Model_DenseNet/app.py

# app.py
import tensorflow as tf
import numpy as np
from PIL import Image

model = tf.keras.models.load_model('.')

def predict(image):
    # Preprocess image
    image = image.resize((224, 224))
    image_array = np.array(image) / 255.0
    image_array = np.expand_dims(image_array, axis=0)
    
    # Predict
    predictions = model.predict(image_array)
    return predictions[0]