Upload app.py

app.py

@@ -12,28 +12,25 @@ import requests
 transformer = load_model('transformer_pile.h5')
 sc_f = pickle.load(open('scaler_f.pkl', 'rb'))
 
-# URL to the default Excel file (replace with your actual URL)
-DEFAULT_EXCEL_URL = "data_pile.xlsx"
+# URL to the default Excel file
+DEFAULT_EXCEL_URL = "https://huggingface.co/spaces/neng123/Pile_deform/resolve/main/data_pile.xlsx"
 
 def download_default_excel():
     response = requests.get(DEFAULT_EXCEL_URL)
     return io.BytesIO(response.content)
 
 def process_excel(file):
-    if isinstance(file, str) and file == "default":
+    if file == "default":
         file = download_default_excel()
-    
     df = pd.read_excel(file, sheet_name='soil')
     df_y = pd.read_excel(file, sheet_name='pile')
     df_p = pd.read_excel(file, sheet_name='pile_length')
-
     data = np.array(df)
     data_y = np.array(df_y)
     data_pile = np.array(df_p)[:, 1:61]
     x_feature = data_y[:, 0:4]
     bh = data[:, 1:61]
     bh2 = data[:, 61:122] / 2
-
     x_train = bh / 50
     x_feature = sc_f.transform(x_feature)
     soil_data = np.stack([x_train, bh2, data_pile], axis=2)
@@ -57,10 +54,9 @@ def predict_pile(file_choice, uploaded_file, pile_length, section_width, section
     feature = np.reshape(feature, (1, -1))
     fd = sc_f.transform(feature)
     x_feature = fd
-
+    
     # Use the first sample for demonstration
     Xd = X[0:1]
-
     X_train_CNN = np.zeros((Xd.shape[0], Xd.shape[1], x_feature.shape[1] + 3))
     X_train_CNN[:, :, 0:3] = Xd
     for i in range(Xd.shape[0]):
@@ -71,44 +67,58 @@ def predict_pile(file_choice, uploaded_file, pile_length, section_width, section
     
     XT = X_train_CNN
     print(XT.shape)
+    
     y_ini = np.zeros((1, 40))
     y_ini[0, 0] = 0
-
     for step in range(39):
         y = transformer.predict([XT, y_ini, fd])
         y_ini[0, step+1] = y
-
+    
     y_pred = y_ini * 40000
-
+    
     plt.figure(figsize=(10, 6))
     ydist = range(1, 41)
     plt.plot(ydist, y_pred[0], color='blue', label='predict')
     plt.legend()
-    plt.xlabel("Deformation")
-    plt.ylabel("Load")
+    plt.xlabel("Deformation (mm)")
+    plt.ylabel("Load (kN)")
     plt.title(f"Pile Prediction (Length: {pile_length}m, {pile_type})")
-    
     return plt
 
-iface = gr.Interface(
-    fn=predict_pile,
-    inputs=[
-        gr.Radio(["default", "upload"], label="Choose Excel File Source", value="default"),
-        gr.File(label="Upload Excel File", type="binary", visible=False),
-        gr.Number(label="Pile Length (m)", value=30),
-        gr.Number(label="Section Width (m)", value=1),
-        gr.Number(label="Section Length (m)", value=1),
-        gr.Radio(["Circular", "Barrette"], label="Pile Type", value="Circular")
-    ],
-    outputs="plot",
-    title="Pile Prediction Model",
-    description="Choose the default Excel file or upload your own, then enter pile characteristics to predict pile behavior.",
-    live=False
-)
-
 def update_file_input(choice):
     return gr.update(visible=choice == "upload")
 
-iface.inputs[0].change(update_file_input, inputs=[iface.inputs[0]], outputs=[iface.inputs[1]])
+with gr.Blocks() as iface:
+    gr.Markdown("# Pile Prediction Model")
+    gr.Markdown("Choose the default Excel file or upload your own, then enter pile characteristics to predict pile behavior.")
+    
+    with gr.Row():
+        file_choice = gr.Radio(["default", "upload"], label="Choose Excel File Source", value="default")
+        uploaded_file = gr.File(label="Upload Excel File", type="binary", visible=False)
+    
+    with gr.Row():
+        pile_length = gr.Number(label="Pile Length (m) please change data in excel file together", value=30)
+        section_width = gr.Number(label="Section Width (m)", value=1)
+        section_length = gr.Number(label="Section Length (m)", value=1)
+        pile_type = gr.Radio(["Circular", "Barrette"], label="Pile Type", value="Circular")
+    
+    output = gr.Plot()
+    
+    submit_btn = gr.Button("Predict")
+    
+    # Add a download link for the default Excel file
+    gr.Markdown(f"[Download Default Excel File]({DEFAULT_EXCEL_URL})")
+    
+    file_choice.change(
+        fn=update_file_input,
+        inputs=[file_choice],
+        outputs=[uploaded_file]
+    )
+    
+    submit_btn.click(
+        fn=predict_pile,
+        inputs=[file_choice, uploaded_file, pile_length, section_width, section_length, pile_type],
+        outputs=[output]
+    )
 
 iface.launch()