--- title: image_tabular keywords: fastai sidebar: home_sidebar summary: "Integrate image and tabular data for deep learning." description: "Integrate image and tabular data for deep learning." ---
pip install image_tabular
This library utilizes fastai and pytorch to integrate image and tabular data for deep learning and train a joint model using the integrated data.
get_imagetabdatasets
function as below: integrate_train, integrate_valid, integrate_test = get_imagetabdatasets(image_data, tab_data)
The train, validation, and optional test datasets can then be combined in a DataBunch:
db = DataBunch.create(integrate_train, integrate_valid, integrate_test,
path=data_path, bs=bs)
Next, we create a joint model to train on both image and tabular data simultaneously:
integrate_model = CNNTabularModel(cnn_model,
tabular_model,
layers = [cnn_out_sz + tab_out_sz, 32],
ps=0.2,
out_sz=2).to(device)
Finally, we pack everying into a fastai learner and train the joint model:
learn = Learner(db, integrate_model)
learn.fit_one_cycle(10, 1e-4)
The following notebook puts everything together and shows how to use the library for the SIIM-ISIC Melanoma Classification competition on Kaggle: