boxmot 11.0.3

high level network definitions in tensorflow

Meta AI' Segment Anything Model (SAM) for Geospatial Data.

Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.

Fast, flexible, and advanced image augmentation library for deep learning and computer vision. Albumentations offers a wide range of transformations for images, masks, bounding boxes, and keypoints, with optimized performance and seamless integration into ML workflows.

OpenMMLab Detection Toolbox and Benchmark

ModelScope: bring the notion of Model-as-a-Service to life.

Fast inference engine for Transformer models

StarDist is a Python package designed for object detection with star-convex shapes, particularly useful in microscopy. It provides implementations for both 2D and 3D images and uses a model trained to predict distances to the object boundary along fixed rays and object probabilities. These predictions produce an overcomplete set of candidate polygons for a given image, with the final result obtained via non-maximum suppression.

StarDist is compatible with Python 3.6 to 3.10, requires TensorFlow, and provides pre-trained models for 2D images and example workflows via Jupyter notebooks, making it a versatile tool for cell detection and segmentation in microscopy.

Supervisely Python SDK.