简单图像处理（图片->二进制->图片）_用rgb通道计算二进制图片数据生成图片-优快云博客

#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')