def transform(im, flag=True):
'''
将传入的图片进行预处理：对图像进行图像缩放和数据增强
Args:
im : 传入的待处理的图片
Return：
graph : 返回经过预处理的图片
#random.uniform(a, b)随机产生[a, b)之间的一个浮点数
'''
#便历数组
graph=np.zeros(graphSize[1]*graphSize[0]*1).reshape(graphSize[0],graphSize[1],1)
deltaX=0
deltaY=0
ratio=1.464
if flag:
lowerRatio=max(1.269,im.size[1]*1.0/graphSize[0],im.size[0]*1.0/graphSize[1])
upperRatio=max(lowerRatio,2.0)
ratio=random.uniform(lowerRatio,upperRatio)
deltaX=random.randint(0,int(graphSize[0]-im.size[1]/ratio))
deltaY=random.randint(0,int(graphSize[1]-im.size[0]/ratio))
else:
ratio=max(1.464,im.size[1]*1.0/graphSize[0],im.size[0]*1.0/graphSize[1])
deltaX=int(graphSize[0]-im.size[1]/ratio)>>1
deltaY=int(graphSize[1]-im.size[0]/ratio)>>1
height=int(im.size[1]/ratio)
width=int(im.size[0]/ratio)
data = im.resize((width,height),Image.ANTIALIAS).getdata()
data = 1-np.asarray(data,dtype='float')/255.0
data = data.reshape(height,width)
graph[deltaX:deltaX+height,deltaY:deltaY+width,0]=data
return graph
https://blog.csdn.net/searobbers_duck/article/details/70847427