StrepDetection

Detection of strep throat directly from cell phone videos.
Employing intermediate symptom classification combined with rule-based decisions for interpretable results.
Implementing strategies (hard-negative mining, contrastive learning) to combat limited and imbalanced data.

Parsing data from CVAT:

1. Download data from CVAT
   • Actions > Export Dataset > Export Format: CVAT for video 1.1.
   • This will download a folder containing an xml file with the dataset annotations.
2. Parse annotations via parse_xml.py
   • Set the xml file path and run parse_xml.py.
   • This will produce a .csv file with the video, frame, and relevant labels.
3. Merge CVAT data with .xlsx data
   • Follow the steps in data_process.ipynb.
   • This will merge the annotations from the .xlsx training review with the CVAT labels, checking for any overlap.

Model Checkpoints:

OneDrive folder containing model checkpoints.

Authored by Rishi Chandra, rchand18@jhu.edu, as part of the ARCADE Lab at Johns Hopkins University.