adnan-bashir-fuaad
/ ImageNet-200-Classifier.py
Created
August 26, 2018 18:02
Transfer Learning example with PyTorch on ImageNet-200. Base model is SqueezeNet
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| #!/home/adnan/anaconda3/bin/python | |
| import torch | |
| import torch.nn as nn | |
| import torch.optim as optim | |
| from torch.optim import lr_scheduler | |
| import torchvision | |
| from torchvision import datasets, models, transforms | |
| import time | |
| import os | |
| import copy |
adnan-bashir-fuaad
/ Project-Edit-Pipeline-Excerpt.py
Created
August 22, 2018 14:47
Extracting the activations from layers with Keras and pickling them for future use with Scikit-Learn
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| model = load_model('/home/adnan/Datasets/Network-weights/FCN-Classifier-Light-CIFAR-10/Classifier_CIFAR10_FCN_light_trained_models-97-0.7636.h5') | |
| layer_outputs = [layer.output for layer in model.layers] | |
| activation_model = Model(inputs=model.input, outputs=layer_outputs) | |
| def get_activations(img): | |
| layer_activations = list() | |
| activations = activation_model.predict(img) |