tf_infer.py

import tensorflow as tf
import cv2
import numpy as np


graph_def = 'weights/yolov3.pb'

with tf.gfile.GFile(graph_def, "rb") as f:
    restored_graph_def = tf.GraphDef()
    restored_graph_def.ParseFromString(f.read())

# for node in restored_graph_def.node:
#     if 'transpose' in node.name.lower():
#         print(node.name, node.op)
tf.import_graph_def(
    restored_graph_def,
    input_map=None,
    return_elements=None,
    name="")

img = cv2.imread('data/samples/bus.jpg')
img = cv2.resize(img, (416, 416))
img = img[None, :, :, :]
img = np.transpose(img, [0, 3, 1, 2])

with tf.Session() as sess:
    pred = sess.run("concat_84:0", feed_dict={'input.1:0':img})

print(pred)

# writer = tf.summary.FileWriter("./graph", graph)     
# writer.close()