ai-accelerator-2.py

def image_preprocess(img, reps=1):
    img = np.asarray(img.resize((224, 224)))
    img = np.stack([img]*reps)
    img = tf.keras.applications.resnet50.preprocess_input(img)
    return img

from PIL import Image 
import numpy as np
import json

img= Image.open('kitten.jpg')
img = image_preprocess(img, 5)
response = predictor_gpu.predict(data=img)
probs = np.array(response['predictions'][0])

tf.keras.applications.resnet.decode_predictions(np.expand_dims(probs, axis=0), top=5)