Chest-X-Ray-Classification.

Pytorch implementation of Chest-X-ray-Classification

Dataset

Covid-19 Chest X-Ray
Chest X-Ray images
Clasess:

• Normal
• Bacteria
• Covid-19

Set	#Normal	#Bacteria	#Covid-19
#images	1349	2538	156

Installations
pip install torch, torchvision, tensorflow, sklearn

Imbalanced Data (Under sampling, Over sampling, Class weights):

Data Augmentation ('noise', 'RandomRotation', 'RandomHorizontalFlip', 'brightness', 'contrast', 'RandomResizedCrop'):

'Noise' transforms.Compose([transforms.ToTensor(), AddGaussianNoise(0.1, 0.08)])

'RandomRotation', 5%
transforms.Compose([transforms.ToTensor(), transforms.RandomRotation(degrees=5)])

'RandomHorizontalFlip', 90% probability
transforms.Compose([transforms.ToTensor(), transforms.RandomHorizontalFlip(p=0.9)])
'brightness', 50%
transforms.Compose([transforms.ToTensor(), transforms.ColorJitter(brightness=0.5)])

'contrast', 50%
transforms.Compose([transforms.ToTensor(), transforms.ColorJitter(contrast=0.5)])

'RandomResizedCrop', original size=28X28 pixels
transforms.Compose([transforms.ToTensor(), transforms.RandomResizedCrop(size=(28, 28))])