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import tensorflow as tf
from PIL import Image
import numpy as np

new_model = tf.keras.models.load_model('saved_model/my_model')
imgs = ['9.jpg']
for path in imgs:
    #读取图片
    img = Image.open(path)
    img = img.resize((28, 28), Image.ANTIALIAS)
    img_arr = np.array(img.convert('L'))
    for i in range(28):
        for j in range(28):
            if img_arr[i][j] < 150:
                img_arr[i][j] = 255
            else:
                img_arr[i][j] = 0

    # 归一化
    img_arr = img_arr / 255.0

    # 添加一个维度
    x_predict = img_arr.reshape(1, 28, 28, 1)

    # 识别
    result = new_model.predict(x_predict)
    pred = tf.argmax(result[0])
    print('正在识别：{} -> {}'.format(path, pred))