freeze_graph.py

#! /usr/bin/env python
# coding=utf-8
import tensorflow as tf
from core.yolov3 import YOLOV3

def model_freeze(pb_file, ckpt_file):
    with tf.name_scope('input'):
        input_data = tf.placeholder(dtype=tf.float32, name='input_data')

    model = YOLOV3(input_data, trainable=False)                 # 加载yolov3网络
    print(model.conv_sbbox, model.conv_mbbox, model.conv_lbbox)

    sess  = tf.Session(config=tf.ConfigProto(allow_soft_placement=True))
    saver = tf.train.Saver()
    saver.restore(sess, ckpt_file)

    converted_graph_def = tf.graph_util.convert_variables_to_constants(sess,
                                input_graph_def  = sess.graph.as_graph_def(),
                                output_node_names = output_node_names)

    with tf.gfile.GFile(pb_file, "wb") as f:
        f.write(converted_graph_def.SerializeToString())


if __name__ == "__main__":

    pb_file = "./checkpoint/yolov3_coco_v3.pb"
    ckpt_file = "./checkpoint/yolov3_coco_demo.ckpt"
    output_node_names = ["input/input_data", "pred_sbbox/concat_2", "pred_mbbox/concat_2", "pred_lbbox/concat_2",
                         "pred_multi_scale/concat"]

    model_freeze(pb_file, ckpt_file)
    print( 'YOLOV3 模型固化已完成.' )