mirror of https://github.com/kubeflow/examples.git
90 lines
2.2 KiB
Python
90 lines
2.2 KiB
Python
import json
|
|
import time
|
|
import datetime
|
|
from io import BytesIO
|
|
import requests
|
|
import numpy as np
|
|
from PIL import Image
|
|
import tensorflow as tf
|
|
from azureml.core.model import Model
|
|
|
|
def init():
|
|
if Model.get_model_path('tacosandburritos'):
|
|
model_path = Model.get_model_path('tacosandburritos')
|
|
else:
|
|
model_path = '/model/latest.h5'
|
|
print('Attempting to load model')
|
|
model = tf.keras.models.load_model(model_path)
|
|
model.summary()
|
|
print('Done!')
|
|
print('Initialized model "{}" at {}'.format(model_path, datetime.datetime.now()))
|
|
return model
|
|
|
|
|
|
def run(raw_data, model):
|
|
prev_time = time.time()
|
|
|
|
post = json.loads(raw_data)
|
|
img_path = post['image']
|
|
|
|
current_time = time.time()
|
|
|
|
tensor = process_image(img_path, 160)
|
|
t = tf.reshape(tensor, [-1, 160, 160, 3])
|
|
o = model.predict(t, steps=1) # [0][0]
|
|
print(o)
|
|
o = o[0][0]
|
|
inference_time = datetime.timedelta(seconds=current_time - prev_time)
|
|
payload = {
|
|
'time': inference_time.total_seconds(),
|
|
'prediction': 'burrito' if o > 0.5 else 'tacos',
|
|
'scores': str(o)
|
|
}
|
|
|
|
print('Input ({}), Prediction ({})'.format(post['image'], payload))
|
|
|
|
return payload
|
|
|
|
|
|
def process_image(path, image_size):
|
|
# Extract image (from web or path)
|
|
if path.startswith('http'):
|
|
response = requests.get(path)
|
|
img = np.array(Image.open(BytesIO(response.content)))
|
|
else:
|
|
img = np.array(Image.open(path))
|
|
|
|
img_tensor = tf.convert_to_tensor(img, dtype=tf.float32)
|
|
# tf.image.decode_jpeg(img_raw, channels=3)
|
|
img_final = tf.image.resize(img_tensor, [image_size, image_size]) / 255
|
|
return img_final
|
|
|
|
|
|
def info(msg, char="#", width=75):
|
|
print("")
|
|
print(char * width)
|
|
print(char + " %0*s" % ((-1 * width) + 5, msg) + char)
|
|
print(char * width)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
images = {
|
|
'tacos': 'https://c1.staticflickr.com/5/4022/4401140214_f489c708f0_b.jpg',
|
|
'burrito': 'https://www.exploreveg.org/files/2015/05/sofritas-burrito.jpeg'
|
|
}
|
|
|
|
my_model = init()
|
|
|
|
for k, v in images.items():
|
|
print('{} => {}'.format(k, v))
|
|
|
|
info('Taco Test')
|
|
taco = json.dumps({'image': images['tacos']})
|
|
print(taco)
|
|
run(taco, my_model)
|
|
|
|
info('Burrito Test')
|
|
burrito = json.dumps({'image': images['burrito']})
|
|
print(burrito)
|
|
run(burrito, my_model)
|