library

Description

AnyLabeling is Effortless AI-assisted data labeling tool with AI support from Segment Anything and YOLO models!

AnyLabeling = LabelImg + Labelme + Improved UI + Auto-labeling

Installation

Standalone (executable)

The executable file links are provided in Assets section here

Install from source

git clone https://github.com/vietanhdev/anylabeling
cd anylabeling
pip install .

Install from PyPI

pip install anylabeling

With GPU support:

pip install anylabeling-gpu
Description

BraiAn is an open-source suite of tools designed to simplify signal quantification, analysis and visualization of large datasets typically obtained in whole-brain imaging experiments, following registration to an atlas. 

The package consists of two separate modules.

  1. BrainAnDetect: A QuPath extension for multi-channel cell segmentation across large and variable datasets. It leverages QuPath's built in algorithms for cell detection, and features additional options for refining signal quantification, including machine-learning-based object classification, region-specific cell segmentation, multiple marker co-expression analysis, and an interface for selective exclusion of damaged tissue portions.
  2. BraiAnalyse: A modular Python library for the easy navigation, visualization, and analysis of whole-brain quantification outputs.
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Description
# Install the ultralytics package from PyPI
pip install ultralytics

You can also install ultralytics directly from the Ultralytics GitHub repository. This can be useful if you want the latest development version. Ensure you have the Git command-line tool installed, and then run:

# Install the ultralytics package from GitHub
pip install git+https://github.com/ultralytics/ultralytics.git@main
Description

Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use. They excel at object detection, tracking, instance segmentation, image classification, and pose estimation tasks.

Description

Big-FISH is a python package for the analysis of smFISH images (2D/3D). It includes various methods to analyze microscopy images, such spot detection and segmentation of cells and nuclei.

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