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41 lines
1.1 KiB
41 lines
1.1 KiB
from PIL import Image
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import numpy as np
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import tensorflow as tf
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model_save_path = './checkpoint/mnist.ckpt'
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model = tf.keras.models.Sequential([
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tf.keras.layers.Flatten(),
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tf.keras.layers.Dense(128, activation='relu'),
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tf.keras.layers.Dense(10, activation='softmax')])
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model.load_weights(model_save_path)
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preNum = int(input("input the number of test pictures:"))
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for i in range(preNum):
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image_path = input("the path of test picture:")
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img = Image.open(image_path)
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img = img.resize((28, 28), Image.Resampling.LANCZOS)
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img_arr = np.array(img.convert('L'))
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#
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# for i in range(28):
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# for j in range(28):
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# if img_arr[i][j] < 200:
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# img_arr[i][j] = 255
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# else:
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# img_arr[i][j] = 0
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img_arr = img_arr / 255.0
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x_predict = img_arr[tf.newaxis, ...]
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result = model.predict(x_predict)
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pred = tf.argmax(result, axis=1)
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if result[0][pred] <= 0.3:
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print(result)
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print("无法判断，请重新输入！")
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else:
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print(result)
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tf.print(pred[0])
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