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freeze_graph.py
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freeze_graph.py
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import tensorflow as tf
from keras import backend as K
from keras.models import load_model
from tensorflow.python.framework.graph_util import convert_variables_to_constants
def freeze_session(session, keep_var_names=None, output_names=None, clear_devices=True):
graph = session.graph
with graph.as_default():
freeze_var_names = list(set(v.op.name for v in tf.global_variables()).difference(keep_var_names or []))
output_names = output_names or []
output_names += [v.op.name for v in tf.global_variables()]
input_graph_def = graph.as_graph_def()
if clear_devices:
for node in input_graph_def.node:
node.device = ""
frozen_graph = convert_variables_to_constants(session, input_graph_def,
output_names, freeze_var_names)
return frozen_graph
def main():
# load model
model = load_model('model/face_classifier.h5')
frozen_graph = freeze_session(K.get_session(),
output_names=[out.op.name for out in model.outputs])
tf.train.write_graph(frozen_graph, "model", "face_classifier.pb", as_text=False)
if __name__ == '__main__':
main()