

In [83]:

 
import pandas as  pd
import  matplotlib.pyplot as plt

In [85]:

 
moon=plt.imread('./moonlanding.png')
moon.shape

Out[85]:

(555, 738, 4)

In [91]:

 
plt.figure(figsize=(12,9))
# plt.imshow(moon)
# plt.show()

IOPub data rate exceeded.
The notebook server will temporarily stop sending output
to the client in order to avoid crashing it.
To change this limit, set the config variable
`--NotebookApp.iopub_data_rate_limit`.

In [97]:

 
 
 
 
 

#高斯分布，正态分布，概率不同
#misc，imfilter(moon,'smooth')原理一样
'''
input : array_like
    Input array to filter.
sigma : scalar or sequence of scalars
    Standard deviation for Gaussian kernel. The standard
    deviations of the Gaussian filter are given for each axis as a
    sequence, or as a single number, in which case it is equal for
    all axes.'''
moon2= ndimage.gaussian_filter(moon,sigma=2)#卷积操作,（概率），而不是数据提取成波
plt.figure(figsize=(12,9))
plt.imshow(moon2)
plt.show()
 

中值滤波参数size：给出差在每个原=元素上的从输入数组中提取出来的形状位置，定义过滤器功能的输入

In [100]:

 
moon2=ndimage.median_filter(moon,size=5)
plt.figure(figsize=(12.,9))
plt.imshow(moon2)
plt.show()

cheflone

恆～

scipy图片处理(2)