Update app.py

app.py

@@ -200,14 +200,18 @@ if picture is not None:
     ## Create DataLoader for Webcam Image
     webcam_ds = dataset_prod_obj.create_dataset(picture, webcam=True)
     webcam_dl = DataLoader(webcam_ds, batch_size=BATCH_SIZE)
+
+    # Testing the dataloader
+    prod_inputs = next(iter(webcam_dl))
+    st.write(prod_inputs['pixel_values'].shape)
     
     ## Run the predictions
-    prediction = prod_function(model_pretrained, prod_dl, webcam_dl)
-    predictions = torch.cat(prediction, 0).to(device)
-    match_idx = torch.argmin(predictions)
+    #prediction = prod_function(model_pretrained, prod_dl, webcam_dl)
+    #predictions = torch.cat(prediction, 0).to(device)
+    #match_idx = torch.argmin(predictions)
 
     ## Display the results
-    if predictions[match_idx] <= 0.3:
-      st.write('Welcome: ',image_paths[match_idx].split('/')[-1].split('.')[0])
-    else:
-      st.write("Match not found")
+    #if predictions[match_idx] <= 0.3:
+    #  st.write('Welcome: ',image_paths[match_idx].split('/')[-1].split('.')[0])
+    #else:
+    #  st.write("Match not found")