Update app.py

app.py

@@ -35,7 +35,7 @@ iface = gr.Interface(
 
 # Launch the Gradio interface
 iface.launch()
-'''
+
 import gradio as gr
 import pickle
 import numpy as np
@@ -67,3 +67,87 @@ interface = gr.Interface(
 
 # Launch the Gradio app
 interface.launch()
+'''
+import gradio as gr
+import pickle
+import numpy as np
+
+# Load the model
+with open('model_AD.pkl', 'rb') as f:
+    loaded_model = pickle.load(f)
+
+# Define the prediction function
+def predict_pcos(
+    age, weight, height, bmi, blood_group, pulse_rate, rr, hb, cycle_ri,
+    cycle_length, marriage_status, pregnant, no_of_abortions, fsh, lh, fsh_lh, 
+    hip, waist, waist1, tsh, prl, vit_d3, prg, rbs, weight_gain, hair_growth, 
+    skin_darkening, hair_loss, pimples, fast_food, reg_exercise, bp_systolic, 
+    bp_diastolic, follicle_no_l, follicle_no_r, avg_f_size_l, avg_f_size_r, endometrium):
+    
+    # Prepare the input data as a single-row array
+    input_data = np.array([[
+        age, weight, height, bmi, blood_group, pulse_rate, rr, hb, cycle_ri,
+        cycle_length, marriage_status, pregnant, no_of_abortions, fsh, lh, fsh_lh, 
+        hip, waist, waist1, tsh, prl, vit_d3, prg, rbs, weight_gain, hair_growth, 
+        skin_darkening, hair_loss, pimples, fast_food, reg_exercise, bp_systolic, 
+        bp_diastolic, follicle_no_l, follicle_no_r, avg_f_size_l, avg_f_size_r, endometrium
+    ]])
+
+    # Get prediction
+    prediction = loaded_model.predict(input_data)[0]
+    return "PCOS Detected" if prediction == 1 else "No PCOS"
+
+# Define the Gradio interface
+inputs = [
+    gr.Number(label="Age (yrs)"),
+    gr.Number(label="Weight (Kg)"),
+    gr.Number(label="Height (Cm)"),
+    gr.Number(label="BMI"),
+    gr.Number(label="Blood Group"),  # Convert categorical data appropriately if needed
+    gr.Number(label="Pulse rate (bpm)"),
+    gr.Number(label="RR (breaths/min)"),
+    gr.Number(label="Hb (g/dl)"),
+    gr.Number(label="Cycle (R/I)"),
+    gr.Number(label="Cycle length (days)"),
+    gr.Number(label="Marriage Status (Yrs)"),
+    gr.Number(label="Pregnant (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="No. of abortions"),
+    gr.Number(label="FSH (mIU/mL)"),
+    gr.Number(label="LH (mIU/mL)"),
+    gr.Number(label="FSH/LH"),
+    gr.Number(label="Hip (inch)"),
+    gr.Number(label="Waist (inch)"),
+    gr.Number(label="Waist1 (inch)"),
+    gr.Number(label="TSH (mIU/L)"),
+    gr.Number(label="PRL (ng/mL)"),
+    gr.Number(label="Vit D3 (ng/mL)"),
+    gr.Number(label="PRG (ng/mL)"),
+    gr.Number(label="RBS (mg/dl)"),
+    gr.Number(label="Weight gain (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Hair growth (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Skin darkening (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Hair loss (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Pimples (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Fast food (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="Regular Exercise (Y/N)"),  # 1 for Yes, 0 for No
+    gr.Number(label="BP Systolic (mmHg)"),
+    gr.Number(label="BP Diastolic (mmHg)"),
+    gr.Number(label="Follicle No. (L)"),
+    gr.Number(label="Follicle No. (R)"),
+    gr.Number(label="Avg. F size (L) (mm)"),
+    gr.Number(label="Avg. F size (R) (mm)"),
+    gr.Number(label="Endometrium (mm)")
+]
+
+outputs = gr.Textbox(label="PCOS Prediction")
+
+# Create and launch the app
+app = gr.Interface(
+    fn=predict_pcos, 
+    inputs=inputs, 
+    outputs=outputs, 
+    title="PCOS Prediction Model",
+    description="Enter the patient's information to predict PCOS."
+)
+
+app.launch()