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exp2/source/predict.py

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+import tensorflow as tf
+from PIL import Image
+import numpy as np
+import matplotlib.pyplot as plt
+
+from train import CNN
+
+'''
+python 3.9 
+tensorflow 2.0.0b0
+pillow(PIL) 4.3.0
+''' 
+
+
+class Predict(object):
+    def __init__(self):
+        latest = tf.train.latest_checkpoint('./ckpt')
+        self.cnn = CNN()
+        # 恢复网络权重
+        self.cnn.model.load_weights(latest)
+
+    def predict(self, image_path):
+        # 以黑白方式读取图片
+        img = Image.open(image_path).convert('L')
+        img = np.reshape(img, (28, 28, 1)) / 255.
+        x = np.array([1 - img])
+        y = self.cnn.model.predict(x)
+
+        # 因为x只传入了一张图片，取y[0]即可
+        # np.argmax()取得最大值的下标，即代表的数字
+        print(image_path)
+#        print(y[0])
+        print('        -> Predict digit', np.argmax(y[0]))
+        plt.figure("Image")  # 图像窗口名称
+        plt.imshow(img)
+        plt.axis('on')  # 关掉坐标轴为 off
+        plt.title(np.argmax(y[0]))  # 图像题目 # 必须有这个，要不然无法显示
+        plt.show()
+
+
+if __name__ == "__main__":
+    app = Predict()
+    app.predict('./test_images/0.png') 
+    app.predict('./test_images/1.png')
+    app.predict('./test_images/4.png')