Covid-19 Detection with Chest X ray using PyTorch

Task: Classify the Chest X-Ray Radiography Dataset into three classes 'Normal', 'Viral Pneumonia', and 'Covid'.

Dataset: Chest X-Ray Radiography Dataset

Architecture: ResNet-18

Implementation Steps:

1. Import Packages and Libraries (torch, torchvision, numpy, matplotlib, PIL, random)

2. Creating Custom Dataset - Pytorch Format

3. Image Transformations (torchvision.transforms)

4. Prepare Dataloader (torch.utils.data.Dataloader)

5. Data Visualization - Plotting (Matplotlib)

6. Creating the Model (resnet18 - pretrained)

7. Training the Model (training the model until we get 95% accuracy)

8. Final Results (predictions)

Details: Loss - Cross Entropy, Optimizer - Adams Optimizer

Results: Accuracy - 95 %

GitHub Code: https://github.com/Rubo12345/Covid-19-Detection-with-Chest-X-Ray-using-PyTorch