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example_usage_model_script.py
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example_usage_model_script.py
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import tensorflow as tf
def load_graph(frozen_graph_filename):
# We load the protobuf file from the disk and parse it to retrieve the
# unserialized graph_def
with tf.gfile.GFile(frozen_graph_filename, "rb") as f:
graph_def = tf.GraphDef()
graph_def.ParseFromString(f.read())
# Then, we import the graph_def into a new Graph and returns it
with tf.Graph().as_default() as graph:
# The name var will prefix every op/nodes in your graph
# Since we load everything in a new graph, this is not needed
tf.import_graph_def(graph_def)
return graph
class ExampleModel(object):
def __init__(self, graph_path):
self._graph_path = graph_path
def get_model(self):
config = tf.ConfigProto(
allow_soft_placement=True,
device_count={'GPU': 0}
)
config.gpu_options.allow_growth = True
graph = load_graph(self._graph_path)
sess = tf.Session(config=config, graph=graph)
input_images = graph.get_tensor_by_name('import/input_images:0')
some_sigmoid_output = graph.get_tensor_by_name('import/feature_fusion/Conv_7/Sigmoid:0')
some_concat_output_if_necessary = graph.get_tensor_by_name('import/feature_fusion/concat_3:0')
# ... using ops as normally with session