test_efficientnet_gfx803.py

import os
import sys
import numpy as np

from skimage.io import imread
from keras.applications.imagenet_utils import decode_predictions
from efficientnet import EfficientNetB0
from efficientnet import center_crop_and_resize, preprocess_input


def test_efficientnet():
    # Load pretrained model
    model = EfficientNetB0(weights='imagenet')

    # preprocess input
    image = imread('Giant_Panda_in_Beijing_Zoo_1.JPG')
    image_size = model.input_shape[1]
    x = center_crop_and_resize(image, image_size=image_size)
    x = preprocess_input(x)
    x = np.expand_dims(x, 0)

    # make prediction and decode
    y = model.predict(x)
    actual = list(decode_predictions(y)[0][i][1] for i in range(len(decode_predictions(y)[0])))

    expected = [
        'giant_panda', 'ice_bear', 'lesser_panda', 'American_black_bear', 'brown_bear'
    ]

    assert actual == expected