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PyVision fork by Steve O'Hara
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PyVision is a object-oriented Computer Vision Toolkit (BSD Licenses) that is designed to allow the rapid prototype and analysis of computer vision algorithms. Using python as a foundation this package provides a simple framework that unifies the Matlab like functionality of scipy/numpy, Open Computer Vision Library (opencv), and other vision and machine learning software packages. In addition PyVision provides a set of analysis tools that allows the researcher to evaluate there algorithms in python or to export those results in csv format for analysis in Excel, R, or SAS. The purpose of the library is to provide a set of utilities that interface with common computer vision and machine learning libraries that will allow rapid vision algorithm prototyping. For example the current implementation has an image class which will easily translate image data between PIL, numpy array, and opencv formats. Dependencies pillow (update of PIL, the Python Image Library) scipy numpy OpenCV Features: Python based for rapid prototyping. Common data types with easy conversion. Automatically tuned or easy to configure algorithms. Numerical support from scipy. Image support from PIL. Pretrained algorithms for common tasks. Python and R based algorithms analysis. Unit tests for algorithm verification. Sample code and tutorials. Save and load configurations with python's pickle. Simple interfaces to third party software: OpenCV and libsvm. Notes: Image.asOpenCV() - Requires fix to opencv bug #1618474 included in cvs on Jan 25, 2007 18:19:21 UTC by rstanchak Releases: 1.0.0 - Many interface things have been cleaned up. Function arguments that are keywords have been change and may not work as in previous version. These include: buffer, type, filter, iter All warnings and errors from the code analysis have been fixed. 0.8.1 - Released in July 2010. This is the last release before a major upgrade and the last version to support OpenCV 1.0 with the swig bindings. 0.8.0 - Released in June 2009. This was primarily to support FaceL.
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