forked from xuos/xiuos
38d2cb3c85
1.fix some Kconfig file 2.add tensorflow-lite-for-mcu in knowing file 3.add mnist application,note the application cannot be used with RAM less than 500K. 4.the version need to separate application and OS(rtt),later by using add transform layer to solve it.
37 lines
964 B
Python
37 lines
964 B
Python
#!/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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