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convert_weight.py
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convert_weight.py
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# coding: utf-8
# for more details about the yolo darknet weights file, refer to
# https://itnext.io/implementing-yolo-v3-in-tensorflow-tf-slim-c3c55ff59dbe
from __future__ import division, print_function
import os
import sys
import tensorflow as tf
import numpy as np
from model import yolov3
from utils.misc_utils import parse_anchors, load_weights
num_class = 80
img_size = 416
weight_path = './data/darknet_weights/yolov3.weights'
save_path = './data/darknet_weights/yolov3.ckpt'
anchors = parse_anchors('./data/yolo_anchors.txt')
model = yolov3(80, anchors)
with tf.Session() as sess:
inputs = tf.placeholder(tf.float32, [1, img_size, img_size, 3])
with tf.variable_scope('yolov3'):
feature_map = model.forward(inputs)
saver = tf.train.Saver(var_list=tf.global_variables(scope='yolov3'))
load_ops = load_weights(tf.global_variables(scope='yolov3'), weight_path)
sess.run(load_ops)
saver.save(sess, save_path=save_path)
print('TensorFlow model checkpoint has been saved to {}'.format(save_path))