LIDC to COCO format

This is a simple script which converts processed numpy image and binary mask files into the COCO annotation format. The Dicom files where converted to numpy files using the repo: https://github.com/jaeho3690/LIDC-IDRI-Preprocessing

Required Files

• 2D numpy files with corresponding binary mask numpy files.
• Metadata CSV with tuples for each slice's name and classification category Test/Train/Validation Split.

This 3D numpy to 2D and generation of metadata csv will require existing file structure and metadata format.

Customization required

• I/O paths need to be changed
  • image_path_annon (line 15)
  • mask_path_annon (line 16)
  • out_path (line 18)
  • Metadata file path (line 22)
• Metadata reading and access format must be changes according to availability. It will depend on the file structure of the data and the csv file.
  • File name Attribute (line 42)
  • Mask name Attribute (line 43)
  • Class Attribute (line 44)
  • Split Attribute (line 45)
• Misc Edits
  • Decide final class for annotation (will be same as annotation from csv file)(line 68-73)
  • Numerical ID for images (line 60-65)