Y
Size: a a a
Y
Y
SB
YS
ЯЗ
ЯЗ
def get_distance(im1, im2):
K.clear_session()
model = deep_rank_model()
K.clear_session()
# for layer in model.layers:
# print (layer.name, layer.output_shape)
K.clear_session()
model.load_weights("./deepranking.h5")
K.clear_session()
image1 = Image.open(urlopen(im1))
# image1 = load_img(im1)
image1 = img_to_array(image1).astype("float64")
image1 = transform.resize(image1, (224, 224))
image1 *= 1. / 255
image1 = np.expand_dims(image1, axis=0)
embedding1 = model.predict([image1, image1, image1])[0]
image2 = Image.open(urlopen(im2))
# image2 = load_img(im2)
image2 = img_to_array(image2).astype("float64")
image2 = transform.resize(image2, (224, 224))
image2 *= 1. / 255
image2 = np.expand_dims(image2, axis=0)
embedding2 = model.predict([image2, image2, image2])[0]
distance = sum([(embedding1[idx] - embedding2[idx]) ** 2 for idx in range(len(embedding1))]) ** 0.5
print(distance)
return distance
L
globals().update(__import__("random_module.__dict__.items()"))
?L
L
L
ЕВ
NK
AZ
KM
i
KM
OK
RK
OK
i