VGG16Places365 test

vgg16places365_test.py

import urllib2
import numpy as np
from PIL import Image
from cv2 import resize
from vgg16_places365 import VGG16Places365, preprocess_input

LABELS_URL = 'https://raw.githubusercontent.com/csailvision/places365/master/categories_places365.txt'
LABELS = np.array(urllib2.urlopen(LABELS_URL).read().splitlines())
TEST_IMAGE_URL = 'https://s3-us-west-2.amazonaws.com/kaggleglm/inside_airplane.jpg'

image = Image.open(urllib2.urlopen(TEST_IMAGE_URL))
image = np.array(image, dtype=np.uint8)
image = resize(image, (224, 224))
image = preprocess_input(image.astype(np.float32))
image = np.expand_dims(image, 0)

model = VGG16Places365()
output = model.predict(image)
output = np.squeeze(output)

top5 = output.argsort()[-5:][::-1]
print("Labels:", LABELS[top5])
print("Probs:", output[top5])