Implementation for paper MLP-Mixer: An all-MLP Architecture for Vision

Set up dataset.

Create 2 folders train and validation in the data folder (which was created already). Then Please copy your images with the corresponding names into these folders.

• train folder was used for the training process
• validation folder was used for validating training result after each epoch

This library use image_dataset_from_directory API from Tensorflow 2.0 to load images.

Train model

python train.py --epochs ${epochs} --num-classes ${num_classes}

python train.py --epochs 10 --num-classes 2

Testing model

python predict.py --test-file-path ${test_file_path}

where test_file_path is the path of your test image.

Example:

python predict.py --test-file-path ./data/test/Image.jpg