Update src/app.py

src/app.py

@@ -22,7 +22,7 @@ def index_dataset(dataset):
 
     print("LBP Embeddings")
     lbp_model = LBPImageEncoder(8,2)
-    dataset_with_embeddings = dataset_with_embeddings.map(lambda row: {'lbp_embeddings': lbp_model.preprocess_img(row["image"])})
+    dataset_with_embeddings = dataset_with_embeddings.map(lambda row: {'lbp_embeddings': lbp_model.describe(row["image"])})
 
     # Add index
     dataset_with_embeddings.add_faiss_index(column='color_embeddings')
@@ -78,7 +78,7 @@ def get_neighbors(query_image, selected_descriptor, top_k=5):
         return images
     if "LBP" in selected_descriptor:
         lbp_model = LBPImageEncoder(8,2)
-        qi_embedding = lbp_model.preprocess_img(query_image)
+        qi_embedding = lbp_model.describe(query_image)
         scores, retrieved_examples = dataset_with_embeddings.get_nearest_examples(
             'lbp_embeddings', qi_embedding, k=top_k)
         images = retrieved_examples['image']