Update app.py

app.py

@@ -3,26 +3,52 @@ import cv2
 import numpy as np
 from skimage.metrics import structural_similarity as ssim
 from PIL import Image
-import io
+import pytesseract
+import matplotlib.pyplot as plt
 
 # Function to calculate SSIM between two images
 def calculate_ssim(img1, img2):
     img1_gray = img1.convert("L")
     img2_gray = img2.convert("L")
-    # Resize images to a common size
     img1_resized = img1_gray.resize((256, 256))
     img2_resized = img2_gray.resize((256, 256))
     return ssim(np.array(img1_resized), np.array(img2_resized))
 
+# Function to extract text from an image
+def extract_text(image):
+    text = pytesseract.image_to_string(image)
+    return text
+
+# Function to calculate color difference between two images
+def calculate_color_difference(img1, img2):
+    hist1 = cv2.calcHist([np.array(img1)], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
+    hist2 = cv2.calcHist([np.array(img2)], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
+    return cv2.compareHist(hist1, hist2, cv2.HISTCMP_CHISQR)
+
 # Function to compare two trademarks
 def compare_trademarks(trademark1, trademark2):
     ssim_score = calculate_ssim(trademark1, trademark2)
-    return ssim_score
+    text1 = extract_text(trademark1)
+    text2 = extract_text(trademark2)
+    text_similarity = calculate_text_similarity(text1, text2)
+    color_difference = calculate_color_difference(trademark1, trademark2)
+    return ssim_score, text_similarity, color_difference
+
+# Function to calculate text similarity ratio
+def calculate_text_similarity(text1, text2):
+    if text1 == "" or text2 == "":
+        return 0.0
+    text1 = text1.lower()
+    text2 = text2.lower()
+    intersection = len(set(text1.split()) & set(text2.split()))
+    union = len(set(text1.split()) | set(text2.split()))
+    return intersection / union
 
 # Function to handle the Gradio interface
 def prevent_trademark_conflict(trademark1, trademark2):
-    similarity_score = compare_trademarks(trademark1, trademark2)
-    return similarity_score
+    ssim_score, text_similarity, color_difference = compare_trademarks(trademark1, trademark2)
+    result = f"SSIM Score: {ssim_score:.2f}\nText Similarity: {text_similarity:.2f}\nColor Difference: {color_difference:.2f}"
+    return result
 
 # Prepare Gradio interface
 iface = gr.Interface(