forked from s452751/AI_PRO
minor changes
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@ -16,6 +16,7 @@ for img in os.listdir(path_potatoes):
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pic = cv2.resize(pic,(size,size))
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pic = cv2.resize(pic,(size,size))
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training_data_potatoes.append([pic])
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training_data_potatoes.append([pic])
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np.save(os.path.join('neural_network','potatoes-dataset'),np.array(training_data_potatoes))
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np.save(os.path.join('neural_network','potatoes-dataset'),np.array(training_data_potatoes))
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saved_potatoes = np.load(os.path.join('neural_network','potatoes-dataset.npy'))
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saved_potatoes = np.load(os.path.join('neural_network','potatoes-dataset.npy'))
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@ -32,6 +33,10 @@ np.save(os.path.join('neural_network','beetroot-dataset'),np.array(training_data
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saved_potatoes = np.load(os.path.join('neural_network','beetroot-dataset.npy'))
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saved_potatoes = np.load(os.path.join('neural_network','beetroot-dataset.npy'))
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# for i in range(5):
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dict = {
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# plt.imshow(np.array(training_data_potatoes[i]).reshape(size,size,3))
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'beetroots': training_data_beetroot,
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# plt.show()
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'potatoes': training_data_potatoes
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}
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print(dict)
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np.save(os.path.join('neural_network','dataset'), np.array(dict))
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