云计算期末大作业 论文图像复用的机器自动检查 魏如蓝 10172100262
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36 regels
883 B

# 正则化图像
def regularizeImage(img, size = (9, 8)):
return img.resize(size).convert('L')
# 计算hash值
def getHashCode(img, size = (9, 8)):
result = []
for i in range(size[0] - 1):
for j in range(size[1]):
current_val = img.getpixel((i, j))
next_val = img.getpixel((i + 1, j))
if current_val > next_val:
result.append(1)
else:
result.append(0)
return result
# 比较hash值
def compHashCode(hc1, hc2):
cnt = 0
for i, j in zip(hc1, hc2):
if i == j:
cnt += 1
return cnt
# 计算差异哈希算法相似度
def caldHashSimilarity(img1, img2):
img1 = regularizeImage(img1)
img2 = regularizeImage(img2)
hc1 = getHashCode(img1)
hc2 = getHashCode(img2)
return compHashCode(hc1, hc2)
__all__ = ['caldHashSimilarity']