v0.0.5

Populated the following properties in ConfusionMatrix class

• true_positives
• predicted_positives
• false_positives
• actual_positives
• false_negatives
• precision
• recall
• f1_score
• summary

v0.0.4

• from garuda.ops import obb_iou function is implemented as numpy variant of probiou in ultralytics. However, obb_iou works more like the iou function of supervision i.e. given n ground truth boxes and m predicted boxes, it will return nxm IoU matrix, unlike ultralytics probiou which takes n ground truth boxes, n predicted boxes and returns their one-to-one IoU vector of size n.
• Added from garuda.od import ConfusionMatrix pipeline for computing confusion matrix for OBB detection. This is heavily inspired by ConfusionMatrix from supervision.

v0.0.3

• Added label-studio CSV to YOLO OBB conversion functions
• Added bulk operations
  • Save all labels in YOLO OBB format to a directory from a label-studio CSV
  • Read all labels in YOLO OBB, convert them to YOLO AA, and save them to a new directory
• Added testing for README snippets

v0.0.2

Initial release

• Added basic functionality and populated README with useful information.