Update app.py

app.py

@@ -1,15 +1,8 @@
-import cv2
 import numpy as np
 from skimage.metrics import structural_similarity as ssim
 import gradio as gr
 
 # Function to calculate SSIM between two images
-def calculate_similarity(img1, img2):
-    img1 = cv2.cvtColor(img1, cv2.COLOR_RGB2GRAY)
-    img2 = cv2.cvtColor(img2, cv2.COLOR_RGB2GRAY)
-    return ssim(img1, img2)
-
-# Function to compute similarity scores for all images
 def calculate_similarity(img1, img2):
     if len(img1.shape) == 2:
         img1 = cv2.cvtColor(img1, cv2.COLOR_GRAY2RGB)
@@ -17,12 +10,19 @@ def calculate_similarity(img1, img2):
         img2 = cv2.cvtColor(img2, cv2.COLOR_GRAY2RGB)
     return ssim(img1, img2)
 
+# Function to compute similarity scores for all images
+def compute_similarity(target_image, image_list):
+    scores = []
+    for image in image_list:
+        similarity_score = calculate_similarity(target_image, image)
+        scores.append(similarity_score)
+    return scores
 
 # Function to handle the Gradio interface
 def image_similarity(target_image, image_list):
     target_image = target_image.astype(np.uint8)
     image_list = [image.astype(np.uint8) for image in image_list]
-    scores = calculate_similarity(target_image, image_list)
+    scores = compute_similarity(target_image, image_list)
     results = list(zip(image_list, scores))
     results.sort(key=lambda x: x[1], reverse=True)  # Sort by similarity score
     return [str(result) for result in results]
@@ -40,4 +40,4 @@ iface = gr.Interface(
 )
 
 # Launch the interface
-iface.launch()
+iface.launch()