import tensorflow as tf
from tensorflow.keras.applications import ResNet50
from tensorflow.keras.applications.resnet50 import preprocess_input, decode_predictions
from tensorflow.keras.preprocessing import image
import numpy as np
 
def process_image(image_path):
    # Load the pre-trained model
    model = ResNet50(weights='imagenet')
 
    # Load and preprocess the image
    img = image.load_img(image_path, target_size=(224, 224))
    img_array = image.img_to_array(img)
    img_array = np.expand_dims(img_array, axis=0)
    img_array = preprocess_input(img_array)
 
    # Predict
    predictions = model.predict(img_array)
    description = decode_predictions(predictions, top=1)[0][0][1]
 
    return description
 

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