Update src/app.py

src/app.py

@@ -1,6 +1,7 @@
 from colordescriptor import ColorDescriptor
 from CLIP import CLIPImageEncoder
 from LBP import LBPImageEncoder
+from helper import chi2_distance, euclidian_distance
 import gradio as gr
 import os
 import cv2
@@ -50,6 +51,12 @@ def check_index(ds):
         return index_dataset(ds)
 
 
+def find_similar_images(method):
+    if method == "FAISS":
+        
+    return retrieved examples
+    
+
 dataset_with_embeddings = check_index(candidate_subset)
 
 # Main function, to find similar images
@@ -69,8 +76,16 @@ def get_neighbors(query_image, selected_descriptor, top_k=5):
         cd = ColorDescriptor((8, 12, 3))
         qi_embedding = cd.describe(query_image)
         qi_np = np.array(qi_embedding)
-        scores, retrieved_examples = dataset_with_embeddings.get_nearest_examples(
-            'color_embeddings', qi_np, k=top_k)
+        if distance_measure == "FAISS":
+            scores, retrieved_examples = dataset_with_embeddings.get_nearest_examples(
+                'color_embeddings', qi_np, k=top_k)
+        elif distance_measure == "Chi-squared":
+            tmp_dataset = dataset_with_embeddings.map(lambda row: {'distance': chi2_distance(histA=query_vector, histB=row['color_embeddings'])})
+            retrieved_examples = tmp_dataset.sort("distance")
+        else: 
+            tmp_dataset = dataset_with_embeddings.map(lambda row: {'distance': euclidian_distance(histA=query_vector, histB=row['color_embeddings'])})
+            retrieved_examples = tmp_dataset.sort("distance")
+  
         images = retrieved_examples['image'] #retrieved images is a dict, with images and embeddings
         return images
     if "CLIP" == selected_descriptor:
@@ -126,17 +141,6 @@ with gr.Blocks() as demo:
     )
     btn.click(get_neighbors, inputs=[image_input, descr_dropdown], outputs=[gallery_output])
 
-    # gr.Markdown(
-    # """
-    # ## Upload your own data to the CBIR
-    # WARNING! Please be aware, that what you are uploading here, will be public to anyone.
-    # Don't upload images for which you don't have the rights to do so.
-    # """)
-
-    # file_output = gr.File()
-    # upload_button = gr.UploadButton("Click to upload a file", file_types=["image"], file_count="multiple")
-    # upload_button.upload(upload_file, upload_button, file_output)
-
 
 if __name__ == "__main__":
     demo.launch()