update app.py

app.py

@@ -2,23 +2,42 @@ import gradio as gr
 import numpy as np
 import os
 import utils
-from pathlib import Path
+import channel_mapping
 
-def test(csv_file):
-    tmp_filepath = str(Path(str(csv_file)).parent)
+def test(model_name, csv_file, chanloc_file):
+    #print('model:[', model_name, ']')
+    tmp_path = os.path.dirname(str(csv_file))
+    
+    input_data_name = os.path.basename(str(csv_file))
+    output_data_name = os.path.splitext(input_data_name)[0]+'_'+model_name+'.csv'
+    #print('in_data_name:[', input_data_name, ']')
+    #print('out_data_name:[', output_data_name, ']')
+    
+    # Channel mapping
+    input_loc_name = os.path.basename(str(chanloc_file))
+    #print('in_loc_name:[', input_loc_name, ']')
+    
     
     # step1: Data preprocessing
-    total_file_num = utils.preprocessing(csv_file, 256)
+    total_file_num = utils.preprocessing(tmp_path, input_data_name, 256)
     
     # step2: Signal reconstruction
-    utils.reconstruct("EEGART", total_file_num, tmp_filepath, "EEGART_test.csv")
+    utils.reconstruct(model_name, total_file_num, tmp_path, output_data_name)
     
-    return tmp_filepath+"/EEGART_test.csv"
+    return tmp_path+'/'+output_data_name
+
+input_data = gr.File(label="CSV file", file_types=[".csv"])
+input_loc = gr.File(label="Channel location", file_types=[".loc", "locs"])
+input_model_name = gr.Dropdown(choices=["ICUNet", "UNetpp", "AttUnet", "EEGART"],
+                                value="ICUNet",
+                                label="model")
+
+inputs = [input_model_name, input_data, input_loc]
 
 app = gr.Interface(fn=test,
-                   inputs=gr.File(label="CSV file", file_types=[".csv"]),
+                   inputs=inputs,
                    outputs=gr.File(),
                    allow_flagging="never")
 
 if __name__ == "__main__":
-    app.launch()
+    app.launch(server_name="0.0.0.0", server_port=7859, share=False)