Update app.py

app.py

@@ -74,11 +74,11 @@ def download_img(identifier, url):
 def predict(image=None, text=None, sketch=None):
     if image is not None:
         input_embeddings = compute_image_embeddings([load_image(image)]).detach().numpy()
-        topk = {"local": 100}
+        topk = {"local": 1}
     else:
         if text:
             query = text
-            topk = {text: 100}
+            topk = {text: 1}
         else:
             x = torch.tensor(sketch, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.
             with torch.no_grad():
@@ -86,7 +86,7 @@ def predict(image=None, text=None, sketch=None):
             probabilities = torch.nn.functional.softmax(out[0], dim=0)
             values, indices = torch.topk(probabilities, 5)
             query = LABELS[indices[0]]
-            topk = {LABELS[i]: v.item() for i, v in zip(indices, values)}
+            topk = {LABELS[i]: v.item() / 100.0 for i, v in zip(indices, values)}
         input_embeddings = compute_text_embeddings([query]).detach().numpy()
 
     n_results = 3