app.py

import gradio as gr
import cv2
import numpy as np
from tensorflow.keras.models import load_model
import os  # Import modul os untuk mengakses secret

model = load_model("model_deri.h5")

def predict_image(image):
    img = cv2.resize(image, (128, 128))
    img = img / 255.0
    img = np.expand_dims(img, axis=0)
    
    prediction = model.predict(img)[0][0]
    
    # Cek nilai threshold
    if prediction > 0.5:
        # Mengambil secret 'deri' dari environment variables
        secret_deri = os.environ.get('deri')
        label = f"Ini Deri, secret: {secret_deri}"
    else:
        label = "Ini bukan Deri"
    return label, float(prediction)

iface = gr.Interface(
    fn=predict_image,
    inputs=gr.Image(type="numpy"),
    outputs=[gr.Label(), gr.Number()],
    title="Deri Classifier",
    description="Upload gambar dan model akan memprediksi apakah itu Deri atau bukan."
)

iface.launch()