predict.py

#!/usr/bin/env python
# -*- coding:utf-8 -*-
#       FileName:  predict.py
#
#    Description:
#
#        Version:  1.0
#        Created:  2019-10-08 16:50:42
#  Last Modified:  2019-10-09 11:37:25
#       Revision:  none
#       Compiler:  gcc
#
#         Author:  zt ()
#   Organization:

import random
import numpy as np
import matplotlib.pyplot as plt
from keras.datasets import mnist
from keras.models import load_model

# 数据集
# 划分MNIST训练集、测试集
(_, _), (X_test, y_test) = mnist.load_data()

# 随机数
index = random.randint(0, X_test.shape[0])
x = X_test[index]
y = y_test[index]

# 显示该数字
plt.imshow(x, cmap='gray_r')
plt.title("original {}".format(y))
plt.show()

# 加载
mymodel = load_model('mnistmodel.h5')

# 预测
x.shape = (1, 784)  # 变成[[]]
# x = x.flatten()[None]  # 也可以用这个
predict = mymodel.predict(x)
# print(predict)
predict = np.argmax(predict)  # 取最大值的位置

print('index', index)
print('original:', y)
print('predicted:', predict)