run_imagenet_based_unsupervised_feature_experiments.sh

#!/bin/bash

# Train a RotNet model (with AlexNet architecture) on the training images of ImageNet.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=ImageNet_RotNet_AlexNet

# Train & evaluate non-linear object classifiers for the ImageNet task on the feature maps
# generated by the conv4 and conv5 convolutional layers ofthe above trained AlexNet-based RotNet model.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=ImageNet_NonLinearClassifiers_ImageNet_RotNet_AlexNet_Features

# Train & evaluate linear object classifiers for the ImageNet task on the feature maps 
# generated by the convolutional layers (i.e., conv1, conv2, conv3, conv4, and conv5) of
# the above trained AlexNet-based RotNet model.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=ImageNet_LinearClassifiers_ImageNet_RotNet_AlexNet_Features

# Train & evaluate linear object classifiers for the Places205 task on the feature maps
# generated by the convolutional layers (i.e., conv1, conv2, conv3, conv4, and conv5) of
# the above trained AlexNet-based RotNet model.
CUDA_VISIBLE_DEVICES=0 python main.py --exp=Places205_LinearClassifiers_ImageNet_RotNet_AlexNet_Features