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Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within...

- 15 segmentation tools (FloodFill Strict, Adaptive Gaussian Threshold, Manual Brush (Freehand Lasso), Polygon Lasso (Click Points), Manual Bounding Box, Auto Bounding Box, Local Otsu Auto-Threshold, K-Means Clustering, Watershed, GrabCut AI, Canny Edge + Morphological Close, Morphologic Active Contours, Interactive Heatmap, Topographical Relief Map, Segment Anything AI) - Hybrid Layout (1 window with editor tools or Split-View with a preview window) - Intelligent file management (once a...

...To learn for library please try to use test examples at OpenCezeriLibrary\test\test. It is originally developed at el-cezeri laboratory of Siirt University, in order to establish generic framework of reusable components and software tools for machine vision, machine learning, AI and robotic applications. Currently, it holds following main concepts 1- Vision: It can access web cams, imaging source industrial cameras for manuel settings and advanced issues. Studies on accesing Leapmotion and Kinect is still under-development. 2- Machine learning: It uses Weka Software tool and some personel coded ML algorithms 3- CMatrix: Special matrix library called as CMatrix meaning Cezeri Maztrix Class. ...