blind_watermark.py 文件源码

def inner_extract(self,B,signature):
        sig_size=np.int(np.sqrt(len(signature)))
        size = self.size

        ext_sigs =[] 
        #???????????????
        #???????????????????????
        #  (0,0)    (0,w-32)
        #  (h-32,0)    (h-32,w-32)
        w ,h = B.shape
        embed_pos =[(0,0)]
        embed_pos.append((w-sig_size*size,0))
        embed_pos.append((0,h-sig_size*size))
        embed_pos.append((w-sig_size*size,h-sig_size*size))

        for x,y in embed_pos:
            ext_sig = np.zeros(len(signature),dtype=np.int)

            for i in range(x,x+sig_size*size,size):
                for j in range(y,y+sig_size * size,size):
                    v = cv2.dct(np.float32(B[i:i+size,j:j+size]))
                    if v[size-1,size-1] > self.Q/2:
                        ext_sig[((i-x)//size)*sig_size+(j-y)//size] = 1 


            ext_sigs.append(ext_sig)
            ext_sig_arr = np.array(ext_sig).reshape((sig_size,sig_size))
            ext_sigs.append(np.rot90(ext_sig_arr,1).flatten())
            ext_sigs.append(np.rot90(ext_sig_arr,2).flatten())
            ext_sigs.append(np.rot90(ext_sig_arr,3).flatten())

        return ext_sigs