Malaria-Cell-Detection-Model

Dataset can be found at https://www.kaggle.com/iarunava/cell-images-for-detecting-malaria

How I built it

1. Download the dataset
2. Import the dataset into PyTorch using ImageFolder (resize and crop each image)

dataset = ImageFolder(data_dir, tt.Compose([tt.Resize(64), 
                                            tt.RandomCrop(64),
                                            tt.ToTensor()]))

3. Split dataset into two groups: training set and validating set

train_ds, valid_ds = random_split(dataset, [train_size, val_size])

4. Prepare the set for training (using DataLoader and make_grid)
5. Move the dataset to the GPU
6. Define a neural network (ResNet9)
7. Train the model
8. Plot losses against epochs
9. Test model and record the results