path filename

app.py

@@ -40,6 +40,7 @@ def initialize_huggingface():
 def load_model_and_data():
     print("Loading everything...")
     dataset = load_dataset("CHSTR/ecommerce")
+    print(dataset['validation']['image'][0].filename)
     path_images = "/".join(dataset['validation']
                            ['image'][0].filename.split("/")[:-3]) + "/"
 
@@ -81,7 +82,7 @@ def compute_sketch(_sketch, model):
 def image_search(_query, corpus, model, embeddings, n_results=N_RESULTS):
     query_embedding = compute_sketch(_query, model)
     corpus_id = 0 if corpus == "Unsplash" else 1
-    image_features = torch.tensor(
+    image_features = torch.from_numpy(
         [item[0] for item in embeddings[corpus_id]]).to(device)
 
     dot_product = (image_features @ query_embedding.T)[:, 0]