update

app.py

@@ -47,7 +47,7 @@ After completing the previous steps, your channels will be aligned with the temp
 - In case there are still some channels that haven't been mapped, we will automatically batch and optimally assign them to the template. This ensures that even channels not initially mapped will still be included in the final result.
 - Once the mapping process is completed, a JSON file containing the mapping result will be generated. This file is necessary only if you plan to run the models using the <a href="https://github.com/CNElab-Plus/ArtifactRemovalTransformer">source code</a>; otherwise, you can ignore it.
 
-## 2. Decode data
+## 2. Data Denoising
 After clicking on ``Run`` button, we will process your EEG data based on the mapping result. If necessary, your data will be divided into batches and run the models on each batch sequentially, ensuring that all channels are properly processed.
 """
 
@@ -271,7 +271,7 @@ with gr.Blocks(js=js, delete_cache=(3600, 3600)) as demo:
 			# -----------------------------------------------
 		
 		with gr.Column(variant="panel"):
-			gr.Markdown("# 2.Decode Data")
+			gr.Markdown("# 2.Data Denoising")
 			# ---------------------input---------------------
 			with gr.Row():
 				in_data_file = gr.File(label="Raw data (.csv)", file_types=[".csv"])
@@ -789,7 +789,7 @@ with gr.Blocks(js=js, delete_cache=(3600, 3600)) as demo:
 	)
 	
 	# +========================================================================================+
-	# |                                  Stage2: decode data                                   |
+	# |                                  Stage2: data denoising                                   |
 	# +========================================================================================+
 	@cancel_btn.click(inputs = stage2_json, outputs = [stage2_json, cancel_btn, batch_md])
 	def stop_stage2(stage2_info):