File size: 1,624 Bytes
ae29340 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | import tensorflow as tf
import os
from foolbox.models import TensorFlowModel
from resnet18.resnet_model import Model
def create_model():
graph = tf.Graph()
with graph.as_default():
images = tf.placeholder(tf.float32, (None, 64, 64, 3))
# preprocessing
_R_MEAN = 123.68
_G_MEAN = 116.78
_B_MEAN = 103.94
_CHANNEL_MEANS = [_R_MEAN, _G_MEAN, _B_MEAN]
features = images - tf.constant(_CHANNEL_MEANS)
model = Model(
resnet_size=18,
bottleneck=False,
num_classes=200,
num_filters=64,
kernel_size=3,
conv_stride=1,
first_pool_size=0,
first_pool_stride=2,
second_pool_size=7,
second_pool_stride=1,
block_sizes=[2, 2, 2, 2],
block_strides=[1, 2, 2, 2],
final_size=512,
version=2,
data_format=None,
)
logits = model(features, False)
with tf.variable_scope("utilities"):
saver = tf.train.Saver()
return graph, saver, images, logits
def create_fmodel():
graph, saver, images, logits = create_model()
sess = tf.Session(graph=graph)
path = os.path.dirname(os.path.abspath(__file__))
path = os.path.join(path, "resnet18", "checkpoints", "models_repo")
saver.restore(sess, tf.train.latest_checkpoint(path))
with sess.as_default():
fmodel = TensorFlowModel(images, logits, bounds=(0, 255))
return fmodel
if __name__ == "__main__":
# executable for debuggin and testing
print(create_fmodel())
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