Created
June 17, 2022 15:01
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Retrieving the features of the VGG16 model
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| import numpy as np | |
| def get_features_and_labels(dataset): | |
| all_features = [] | |
| all_labels = [] | |
| for images, labels in dataset: | |
| preprocessed_images = keras.applications.vgg16.preprocess_input(images) | |
| features = conv_base.predict(preprocessed_images) | |
| all_features.append(features) | |
| all_labels.append(labels) | |
| return np.concatenate(all_features), np.concatenate(all_labels) | |
| train_features, train_labels = get_features_and_labels(train_dataset) | |
| val_features, val_labels = get_features_and_labels(validation_dataset) | |
| test_features, test_labels = get_features_and_labels(test_dataset) |
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