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app.py

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+import gradio as gr
+import numpy as np
+import joblib
+from sklearn.preprocessing import StandardScaler 
+
+
+model = joblib.load("final_rf_model.pkl")
+scaler = StandardScaler()  
+
+class_labels = {
+    0: 'Insufficient Weight',
+    1: 'Normal Weight',
+    2: 'Overweight Level I',
+    3: 'Overweight Level II',
+    4: 'Obesity Type I',
+    5: 'Obesity Type II',
+    6: 'Obesity Type III'
+}
+
+# Function to make predictions
+def predict_obesity(weight, height, age, fcvc, gender, ncp, ch2o, faf, tue, fhwow,
+                    caec_sometimes, calc_no, calc_sometimes, caec_frequently,
+                    alcohol_choice, mtrans_choice, favc):
+    
+    # Prepare input data for prediction
+    input_data = np.array([[weight, height, age, fcvc, 1 if gender == "Male" else 0, ncp, ch2o, faf, tue, fhwow,
+                             1 if caec_sometimes else 0, 1 if calc_no else 0, 1 if calc_sometimes else 0,
+                             1 if caec_frequently else 0, 1 if alcohol_choice == "Yes" else 0,
+                             1 if favc else 0, 1 if mtrans_choice == "Automobile" else 0]])
+
+    # Scale the appropriate input values
+    input_data[:, 0:4] = scaler.fit_transform(input_data[:, 0:4])  
+    input_data[:, 5:10] = scaler.fit_transform(input_data[:, 5:10])  
+
+    # Make prediction
+    prediction = model.predict(input_data)
+
+    # Map the numeric prediction to the corresponding label
+    predicted_label = class_labels.get(prediction[0], "Unknown Class")
+    return predicted_label
+
+# Custom CSS for better styling
+custom_css = """
+<style>
+    .gradio-container {
+        background-color: #0a0a2c;
+        background-image: 
+            linear-gradient(45deg, #0a0a2c 25%, #12124a 25%, #12124a 50%, #0a0a2c 50%, #0a0a2c 75%, #12124a 75%, #12124a 100%);
+        background-size: 56.57px 56.57px;
+        border-radius: 15px;
+        padding: 30px;
+        box-shadow: 0 0 20px rgba(66, 220, 219, 0.3),
+                    0 0 40px rgba(233, 30, 99, 0.2);
+        border: 1px solid rgba(66, 220, 219, 0.3);
+    }
+
+    .title {
+        font-family: 'Orbitron', sans-serif;
+        font-size: 36px;
+        font-weight: bold;
+        color: #00fff2;
+        text-align: center;
+        margin-bottom: 30px;
+        text-transform: uppercase;
+        letter-spacing: 3px;
+        text-shadow: 0 0 10px rgba(0, 255, 242, 0.5),
+                     0 0 20px rgba(0, 255, 242, 0.3),
+                     0 0 30px rgba(0, 255, 242, 0.1);
+    }
+
+    .description {
+        font-family: 'Rajdhani', sans-serif;
+        font-size: 18px;
+        color: #b4f8fc;
+        text-align: center;
+        margin-bottom: 30px;
+        line-height: 1.6;
+        text-shadow: 0 0 5px rgba(180, 248, 252, 0.3);
+    }
+
+    /* Input fields styling */
+    input[type="number"] {
+        background-color: rgba(16, 16, 44, 0.9);
+        border: 2px solid #00fff2;
+        border-radius: 8px;
+        padding: 12px;
+        color: #fff;
+        font-family: 'Rajdhani', sans-serif;
+        transition: all 0.3s ease;
+        box-shadow: 0 0 10px rgba(0, 255, 242, 0.2);
+    }
+
+    input[type="number"]:focus {
+        border-color: #ff2e63;
+        box-shadow: 0 0 15px rgba(255, 46, 99, 0.4);
+        outline: none;
+    }
+
+    /* Radio and Checkbox styling */
+    input[type="radio"],
+    input[type="checkbox"] {
+        accent-color: #ff2e63;
+    }
+
+    .input-container label {
+        color: #b4f8fc;
+        font-family: 'Rajdhani', sans-serif;
+        font-size: 16px;
+        margin-bottom: 8px;
+        display: block;
+    }
+
+    /* Button styling */
+    button {
+        background: linear-gradient(45deg, #ff2e63, #00fff2);
+        color: #fff;
+        border: none;
+        padding: 15px 30px;
+        border-radius: 8px;
+        cursor: pointer;
+        font-family: 'Orbitron', sans-serif;
+        font-size: 18px;
+        text-transform: uppercase;
+        letter-spacing: 2px;
+        transition: all 0.3s ease;
+        box-shadow: 0 0 15px rgba(255, 46, 99, 0.3),
+                    0 0 30px rgba(0, 255, 242, 0.2);
+    }
+
+    button:hover {
+        transform: translateY(-2px);
+        box-shadow: 0 0 20px rgba(255, 46, 99, 0.5),
+                    0 0 40px rgba(0, 255, 242, 0.3);
+    }
+
+    /* Output label styling */
+    .output-label {
+        background: rgba(16, 16, 44, 0.9);
+        border: 2px solid #ff2e63;
+        border-radius: 8px;
+        padding: 20px;
+        color: #00fff2;
+        font-family: 'Orbitron', sans-serif;
+        font-size: 24px;
+        text-align: center;
+        margin-top: 20px;
+        box-shadow: 0 0 15px rgba(255, 46, 99, 0.3);
+    }
+
+    /* Add cyberpunk grid lines to the background */
+    .gradio-container::before {
+        content: '';
+        position: absolute;
+        top: 0;
+        left: 0;
+        right: 0;
+        bottom: 0;
+        background: 
+            linear-gradient(90deg, rgba(66, 220, 219, 0.1) 1px, transparent 1px),
+            linear-gradient(0deg, rgba(66, 220, 219, 0.1) 1px, transparent 1px);
+        background-size: 20px 20px;
+        pointer-events: none;
+    }
+
+    /* Add some hover effects to input containers */
+    .input-container:hover {
+        transform: translateX(5px);
+        transition: transform 0.3s ease;
+    }
+
+    /* Scrollbar styling */
+    ::-webkit-scrollbar {
+        width: 10px;
+        background: #0a0a2c;
+    }
+
+    ::-webkit-scrollbar-thumb {
+        background: linear-gradient(45deg, #ff2e63, #00fff2);
+        border-radius: 5px;
+    }
+</style>
+"""
+
+# Gradio interface
+iface = gr.Interface(
+    fn=predict_obesity,
+    inputs=[
+        gr.Number(label="Weight (40-160 kg)"),
+        gr.Number(label="Height (1-2 m)"),
+        gr.Number(label="Age (10-60 years)"),
+        gr.Number(label="FCVC (Frequency of Vegetable Consumption 1-4)"),
+        gr.Radio(choices=["Male", "Female"], label="Gender"),
+        gr.Number(label="NCP (Number of meals per day 1-3)"),
+        gr.Number(label="CH2O (Water Consumption 1-3)"),
+        gr.Number(label="FAF (Physical Activity Frequency 1-4)"),
+        gr.Number(label="TUE (Time Spent on Exercise 1-4)"),
+        gr.Number(label="FHWOW (Family History with OverWeight)"),
+        gr.Radio(choices=["No", "Sometimes", "Frequently"], label="Alcohol Consumption"),
+        gr.Radio(choices=["Public Transportation", "Automobile"], label="Transportation Method"),
+        gr.Checkbox(label="FAVC (Frequent Consumption of High-Calorie Foods)"),
+    ],
+    outputs=gr.Label(label="Predicted Obesity Level"),
+    title="Obesity Level Estimator",
+    description="Enter the features related to eating habits and physical condition to estimate obesity levels.",
+    css=custom_css
+)
+
+# Launch the interface
+iface.launch(share=True)

final_rf_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:21365aae2145e53e3f6221b77d8812f40895c5cf418a90f35519e20b12e83bd9
+size 1303443