Create app.py

app.py

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+# Import libraries
+import numpy as np
+import pandas as pd
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+import gradio as gr
+import joblib
+
+# Step 1: Generate or Load Sample Data
+# Features: Pressure, Temperature, Material Type (encoded as integers)
+# Target: Defect Type (0 = No Defect, 1 = Crack, 2 = Wrinkle)
+np.random.seed(42)
+data = pd.DataFrame({
+    "Pressure": np.random.randint(50, 200, 200),
+    "Temperature": np.random.randint(300, 700, 200),
+    "Material_Type": np.random.randint(1, 5, 200),
+    "Defect_Type": np.random.choice([0, 1, 2], 200, p=[0.6, 0.3, 0.1])
+})
+
+# Splitting data
+X = data[["Pressure", "Temperature", "Material_Type"]]
+y = data["Defect_Type"]
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+# Step 2: Train the Model
+model = RandomForestClassifier(n_estimators=100, random_state=42)
+model.fit(X_train, y_train)
+
+# Save the model
+joblib.dump(model, "defect_model.pkl")
+
+# Step 3: Test the Model
+y_pred = model.predict(X_test)
+print(f"Model Accuracy: {accuracy_score(y_test, y_pred):.2f}")
+
+# Step 4: Create a Gradio Interface
+def predict_defect(pressure, temperature, material_type):
+    # Load the model
+    loaded_model = joblib.load("defect_model.pkl")
+    # Predict
+    input_data = np.array([[pressure, temperature, material_type]])
+    prediction = loaded_model.predict(input_data)[0]
+    defect_map = {0: "No Defect", 1: "Crack", 2: "Wrinkle"}
+    return defect_map[prediction]
+
+# Gradio Interface
+interface = gr.Interface(
+    fn=predict_defect,
+    inputs=[
+        gr.inputs.Slider(50, 200, step=1, label="Pressure"),
+        gr.inputs.Slider(300, 700, step=1, label="Temperature"),
+        gr.inputs.Dropdown(["1", "2", "3", "4"], label="Material Type"),
+    ],
+    outputs="text",
+    title="Defect Prediction Model",
+    description="Predicts defect type based on input features: Pressure, Temperature, and Material Type."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()