Python library 1.1.0 version

This library facilitates various visualizations of inference results from ultralytics segmentation/detection models, including cropping with overlays, as well as a patch-based inference algorithm enabling the detection of small objects in images. It caters to both object detection and instance segmentation tasks.

Model Support: The library offers support for multiple ultralytics deep learning models, such as YOLOv8, YOLOv9, SAM, and RTDETR. Users can select from pre-trained options or utilize custom-trained models to best meet their task requirements.

Functional Python library 1.0.2 version

A fully functional Python library, implemented solely through the utilization of the Non-Maximum Suppression (NMS) algorithm based on bounding boxes from model inferences, to suppress duplicates arising from overlapping patches.