添加image similarity

1 files changed, 92 insertions, 0 deletions

diff --git a/cv/image_similarity/dhash_detect.py b/cv/image_similarity/dhash_detect.py
new file mode 100644
index 0000000..5b68aa2
--- /dev/null
+++ b/cv/image_similarity/dhash_detect.py
@@ -0,0 +1,92 @@
+
+
+from PIL import Image
+import numpy as np
+import imagehash
+
+
+def image_to_dhash(image_path, hash_size=8):
+    image = Image.open(image_path)
+    # grey, resize: 9*8
+    image = image.convert('L').resize((hash_size+1, hash_size), Image.ANTIALIAS)
+    pixels = np.asarray(image)
+    diff = pixels[:, 1:] > pixels[:, :-1]
+    # dhash = sum(2**(i%8) for i, v in enumerate(diff.flatten()) if v)
+    return diff
+
+# def image_to_phash():
+
+
+def binary_to_hex(arr):
+    bit_str = ''.join(str(b) for b in 1*arr.flatten())
+    print(bit_str)
+    width = int(np.ceil(len(bit_str)/4))
+    return '{:0>{width}x}'.format(int(bit_str, 2), width=width)
+
+
+def hamming_distance(dhash1, dhash2, f=64):
+    if isinstance(dhash1, str):
+        dhash1 = int(dhash1, base=16)
+    if isinstance(dhash2, str):
+        dhash2 = int(dhash2, base=16)
+    x = (dhash1 ^ dhash2) & ((1 << f) - 1)
+    # 数1的个数
+    ans = 0
+    while x:
+        ans += 1
+        x &= x-1
+    return ans
+
+
+def hamming_dist(dhash1, dhash2):
+    difference = (int(dhash1, 16)) ^ (int(dhash2, 16))
+    return bin(difference).count("1")
+
+
+def hash_functions_eval(hash_function=imagehash.dhash):
+    lena_1 = hash_function(Image.open('./imgs/lena/origin-lena.png'))
+    lena_2 = hash_function(Image.open('./imgs/lena/blur-lena.png'))
+    lena_3 = hash_function(Image.open('./imgs/lena/resize-lena.png'))
+    lena_4 = hash_function(Image.open('./imgs/lena/shift-lena.png'))
+    forest = hash_function(Image.open('./imgs/forest-high.jpg'))
+
+    hashs = [lena_1, lena_2, lena_3, lena_4, forest]
+    for i in range(len(hashs)):
+        for j in range(i + 1, len(hashs)):
+            print(hash_function.__name__, i, j, hashs[i] - hashs[j])
+
+
+def rotate_eval(img_path='./imgs/lena/origin-lena.png', hash_function=imagehash.dhash):
+    origin_image = Image.open(img_path)
+    origin_hash = hash_function(origin_image)
+    for r in range(1, 180, 10):
+        rotate_hash = hash_function(origin_image.rotate(r))
+        print(hash_function.__name__, r, origin_hash - rotate_hash)
+
+
+if __name__ == '__main__':
+    # hash_functions_eval(imagehash.average_hash)
+    # print('----------------------')
+    #
+    # hash_functions_eval(imagehash.phash)
+    # print('----------------------')
+    #
+    # hash_functions_eval(imagehash.dhash)
+    # print('----------------------')
+    #
+    # hash_functions_eval(imagehash.whash)
+
+    rotate_eval(hash_function=imagehash.phash)
+
+class Solution:
+    def str_to_hex(self, s):
+        return ''.join([hex(ord(c)).replace('0x', '') for c in s])
+    def toHexspeak(self, num: str) -> str:
+        h = self.str_to_hex(num)
+        h = h.replace('1', 'I').replace('0', 'O')
+        s = '23456789'
+        for c in s:
+            if c in h:
+                return "ERROR"
+        return h
+Solution().toHexspeak("257")