Update app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+import numpy as np
+from PIL import Image
+from tensorflow.keras.models import load_model
+
+model_path = "vehicle_classification_model.keras"  
+try:
+    model = load_model(model_path)
+except OSError as e:
+    print("Error loading model:", e)
+
+class_labels = ['Auto Rickshaw', 'Bike', 'Car', 'Motorcycle', 'Plane', 'Ship', 'Train']
+
+def predict_vehicle(img):
+    img = img.resize((224, 224))  
+    img = np.array(img) / 255.0  
+    img = np.expand_dims(img, axis=0)
+
+    predictions = model.predict(img)
+    predicted_class = np.argmax(predictions, axis=1)[0]
+    confidence = np.max(predictions, axis=1)[0]
+    predicted_label = class_labels[predicted_class]
+
+    return {"vehicle_type": predicted_label, "confidence": float(confidence)}
+
+gr.Interface(
+    fn=predict_vehicle,
+    inputs=gr.Image(type="pil", label="Upload Image"),
+    outputs=gr.JSON(label="Prediction Result"),
+    title="Vehicle Classification System",
+    description="Upload an image of a vehicle and the model will predict its type.",
+    live=True
+).launch()