Transfer_ViT

Pretraining and finetuning different vision transformer models on the ImageNet and Ham10000 dataset.

This repository constians implementation of 11 image classifier models.
List of implemented models:

1. VGGNet19bn
2. ResNet152
3. DenseNet
4. InceptionV3
5. ViT_base
6. DeepViT_base
7. CaiT_base
8. T2TViT_base
9. ViT_pretrained
10. DeiT_pretrained
11. BeiT_pretrained

Data Preprocessing:

Carry out the following steps to download and preprocess the dataset:

1. Download the HAM10000 dataset from the following link: https://www.kaggle.com/datasets/kmader/skin-cancer-mnist-ham10000
   
2. Extract the zip file and put all put the HAM10000 folder in the parent directory.
   
3. Copy all the images from the HAM10000_images_part_2 folder and paste them into the HAM10000_images_part_1 folder
4. Run the data_preprocessing.py script

Implementing models:

To implement each model run the python script with the model name