Update app.py

app.py

@@ -446,7 +446,7 @@ def process_hdf5_file(uploaded_file, percentage):
 
         # Step 5: Load the HDF5 file and extract the channels and labels
         with h5py.File(uploaded_file.name, 'r') as f:
-            channels = np.array(f['channels'])  # Assuming 'channels' dataset in the HDF5 file
+            channels = np.array(f['channels']).float()  # Assuming 'channels' dataset in the HDF5 file
             labels = np.array(f['labels'])  # Assuming 'labels' dataset in the HDF5 file
         print(f"Loaded dataset with {channels.shape[0]} samples.")
 
@@ -455,7 +455,7 @@ def process_hdf5_file(uploaded_file, percentage):
         #print(preprocessed_chs[0][0][1])
 
         # Step 7: Perform inference using the functions from inference.py
-        output_emb = inference.lwm_inference(preprocessed_chs.float(), 'cls_emb', model)
+        output_emb = inference.lwm_inference(preprocessed_chs, 'cls_emb', model)
         output_raw = inference.create_raw_dataset(preprocessed_chs, device)
 
         print(f"Output Embeddings Shape: {output_emb.shape}")