This repo contains the code and data used for our work on Gaze-based annotation of histopathology images. Table of contents is given below

• Dataset
  • Gaze
  • Hand
• Setup for Training
• Training
• Reference

Download our dataset here:

Gaze:

• Images used for training and testing of gaze-based object detectors can be downloaded from here.
• The labels corresponding to each file in the training and test dataset can be found in "Gaze_Data/labels/train" and "Gaze_Data/labels/test" respectively.

Hand:

• Images used for training and testing of object detectors on hand-labelled data can be downloaded from here.
• The labels corresponding to each file in the training and test dataset can be found in "Hand_Data/labels/train" and "Hand_Data/labels/test" respectively.

NOTE: Hand generated labels were used for performance evaluation of both gaze-based and hand-labelled object detectors. Therefore, the contents of both the "Gaze_Data/labels/test" and the "Hand_Data/labels/test" folders are identical.

• After Downloading the dataset, files required for training the yolo models need to be generated
• The voc_to_yolo.py file can be used to generate corrsponding files for yolov3 or yolov4

$ python voc_to_yolo.py \
  --data {pth to data folder e.g. data/Gaze_Data} \
  --version {`yolov3` or `yolov4`} \
  --classes Keratin_Pearl # Pass multiple classes using space as the delimeter

• The training code and required instructions are available for the following modules in their respective folder in the repository:
  • Yolov3
  • Yolov4

This repo was used to generate the results for the following paper on Gaze-based labelling of Pathology data.

Komal Mariam, Osama Mohammed Afzal, Wajahat Hussain, Muhammad Umar Javed, Amber Kiyani, Nasir Rajpoot, Syed Ali Khurram and Hassan Aqeel Khan, "On Smart Gaze based Annotation of Histopathology Images for Training of Deep Convolutional Neural Networks", submitted to IEEE Journal of Biomedical and Health Informatics.

BibTex Reference: Available after acceptance.