CS302-Python-2020-Group39
Dataset:
For access to our data-set, click on the Kaggle link and press the download tab: https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia
Instructions for training particular models:
AlexNet: on line 175, change model to equal model = AlexNet().to(device)
LeNet5: on line 175, change model to equal model = LeNet5().to(device)
VGG-16: on line 175, change model to equal model = vgg16().to(device)
ResNet50: on line 175, change model to equal model = ResNet50().to(device)
Instructions on loading the dataset:
- on the lines 159 and 163 attach the file location path for trainset and testset:
- trainset = torchvision.datasets.ImageFolder(root='./data/chest_xray/train', transform=transform)
- testset = torchvision.datasets.ImageFolder(root='./data/chest_xray/test', transform=transform)
Results
AlexNet produced the best results out of the 4 models. It’s final epoch returns an accuracy of 86%. Both ResNet50 and LeNet5 had similar results of 82% and 81% respectively. VGG16 had the lowest accuracy of 76%.
