Update app.py

app.py

@@ -8,14 +8,18 @@ import scipy
 from scipy import signal
 import pickle
 
+global_data = None
+
 def get_data_preview(file):
-    data = pd.read_csv(file.name)
-    return data.head()
+    global global_data
+    global_data = pd.read_csv(file.name)
+    return global_data.head()
 
-def label_data(file, start, end, label):
-    data = pd.read_csv(file.name)
-    data.loc[start:end, 'label'] = label  # Label the specified range
-    return data
+def label_data(ranges):
+    global global_data
+    for start, end, label in ranges:
+        global_data.loc[start:end, 'label'] = label
+    return global_data.head()
 
 def preprocess_data(data):
     data.drop(columns=data.columns[0], axis=1, inplace=True)
@@ -86,7 +90,9 @@ def preprocess_data(data):
     df_features['label'] = labels
     return df_features
 
-def train_model(data):
+def train_model():
+    global global_data
+    data = preprocess_data(global_data)
     scaler = StandardScaler()
     X = data.drop('label', axis=1)
     y = data['label']
@@ -108,15 +114,17 @@ def train_model(data):
     with open(scaler_filename, 'wb') as file:
         pickle.dump(scaler, file)
     
-    return f"Training complete! Model and scaler saved.", gr.File(model_filename), gr.File(scaler_filename)
+    return "Training complete! Model and scaler saved.", model_filename, scaler_filename
 
 
 with gr.Blocks() as demo:
     file_input = gr.File(label="Upload CSV File")
     data_preview = gr.Dataframe(label="Data Preview", interactive=False)
-    start_input = gr.Number(label="Start Index", value=0)
-    end_input = gr.Number(label="End Index", value=100)
-    label_input = gr.Number(label="Label Value", value=1)
+    ranges_input = gr.Dataframe(headers=["Start Index", "End Index", "Label"], label="Ranges for Labeling")
+    
+    #start_input = gr.Number(label="Start Index", value=0)
+    #end_input = gr.Number(label="End Index", value=100)
+    #label_input = gr.Number(label="Label Value", value=1)
     labeled_data_preview = gr.Dataframe(label="Labeled Data Preview", interactive=False)
     training_status = gr.Textbox(label="Training Status")
     model_file = gr.File(label="Download Trained Model")
@@ -124,8 +132,8 @@ with gr.Blocks() as demo:
 
     file_input.upload(get_data_preview, inputs=file_input, outputs=data_preview)
     label_button = gr.Button("Label Data")
-    label_button.click(label_data, inputs=[file_input, start_input, end_input, label_input], outputs=labeled_data_preview)
+    label_button.click(label_data, inputs=[ranges_input], outputs=labeled_data_preview)
     train_button = gr.Button("Train Model")
-    train_button.click(train_model, inputs=labeled_data_preview, outputs=[training_status, model_file, scaler_file])
+    train_button.click(train_model, outputs=[training_status, model_file, scaler_file])
 
-demo.launch()
+demo.launch()