app.py

import gradio as gr
import numpy as np
from tensorflow.keras.preprocessing import image
from tensorflow.keras.models import load_model

# Load trained model (make sure model is in same directory)
model = load_model("eiffel_model3.h5")

img_height, img_width = 224, 224

def predict_burj(img):
    img = img.resize((img_height, img_width))
    img_array = image.img_to_array(img) / 255.0
    img_array = np.expand_dims(img_array, axis=0)
    prediction = model.predict(img_array)[0][0]
    return "Not Eiffel Tower" if prediction > 0.5 else "Eiffel Tower"

examples = [
    "Eiffel1.jpeg",
    "Eiffel2.jpeg",
    "Non_Eiffel1.jpg",
    "Non_Eiffel2.jpeg"
]

interface = gr.Interface(
    fn=predict_burj,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="Eiffel Tower Classifier",
    description="Upload an image to check if it's Eiffel Tower or not.",
    examples=examples
)

interface.launch()