update

app.py

@@ -18,8 +18,8 @@ This tool is designed to assist you with two main tasks:
 ## 1. Channel Mapping
 The following steps will guide you through the process of mapping your EEG channels to our template channels.
 
-### Step1: Initial Matching and Rescaling
-After clicking on ``Mapping`` button, we will first match your channels to our template channels by their names. Using the matched channels as reference points, we will apply Thin Plate Spline (TPS) transformation to rescale your montage to align with our template's scale. The template montage and your rescaled montage will be displayed side by side for comparison. Channels that do not have a match in our template will be **highlighted in red**.
+### Step1: Initial Matching and Scaling
+After clicking on ``Mapping`` button, we will first match your channels to our template channels by their names. Using the matched channels as reference points, we will apply Thin Plate Spline (TPS) transformation to scale your montage to align with our template's dimensions. The template montage and your scaled montage will be displayed side by side for comparison. Channels that do not have a match in our template will be **highlighted in red**.
 - If your data includes all the 30 template channels, you will see the **Mapping Results**.
 - If your data doesn't include all the 30 template channels and you have some channels that do not match the template, you will be directed to **Step2**.
 - If all your channels are included in our template but you have fewer than 30 channels, you will be directed to **Step3**.
@@ -227,66 +227,65 @@ with gr.Blocks() as demo:
 	with gr.Row():
 
 		with gr.Column():
-			# ------------------------input--------------------------
 			with gr.Row(variant='panel'):
 				with gr.Column():
 					gr.Markdown("# 1.Channel Mapping")
+					# --------------------input----------------------
 					in_loc_file = gr.File(label="Channel locations (.loc, .locs, .xyz, .sfp, .txt)",
 									file_types=[".loc", "locs", ".xyz", ".sfp", ".txt"])
+					map_btn = gr.Button("Mapping")
+					# -------------------mapping---------------------
+					desc_md = gr.Markdown(visible=False)
+					# step1 : initial matching and scaling
 					with gr.Row():
-						in_samplerate = gr.Textbox(label="Sampling rate (Hz)", scale=2)
-						map_btn = gr.Button("Mapping", scale=1)
-			# ------------------------mapping------------------------
-			desc_md = gr.Markdown(visible=False)
-			# step1 : initial matching and rescaling
-			with gr.Row():
-				tpl_img = gr.Image("./template_montage.png", label="Template channels", visible=False)
-				mapped_img = gr.Image(label="Input channels", visible=False)
-			# step2 : forward unmatched input channels to empty template channels
-			radio_group = gr.Radio(elem_id="radio-group", visible=False)
-			# step3 : fill the remaining template channels
-			with gr.Row():
-				in_fillmode = gr.Dropdown(choices=["mean", "zero"],
-											value="mean",
-											label="Filling method",
-											visible=False,
-											scale=2)
-				fillmode_btn = gr.Button("OK", visible=False, scale=1)
-			chkbox_group = gr.CheckboxGroup(elem_id="chkbox-group", visible=False)
-			# step4 : mapping result
-			out_json_file = gr.File(label="Mapping result", visible=False)
-			res_md = gr.Markdown("""
-			(Download this file if you plan to run the models using the source code.)
-			""", visible=False)
-			
-			with gr.Row():
-				clear_btn = gr.Button("Clear", visible=False)
-				step2_btn = gr.Button("Next", visible=False)
-				step3_btn = gr.Button("Next", visible=False)
-				next_btn = gr.Button("Next step", visible=False)
-			# -------------------------------------------------------
+						tpl_img = gr.Image("./template_montage.png", label="Template montage", visible=False)
+						mapped_img = gr.Image(label="Matching results", visible=False)
+					# step2 : forward unmatched input channels to empty template channels
+					radio_group = gr.Radio(elem_id="radio-group", visible=False)
+					# step3 : fill the remaining template channels
+					with gr.Row():
+						in_fillmode = gr.Dropdown(choices=["mean", "zero"],
+													value="mean",
+													label="Filling method",
+													visible=False,
+													scale=2)
+						fillmode_btn = gr.Button("OK", visible=False, scale=1)
+					chkbox_group = gr.CheckboxGroup(elem_id="chkbox-group", visible=False)
+					# step4 : mapping result
+					out_json_file = gr.File(label="Mapping result", visible=False)
+					res_md = gr.Markdown("""
+					(Download this file if you plan to run the models using the source code.)
+					""", visible=False)
+					
+					with gr.Row():
+						clear_btn = gr.Button("Clear", visible=False)
+						step2_btn = gr.Button("Next", visible=False)
+						step3_btn = gr.Button("Next", visible=False)
+						next_btn = gr.Button("Next step", visible=False)
+					# -----------------------------------------------
 
 		with gr.Column():
-			# ------------------------input--------------------------
 			with gr.Row(variant='panel'):
 				with gr.Column():
 					gr.Markdown("# 2.Decode Data")
-					in_data_file = gr.File(label="Raw data (.csv)", file_types=[".csv"])
+					# --------------------input----------------------
 					with gr.Row():
-						in_modelname = gr.Dropdown(choices=[
-											("ART", "EEGART"),
-											("IC-U-Net", "ICUNet"),
-											("IC-U-Net++", "UNetpp"),
-											("IC-U-Net-Attn", "AttUnet")],
-											#"(mapped data)"],
-											value="EEGART",
-											label="Model",
-											scale=2)
-						run_btn = gr.Button(interactive=False, scale=1)
-			# ------------------------output-------------------------
-			batch_md = gr.Markdown(visible=False)
-			out_data_file = gr.File(label="Denoised data", visible=False)
-			# -------------------------------------------------------
+						in_data_file = gr.File(label="Raw data (.csv)", file_types=[".csv"])
+						with gr.Column():
+							in_samplerate = gr.Textbox(label="Sampling rate (Hz)")
+							in_modelname = gr.Dropdown(choices=[
+												("ART", "EEGART"),
+												("IC-U-Net", "ICUNet"),
+												("IC-U-Net++", "UNetpp"),
+												("IC-U-Net-Attn", "AttUnet")],
+												#"(mapped data)"],
+												value="EEGART",
+												label="Model")
+							run_btn = gr.Button(interactive=False)
+					# --------------------output---------------------
+					batch_md = gr.Markdown(visible=False)
+					out_data_file = gr.File(label="Denoised data", visible=False)
+					# -----------------------------------------------
 				
 	with gr.Row():
 		with gr.Tab("ART"):
@@ -303,7 +302,7 @@ with gr.Blocks() as demo:
 	# +========================================================================================+
 	# |                                Stage1: channel mapping                                 |
 	# +========================================================================================+
-	def reset_all(in_loc, samplerate):
+	def reset_all(in_loc):
 		# establish a new folder for the current session
 		rootpath = os.path.dirname(str(in_loc))
 		try:
@@ -319,7 +318,6 @@ with gr.Blocks() as demo:
 		channel_info = {}
 		app_info = {
 			"rootPath" : rootpath+"/session_data/",
-			"sampleRate" : int(samplerate),
 			"stage1" : {
 				"filePath" : rootpath+"/session_data/stage1/",
 				"fileNames" : {
@@ -346,7 +344,8 @@ with gr.Blocks() as demo:
 					"input_data" : "",
 					"output_data" : ""
 				},
-				"totalBatchNum" : None
+				"totalBatchNum" : None,
+				"sampleRate" : None
 			}
 		}
 		return {app_info_json : app_info,
@@ -368,6 +367,7 @@ with gr.Blocks() as demo:
 				res_md : gr.Markdown(visible=False),
 				# --------------------Stage2-------------------------
 				in_data_file : gr.File(value=None),
+				in_samplerate : gr.Textbox(visible=""),
 				run_btn : gr.Button(interactive=False),
 				batch_md : gr.Markdown(visible=False),
 				out_data_file : gr.File(visible=False)}
@@ -388,7 +388,7 @@ with gr.Blocks() as demo:
 		    
 			# match the names of in_channels and tpl_channels
 			stage1_info, channel_info, tpl_montage, in_montage = app_utils.match_names(stage1_info, channel_info)
-			# rescale coordinates
+			# scale the coordinates
 			channel_info = app_utils.align_coords(channel_info, tpl_montage, in_montage)
 			# generate and save figures of the montages
 			filename1 = filepath+"input_montage_"+str(random.randint(1,10000))+".png"
@@ -402,12 +402,12 @@ with gr.Blocks() as demo:
 			unassigned_num = len(stage1_info["unassignedInputs"])
 			if unassigned_num == 0:
 				md = """
-				### Step1: Initial Matching and Rescaling
+				### Step1: Initial Matching and Scaling
 				Below is the result of mapping your channels to our template channels based on their names.
 				"""
 			else:
 				md = """
-				### Step1: Initial Matching and Rescaling
+				### Step1: Initial Matching and Scaling
 				Below is the result of mapping your channels to our template channels based on their names.  
 				- channels highlighted in red are those that do not match any template channels.
 				"""
@@ -682,10 +682,10 @@ with gr.Blocks() as demo:
 	# +========================================================================================+
 	map_btn.click(
 	    fn = reset_all,
-	    inputs = [in_loc_file, in_samplerate],
+	    inputs = in_loc_file,
 	    outputs = [app_info_json, channel_info_json, map_btn, desc_md, next_btn, tpl_img, mapped_img,
 	    			radio_group, clear_btn, step2_btn, in_fillmode, fillmode_btn, chkbox_group, step3_btn,
-	    			out_json_file, res_md, in_data_file, run_btn, batch_md, out_data_file]
+	    			out_json_file, res_md, in_data_file, in_samplerate, run_btn, batch_md, out_data_file]
 	).success(
 	    fn = init_next_step,
 	    inputs = [app_info_json, channel_info_json, in_fillmode, radio_group, chkbox_group], 
@@ -833,7 +833,7 @@ with gr.Blocks() as demo:
 	# +========================================================================================+
 	# |                                  Stage2: decode data                                   |
 	# +========================================================================================+
-	def reset_run(app_info, in_data, modelname):
+	def reset_run(app_info, in_data, samplerate, modelname):
 		stage1_info = app_info["stage1"]
 		stage2_info = app_info["stage2"]
 	    
@@ -852,7 +852,8 @@ with gr.Blocks() as demo:
 			"fileNames" : {
 				"input_data" : in_data,
 				"output_data" : new_filepath + new_filename
-			}
+			},
+			"sampleRate" : int(samplerate)
 		})
 		app_info["stage2"] = stage2_info
 		return {app_info_json : app_info,
@@ -865,7 +866,7 @@ with gr.Blocks() as demo:
 		stage2_info = app_info["stage2"]
 		
 		filepath = stage2_info["filePath"]
-		samplerate = app_info["sampleRate"]
+		samplerate = stage2_info["sampleRate"]
 		filename = stage2_info["fileNames"]["input_data"]
 		new_filename = stage2_info["fileNames"]["output_data"]
 		
@@ -917,7 +918,7 @@ with gr.Blocks() as demo:
 	
 	run_btn.click(
 		fn = reset_run,
-		inputs = [app_info_json, in_data_file, in_modelname],
+		inputs = [app_info_json, in_data_file, in_samplerate, in_modelname],
 		outputs = [app_info_json, run_btn, batch_md, out_data_file]
 		
 	).success(
@@ -927,5 +928,5 @@ with gr.Blocks() as demo:
 	)
 	
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(server_name="0.0.0.0", server_port=7860)
 

app_utils.py

@@ -89,7 +89,6 @@ def save_figures(channel_info, tpl_montage, filename1, filename2):
 	tpl_dict = channel_info["templateDict"]
 	in_dict = channel_info["inputDict"]
 	
-	# get the 2D coordinates
 	tpl_x = [tpl_dict[channel]["coord_2d"][0] for channel in tpl_order]
 	tpl_y = [tpl_dict[channel]["coord_2d"][1] for channel in tpl_order]
 	in_x = [in_dict[channel]["coord_2d"][0] for channel in in_order]
@@ -217,7 +216,6 @@ def find_neighbors(channel_info, missing_channels, new_idx):
 	tpl_dict = channel_info["templateDict"]
 	in_dict = channel_info["inputDict"]
 	
-	# get the 3D coordinates
 	all_in = [np.array(in_dict[channel]["coord_3d"]) for channel in in_order]
 	empty_tpl = [np.array(tpl_dict[channel]["coord_3d"]) for channel in missing_channels]
 	
@@ -290,7 +288,6 @@ def optimal_mapping(channel_info):
 	for channel in tpl_dict:
 		tpl_dict[channel]["matched"] = False
 	
-	# get the 3D coordinates
 	all_tpl = np.array([tpl_dict[channel]["coord_3d"] for channel in tpl_order])
 	unassigned_in = np.array([in_dict[channel]["coord_3d"] for channel in unassigned])
 	
@@ -338,11 +335,12 @@ def optimal_mapping(channel_info):
 	return mapping_data, channel_info
 
 def mapping_result(stage1_info, stage2_info, channel_info, filename):
-	# calculate how many times the model needs to be run
 	unassigned_num = len(stage1_info["unassignedInputs"])
 	batch_num = math.ceil(unassigned_num/30) + 1
 	
 	# map the remaining in_channels
+	unassigned_num = len(stage1_info["unassignedInputs"])
+	batch_num = math.ceil(unassigned_num/30) + 1
 	for i in range(1, batch_num):
 		# optimally select 30 in_channels to map to the tpl_channels based on proximity
 		new_mapping_data, channel_info = optimal_mapping(channel_info)