Final VPR App

.gitignore

@@ -1 +0,0 @@
-model1.pt

app.py

@@ -66,6 +66,15 @@ def main():
         
         # similar_image_ids = get_similar_images(temp_image_path)
 
+        target_size = (224, 280)  # Size to resize the images
+
+        search_image = read_image(temp_image_path)
+
+        resized_search_image = Image.fromarray(search_image).resize(target_size)
+                    
+        st.image(resized_search_image, caption="Input Image", use_column_width=False)
+
+
         client = Client("https://thenujan-vpr-deploy.hf.space/")
         result = client.predict(
                         "https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png",	# str (filepath or URL to image) in 'image' Image component
@@ -91,7 +100,7 @@ def main():
         end_idx = min(start_idx + images_per_page, len(similar_image_ids))
 
         images_per_row = 4
-        target_size = (256, 224)  # Size to resize the images
+        # target_size = (256, 224)  # Size to resize the images
 
         for i in range(start_idx, end_idx, images_per_row):
             row_images = similar_image_paths[i:i + images_per_row]

similarity_search.py

@@ -95,22 +95,13 @@ def Model():
     return backbone
 
 def find(img_path):
-    # img_path = '/kaggle/input/vprtestdata/public_dataset/queries/abiding-inchworm-of-ultimate-freedom.jpeg'
 
     image = read_image(img_path)
 
     image = transform_img(image)
 
-    print('1!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
-
     image = image.unsqueeze(dim=0)
 
-    print('2!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
-
-    print(image.shape)
-
-    print('3!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!\n')
-
     feature_vectors_gallery = np.load('./VPR image similarity search/gallary_embedding/feature_vectors_gallery.npy')
 
     model = Model()