This repo contains demos used in the Computer Vision Systems course at BUTE (BMEVIIIMA07).
- Python 3
- PyTorch 3.2 from www.pytorch.org
- torchvision
pip install torchvision - progressbar2
pip install progressbar - visdom
pip install visdom
The first demo uses a simple neural network training implemented in plain PyTorch using nothing but autograd. You can run this demo by:
python net_plain.py
The second demo trains a neural network on random data using five different learning rate settings.
python net_torch.py
The third demo trains a small convolutional neural network on CIFAR-10. This achieves about 70% validation accuracy.
python convnet.py
The fourth demo trains a DenseNet169 net on CIFAR-10. This achieves ~95.6% validation accuracy.
python cifarTrain.py
python cifarTest.py
DenseNet implementation by https://github.com/kuangliu/pytorch-cifar