20170619图像处理start

from PIL import Image

#读取图像，并用 .convert('L')将图像转换为灰度图像pil_im = Image.open('zqlj.jpg').convert('L')

pil_im

import osfor infile in filelist:    outfile = os.path.splitext(infile)[0]+".jpg"    if infile != outfile:        try:            Image.open(infile).save(outfile)        except IOError:            print "cannot convert",infile

---------------------------------------------------------------------------NameError                                 Traceback (most recent call last)<ipython-input-6-ddb674c1c23f> in <module>()      1 import os----> 2 for infile in filelist:      3     outfile = os.path.splitext(infile)[0]+".jpg"      4     if infile != outfile:      5         try:NameError: name 'filelist' is not defined

def get_imlist(path):    """ 返回目录中所有 JPG 图像的文件名列表 """    """文件路径不能出现中文"""    return [os.path.join(path,f) for f in os.listdir(path) if f.endswith('.jpg')]

get_imlist('e:')

['e:zqlj.jpg']

pil_im.thumbnail((128,128))

pil_im

pil_im = Image.open('zqlj.jpg')

pil_im

box = (100,100,400,400)region = pil_im.crop(box)region = region.transpose(Image.ROTATE_180)pil_im.paste(region,box)

pil_im

out = pil_im.rotate(45)out

from PIL import Imagefrom pylab import *# 读取图像到数组中im = array(Image.open('zqlj.jpg'))#绘制图像imshow(im)#一些点x = [100,100,400,400]y = [200,500,200,500]#使用红色星状标记绘制点plot(x,y,'r*')#绘制连接前两个点的线plot(x[:2],y[:2])#添加标题，显示绘制的图像title('Plotting: "zqlj.jpg')#使坐标轴不显示axis('off')show()

from PIL import Imagefrom pylab import *#读取图像到数组中im = array(Image.open('zqlj.jpg').convert('L'))#新建一个图像figure()#不使用颜色信息gray()#在原点的左上角显示轮廓图像contour(im,origin='image')axis('equal')axis('off')

(0.5, 1279.5, 0.5, 852.5)

#绘制灰度直方图figure()hist(im.flatten(),128)show()

#交互式标注from PIL import Imagefrom pylab import *im = array(Image.open('zqlj.jpg'))imshow(im)print 'Please click 3 points'x = ginput(3)print 'you clicked:',xshow()

Please click 3 pointsF:\anaconda\lib\site-packages\matplotlib\figure.py:402: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure  "matplotlib is currently using a non-GUI backend, "---------------------------------------------------------------------------NotImplementedError                       Traceback (most recent call last)<ipython-input-40-43377ba2cd7b> in <module>()      6 imshow(im)      7 print 'Please click 3 points'----> 8 x = ginput(3)      9 print 'you clicked:',x     10 show()F:\anaconda\lib\site-packages\matplotlib\pyplot.pyc in ginput(*args, **kwargs)    710     If *timeout* is negative, does not timeout.    711     """--> 712     return gcf().ginput(*args, **kwargs)    713     714 F:\anaconda\lib\site-packages\matplotlib\figure.pyc in ginput(self, n, timeout, show_clicks, mouse_add, mouse_pop, mouse_stop)   1667                                                   mouse_stop=mouse_stop)   1668         return blocking_mouse_input(n=n, timeout=timeout,-> 1669                                     show_clicks=show_clicks)   1670    1671     def waitforbuttonpress(self, timeout=-1):F:\anaconda\lib\site-packages\matplotlib\blocking_input.pyc in __call__(self, n, timeout, show_clicks)    292         self.clicks = []    293         self.marks = []--> 294         BlockingInput.__call__(self, n=n, timeout=timeout)    295     296         return self.clicksF:\anaconda\lib\site-packages\matplotlib\blocking_input.pyc in __call__(self, n, timeout)    115         try:    116             # Start event loop--> 117             self.fig.canvas.start_event_loop(timeout=timeout)    118         finally:  # Run even on exception like ctrl-c    119             # Disconnect the callbacksF:\anaconda\lib\site-packages\matplotlib\backend_bases.pyc in start_event_loop(self, timeout)   2412         This is implemented only for backends with GUIs.   2413         """-> 2414         raise NotImplementedError   2415    2416     def stop_event_loop(self):NotImplementedError: 

from PIL import Imagefrom numpy import *im = array(Image.open('zqlj.jpg').convert('L'))im2 = 255 - im #对图像进行反相处理im3 = (100.0/255) * im +100 #将图像像素值变换到100...200区间im4 = (255.0) * (im / 255.0)**2 #对图像像素值求平方后的图像print int(im.min()),int(im.max())figure()imshow(im2)figure()imshow(im3)figure()imshow(im4)show()

0 255

pil_im3 = Image.fromarray(uint8(im3))

pil_im3

def imresize(im,sz):    """使用PIL对象重新定义图像数组的大小"""    pil_im = Image.fromarray(uint8(im))    return array(pil_im.resize(sz))

def isteq(im,nbr_bins=256):    '''对一幅灰度图像进行直方图均衡化'''    #计算图像的直方图    imhist,bins = histogram(im.flatten(),nbr_bins,normed=True)    cdf = imhist.cumsum() # cumulative distribution function    cdf = 255*cdf / cdf[-1] #归一化    #使用累积分布函数的线性插值，计算新的像素值    im2 =interp(im.flatten(),bins[:-1],cdf)    return im2.reshape(im.shape),cdf

#图像平均def compute_average(imlist):    '''计算图像列表的平均图像'''    #打开第一幅图像，将其存储在浮点型数组中    averageim = array(Image.open(imlist[0]),'f')    for imname in imlist[1:]:        try:            averageim += array(Image.open(imname))        except:            print imname + '...skipped'    averageim /= len(imlist)    # 返回uint8类型的平均图像    return array(averageim,'uint8')