forked from xuos/xiuos
48 lines
1.6 KiB
Python
48 lines
1.6 KiB
Python
# ==========================================================================================
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# Copyright (c) 2020 AIIT XUOS Lab
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# XiOS is licensed under Mulan PSL v2.
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# You can use this software according to the terms and conditions of the Mulan PSL v2.
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# You may obtain a copy of Mulan PSL v2 at:
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# http://license.coscl.org.cn/MulanPSL2
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# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
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# EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
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# MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
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# See the Mulan PSL v2 for more details.
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# ==========================================================================================
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#!/usr/bin/env python3
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import tensorflow as tf
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print("TensorFlow version %s" % (tf.__version__))
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def show(image):
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for i in range(28):
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for j in range(28):
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if image[i][j] > 0.3:
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print('#', end = '')
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else:
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print('.', end = '')
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print()
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digit_file_path = 'digit.h'
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digit_content = '''const float mnist_digit[] = {
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%s
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};
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const int mnist_label = %d;
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'''
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if __name__ == '__main__':
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mnist = tf.keras.datasets.mnist
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(_, _), (test_images, test_labels) = mnist.load_data()
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index = 0
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shape = 28
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image = test_images[index].astype('float32')/255
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label = test_labels[index]
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print('label: %d' % label)
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#show(image)
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digit_data = (',\n ').join([ (', ').join([ '%.2f' % image[row][col] for col in range(shape)]) for row in range(shape)])
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digit_file = open(digit_file_path, 'w')
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digit_file.write(digit_content % (digit_data, label))
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digit_file.close()
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