Update app.py

app.py

@@ -44,21 +44,21 @@ HTML="""
 """
 
 DESCRIPTION="""Welcome to our video retrieval demo powered by [Searchium-ai/clip4clip-webvid150k](https://huggingface.co/Searchium-ai/clip4clip-webvid150k)! <br>
-               Using free text search - you will find the top 5 most relevant clips among a dataset of 1.5 million video clips. <br>
+               Using free text search - you will find the top 5 most relevant clips among a dataset of 5.5 million video clips. <br>
                Discover, explore, and enjoy the world of video search at your fingertips.
                """
 ENDING = """For search acceleration capabilities, please refer to [Searchium.ai](https://www.searchium.ai)
             """
 
 
-DATA_PATH = './data'
+DATA_PATH = './new_data'
 
-ft_visual_features_file = DATA_PATH + '/dataset_v1_visual_features_database.npy'
+ft_visual_features_file = DATA_PATH + '/video_dataset_visual_features_database.npy'
 
 #load database features:
 ft_visual_features_database = np.load(ft_visual_features_file)
 
-database_csv_path = os.path.join(DATA_PATH, 'dataset_v1.csv')
+database_csv_path = os.path.join(DATA_PATH, 'half_video_dataset.csv')
 database_df = pd.read_csv(database_csv_path)
 
 class NearestNeighbors:
@@ -115,6 +115,7 @@ class NearestNeighbors:
                     
 model = CLIPTextModelWithProjection.from_pretrained("Searchium-ai/clip4clip-webvid150k")
 tokenizer = CLIPTokenizer.from_pretrained("Searchium-ai/clip4clip-webvid150k")
+
 nn_search = NearestNeighbors(n_neighbors=5, metric='binary', rerank_from=100)
 nn_search.fit(np.packbits((ft_visual_features_database > 0.0).astype(bool), axis=1), o_data=ft_visual_features_database)