Provides algorithms, functions, and apps for designing and testing computer vision, 3D vision, and video processing systems. Can be used to train deep and machine learning models and can leverage multicore or GPU systems.

University of Michigan - Ann Arbor

Computer vision has tons of applications but the methods used have become relatively standardized so it's often useful to use established libraries/tools. Some examples are:
- OpenCV
- Scipy ndimage
- TensorFlow
- PyTorch Vision
- MATLAB Computer Vision Toolbox

Computer Vision Libraries

OpenCV is the largest open-source computer vision library that gives access to thousands of state of the art algorithms with detailed documentation. It has classes/functions for face detection, object identification, extraction of 3D models, tracking of movement, stitching frames, etc. Can be used in C++, Python, Java, and MATLAB. 

OpenCV

SciPy ndimage is an n-dimensional image that has a number of classes and functions for image processing and analysis. It can perform classification, feature extraction, registration, image i/o, etc.

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