简单图像处理（图片->二进制->图片） - 好文

* #coding=utf-8
*
* '''''
* 1-将图片转化为数组并存为二进制文件
* 2-从二进制文件中读取数并重新恢复为图片
* '''
*
* from __future__ import print_function
* import numpy
* import PIL.Image
* import pickle
* import matplotlib.pyplot
* import pdb
*
* class Operation(object):
*     image_base_path = "../image/"
*     data_base_path = "../data/"
*
*     def image_to_array(self,filenames):
*         """
*         将图片转化为数组并存为二进制文件
*         """
*         n = filenames.__len__()#获取图片个数
*         result = numpy.array([]) #创建一个空的一维数组
*         print("开始将图片转化为数组")
*         for i in range(n):
*             image = PIL.Image.open(self.image_base_path+filenames[i])
*             r,g,b = image.split() # rgb通道分离
*             # 注意：下面一定要reshpae(1024)使其变为一维数组，否则拼接的数据会出现错误，导致无法恢复图片
*             r_arr = numpy.array(r).reshape(1024)
*             g_arr = numpy.array(g).reshape(1024)
*             b_arr = numpy.array(b).reshape(1024)
*             # 行拼接，类似于接火车；最终结果：共n行，一行3072列，为一张图片的rgb值
*             image_arr = numpy.concatenate((r_arr,g_arr,b_arr))
*             result = numpy.concatenate((result,image_arr))
*
*         result = result.reshape(n,3072) # 将一维数组转化为n行3072列的二维数组
*         print("转化数组over，开始保存为文件")
*         file_path = self.data_base_path + 'data2.bin'
*         with open(file_path,mode='wb') as f:
*             pickle.dump(result,f)
*         print("保存成功")
*
*     def array_to_image(self,filename):
*         '''''
*         从二进制文件中读取数据并重新恢复为图片
*         '''
*         with open(self.data_base_path + filename,mode='rb') as f:
*             arr = pickle.load(f) #加载并反序列化数据
*         rows = arr.shape[0] #rows=5
*         #pdb.set_trace()
*         #print("rows:",rows)
*         arr = arr.reshape(rows,3,32,32)
*         print(arr)<span style="white-space:pre;">   </span>#打印数组
*         for index in range(rows):
*             a = arr[index]
*             #得到RGB通道
*             r = PIL.Image.fromarray(a[0]).convert('L')
*             g = PIL.Image.fromarray(a[1]).convert('L')
*             b = PIL.Image.fromarray(a[2]).convert('L')
*             image = PIL.Image.merge("RGB",(r,g,b))
*             #显示图片
*             matplotlib.pyplot.imshow(image)
*             matplotlib.pyplot.show()
*
#image.save(self.image_base_path + "result" + str(index) + ".png",'png')
*
* if __name__ == "__main__":
*     my_operator = Operation()
*     images = []
*     for j in range(5):
*         images.append(str(j) + ".png")
* #   my_operator.image_to_array(images)
*     my_operator.array_to_image('data2.bin')

热门工具换一换