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Average Ratings 0 Ratings
Description
PyQtGraph is a graphics and GUI library developed in pure Python, utilizing PyQt/PySide alongside NumPy, designed primarily for applications in mathematics, science, and engineering. Despite its complete implementation in Python, the library achieves impressive speed by effectively utilizing NumPy for numerical computations and the Qt GraphicsView framework for efficient rendering. Released under the MIT open-source license, PyQtGraph supports fundamental 2D plotting through interactive view boxes, enabling line and scatter plots with user-friendly mouse control for panning and scaling. Its ability to handle various data types, including integers, floats, and different bit depths, is complemented by functionalities for slicing multidimensional images at various angles, making it particularly useful for MRI data analysis. Furthermore, it facilitates rapid updates suitable for video display or real-time interactions, along with image display features that include interactive lookup tables and level adjustments. The library also provides mesh rendering capabilities with isosurface generation, while interactive viewports allow users to rotate and zoom with ease using the mouse. Additionally, it incorporates a basic 3D scenegraph, simplifying the programming process for three-dimensional data visualization. With its robust set of features, PyQtGraph caters to a wide range of visualization needs and enhances user experience through interactivity.
Description
Scikit-image is an extensive suite of algorithms designed for image processing tasks. It is provided at no cost and without restrictions. Our commitment to quality is reflected in our peer-reviewed code, developed by a dedicated community of volunteers. This library offers a flexible array of image processing functionalities in Python. The development process is highly collaborative, with contributions from anyone interested in enhancing the library. Scikit-image strives to serve as the definitive library for scientific image analysis within the Python ecosystem. We focus on ease of use and straightforward installation to facilitate adoption. Moreover, we are judicious about incorporating new dependencies, sometimes removing existing ones or making them optional based on necessity. Each function in our API comes with comprehensive docstrings that clearly define expected inputs and outputs. Furthermore, arguments that share conceptual similarities are consistently named and positioned within function signatures. Our test coverage is nearly 100%, and every piece of code is scrutinized by at least two core developers prior to its integration into the library, ensuring robust quality control. Overall, scikit-image is committed to fostering a rich environment for scientific image analysis and ongoing community engagement.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Python
Yes
Akira AI
No
Cython
No
Label Studio
No
MLReef
No
PostgresML
No
Yamak.ai
No
Yandex Data Proc
No
ZenML
No
Integrations
Python
Yes
Akira AI
Yes
Cython
Yes
Label Studio
Yes
MLReef
Yes
PostgresML
Yes
Yamak.ai
Yes
Yandex Data Proc
Yes
ZenML
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
PyQtGraph
Website
www.pyqtgraph.org
Vendor Details
Company Name
scikit-image
Country
United States
Website
scikit-image.org