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test.py
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test.py
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import numpy as np
from keras_vggface import VGGFace
from keras.preprocessing import image
from keras_vggface import utils
import keras
import unittest
class VGGFaceTests(unittest.TestCase):
def testVGG16(self):
keras.backend.image_data_format()
model = VGGFace(model='vgg16')
img = image.load_img('image/ajb.jpg', target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = utils.preprocess_input(x, version=1)
preds = model.predict(x)
# print ('\n', "VGG16")
# print('\n',preds)
# print('\n','Predicted:', utils.decode_predictions(preds))
self.assertIn('A.J._Buckley', utils.decode_predictions(preds)[0][0][0])
self.assertAlmostEqual(utils.decode_predictions(preds)[0][0][1], 0.9790116, places=3)
def testRESNET50(self):
keras.backend.image_data_format()
model = VGGFace(model='resnet50')
img = image.load_img('image/ajb.jpg', target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = utils.preprocess_input(x, version=2)
preds = model.predict(x)
# print ('\n',"RESNET50")
# print('\n',preds)
# print('\n','Predicted:', utils.decode_predictions(preds))
self.assertIn('A._J._Buckley', utils.decode_predictions(preds)[0][0][0])
self.assertAlmostEqual(utils.decode_predictions(preds)[0][0][1], 0.91819614, places=3)
def testSENET50(self):
keras.backend.image_data_format()
model = VGGFace(model='senet50')
img = image.load_img('image/ajb.jpg', target_size=(224, 224))
x = image.img_to_array(img)
x = np.expand_dims(x, axis=0)
x = utils.preprocess_input(x, version=2)
preds = model.predict(x)
# print ('\n', "SENET50")
# print('\n',preds)
# print('\n','Predicted:', utils.decode_predictions(preds))
self.assertIn('A._J._Buckley', utils.decode_predictions(preds)[0][0][0])
self.assertAlmostEqual(utils.decode_predictions(preds)[0][0][1], 0.9993529, places=3)
if __name__ == '__main__':
unittest.main()