add image hash funcs

khandy/image/__init__.py

@@ -1,6 +1,7 @@
 from .align_and_crop import *
 from .crop_or_pad import *
 from .flip import *
+from .image_hash import *
 from .resize import *
 from .rotate import *
 from .translate import *

khandy/image/image_hash.py

@@ -0,0 +1,47 @@
+import cv2
+import numpy as np
+
+
+def calc_image_ahash(image):
+    if image.ndim == 3:
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    resized = cv2.resize(image, (8, 8))
+
+    meanval = cv2.mean(resized)[0]
+    hashval = int(0)
+    for i in range(8):
+        for j in range(8):
+            mask = int(resized[i,j] - meanval >= 1e-5)
+            hashval |= mask << (i * 8 + j)
+    return hashval
+
+    
+def calc_image_phash(image):
+    if image.ndim == 3:
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    resized = cv2.resize(image, (32, 32))
+
+    dft = cv2.dft(resized.astype(np.float32))
+    meanval = cv2.mean(dft[:8,:8])[0]
+    hashval = int(0)
+    for i in range(8):
+        for j in range(8):
+            mask = int(dft[i,j] - meanval >= 1e-5)
+            hashval |= mask << (i * 8 + j)
+    return hashval
+
+    
+def calc_image_dhash(image):
+    if image.ndim == 3:
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    resized = cv2.resize(image, (9, 8))
+
+    hashval = int(0)
+    for i in range(8):
+        for j in range(8):
+            mask = int(resized[i,j] > resized[i,j+1])
+            hashval |= mask << (i * 8 + j)
+    return hashval
+    
+    
+