Update app.py

app.py

@@ -13,8 +13,10 @@ tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
 
 
 def calculate_ssim(img1, img2):
-    img1_gray = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
-    img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+    img1_resized = cv2.resize(img1, (img2.shape[1], img2.shape[0]))
+    img2_resized = cv2.resize(img2, (img1.shape[1], img1.shape[0]))
+    img1_gray = cv2.cvtColor(img1_resized, cv2.COLOR_BGR2GRAY)
+    img2_gray = cv2.cvtColor(img2_resized, cv2.COLOR_BGR2GRAY)
     return ssim(img1_gray, img2_gray)
 
 
@@ -35,12 +37,9 @@ def calculate_text_similarity(text1, text2):
 
 
 def calculate_color_similarity(img1, img2):
-    img1_lab = cv2.cvtColor(img1, cv2.COLOR_BGR2Lab)
-    img2_lab = cv2.cvtColor(img2, cv2.COLOR_BGR2Lab)
-
-    color_similarity = ssim(img1_lab, img2_lab, multichannel=True)
-
-    return color_similarity
+    hist1 = cv2.calcHist([img1], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
+    hist2 = cv2.calcHist([img2], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
+    return cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
 
 
 def compare_trademarks(trademark1, trademark2):