30 lines
935 B
Python
30 lines
935 B
Python
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# TensorFlow and tf.keras
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import tensorflow as tf
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from tensorflow import keras
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# Helper libraries
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import numpy as np
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import cv2
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# load an image
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Testing_img_path = "./Testing_images/0.jpg"
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input_image = cv2.imread(Testing_img_path,cv2.IMREAD_GRAYSCALE)
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# Preprae data
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input_image = cv2.resize(input_image,(28, 28))
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input_image = cv2.bitwise_not(input_image) # invert Black to White like data input when trained (Line is White)
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input_image = np.expand_dims(input_image, axis=0) # Change the shape of image array like input image when trained
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# ***load model***
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loadpath = "num_reader.h5"
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model = tf.keras.models.load_model(loadpath)
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# Make predictions
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predictions = model.predict(input_image)
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print(np.argmax(predictions))
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# Visualize, check the answer
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Original_input_image_testing = cv2.imread(Testing_img_path)
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cv2.imshow("This is what your computer has seen.",Original_input_image_testing)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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