resnet_v2_101训练自己的数据,完成分类任务之模型推理

训练完模型肯定是要推理的啦~在这里提醒一下，训练时图像做了什么预处理推理时最好也同样做相应的预处理，否则预测结果会有意外收获，比如意外的差。

port tensorflow as tf 
import numpy as np 
import os
import resnet_v2 as resnet_v2
import tensorflow.contrib.slim as slim
import cv2

height,width=224,224
X=tf.placeholder(tf.float32,[None,height,width,3])
def Infer(checkpoint_path,image_path):
    nameList=os.listdir(image_path)
    with slim.arg_scope(resnet_v2.resnet_arg_scope()):
        net, end_points = resnet_v2.resnet_v2_101(X,num_classes=3,is_training=False)
    with tf.Session() as sess:
        saver=tf.train.Saver(tf.global_variables())
        saver.restore(sess,checkpoint_path)
        num_classes =3
        k=1
        corret=0
        wrong=0
        Info=[]
&nb