39 lines
1.1 KiB
Python
Executable file
39 lines
1.1 KiB
Python
Executable file
#!/usr/bin/env python3
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import tensorflow as tf
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import pathlib
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import random
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import matplotlib.pyplot as plt
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tf.enable_eager_execution()
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data_root = pathlib.Path('../img/')
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all_image_paths = list(data_root.glob('*/*'))
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all_image_paths = [str(path) for path in all_image_paths]
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random.shuffle(all_image_paths)
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image_count = len(all_image_paths)
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label_names = sorted(item.name for item in data_root.glob('*/') if item.is_dir())
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label_to_index = dict((name, index) for index,name in enumerate(label_names))
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all_image_labels = [label_to_index[pathlib.Path(path).parent.name]
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for path in all_image_paths]
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def preprocess_image(image):
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image = tf.image.decode_image(image, channels=3)
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image = tf.image.resize_images(image, [192, 192])
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image /= 255.0 # normalize to [0,1] range
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return image
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def load_and_preprocess_image(path):
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image = tf.read_file(path)
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return preprocess_image(image)
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image_path = all_image_paths[0]
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label = all_image_labels[0]
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image = load_and_preprocess_image(image_path)
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plt.imshow(image)
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plt.grid(False)
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plt.title(label_names[label].title())
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print()
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