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shimat/opencvsharp

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6,011 stars·1,235 forks·C#·Apache-2.0·34 views

Opencvsharp

OpenCVSharp is a .NET library that wraps native OpenCV functions, providing C# developers with access to OpenCV's computer vision capabilities through an API that mirrors the native C/C++ style. It serves as a managed wrapper for image processing, feature detection, object detection, and image manipulation tasks, while also handling automatic disposal of unmanaged OpenCV resources like Mat objects to prevent memory leaks in .NET applications.

The library enables keypoint detection and descriptor extraction using algorithms such as AKAZE, BRISK, or FAST, with brute-force or FLANN-based matching for finding correspondences across images. It supports object detection through pre-trained cascade classifiers using Haar-like or LBP features, and provides conversion of OpenCV Mat objects to GDI+ Bitmap or WPF WriteableBitmap for display in .NET UI frameworks.

OpenCVSharp covers camera calibration and stereo vision, including chessboard corner detection, multi-view calibration, stereo calibration and rectification, and disparity map computation. It offers image processing operations such as color space conversion, adaptive thresholding, histogram analysis, and frequency domain transforms, along with motion analysis through optical flow estimation and background subtraction using Gaussian mixture or K-nearest neighbors models. The library also includes shape detection via Hough transforms, barcode detection and decoding, and data serialization to XML or YAML formats.

Features

  • Computer Vision Libraries - Provides a comprehensive .NET wrapper for OpenCV's computer vision capabilities.
  • .NET Wrappers - Provides a .NET wrapper that mirrors the native OpenCV C/C++ API for image processing and computer vision tasks.
  • Cascade Classifier Detections - Ships cascade classifier object detection using Haar-like and LBP features from .NET code.
  • Keypoint Descriptor Matchers - Detects keypoints and computes descriptors with brute-force or FLANN-based matching.

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  • .NET Feature Matching - Detects keypoints and computes descriptors using algorithms like AKAZE, BRISK, or FAST, and matches them with brute-force or FLANN-based methods.
  • Multi-Channel Pixel Vectors - Holds tuples of 2 to 6 elements of various numeric types for pixel data or small vectors.
  • Mat-to-Bitmap Converters - Converts OpenCV Mat objects to GDI+ Bitmap or WPF WriteableBitmap for .NET UI display.
  • Image File IO - Ships comprehensive image file reading and writing capabilities with format and compression options.
  • Color Space Conversions - Selects source and target color spaces for color conversion operations between formats like RGB and HSV.
  • .NET Image Processing Libraries - Provides a managed .NET wrapper for OpenCV image processing and computer vision operations.
  • Mat-to-Bitmap Converters - Converts OpenCV Mat objects to GDI+ Bitmap or WPF WriteableBitmap for .NET UI display.
  • OpenCV Wrappers - Wraps native OpenCV functions for image processing and computer vision tasks in C#.
  • Stereo Vision Reconstruction - Estimates camera parameters and computes depth maps from stereo image pairs for 3D reconstruction.
  • Stereo Vision Rectification - Transforms stereo image pairs so corresponding epipolar lines become horizontal for depth computation.
  • Disk Image Format Manipulation - Loads and saves images with control over format, compression, and color depth parameters.
  • C-API Wrappers - Wraps native OpenCV C functions into a .NET API that mirrors the original C/C++ interface.
  • OpenCV Wrappers - Mirrors the native OpenCV C/C++ API for image processing and analysis in .NET applications.
  • Native Bindings - Wraps native OpenCV functions by declaring C-style extern methods and marshalling data across the managed-unmanaged boundary.
  • Managed-to-Native Function Calls - Calls native OpenCV functions from .NET using P/Invoke with an API that mirrors the C/C++ style.
  • API Surface Mirroring - Exposes OpenCV functions as static methods that mirror the native C/C++ API surface.
  • Unmanaged Resource Disposals - Provides automatic disposal of unmanaged OpenCV resources to prevent memory leaks in .NET applications.
  • Geometric Primitives - Stores points, rectangles, rotated rectangles, circles, lines, and sizes in 2D space.
  • Mat-to-Bitmap Converters - Converts OpenCV Mat objects to GDI+ Bitmap or WPF WriteableBitmap for .NET UI display.
  • Perspective-n-Point Solvers - Estimates the pose of a calibrated camera from a set of 3D-to-2D point correspondences.
  • Graph-Cut Foreground Segmenters - Extracts foreground objects using iterative graph-cut segmentation initialized by a bounding rectangle.
  • Feature Descriptor Computation - Chains keypoint detection, descriptor extraction, and brute-force or FLANN-based matching.
  • Descriptor Matchers - Matches feature descriptors across images using brute-force or FLANN-based algorithms.
  • Keypoint Descriptor Extractors - Detects salient image keypoints and computes their descriptors using AKAZE, BRISK, or FAST.
  • Camera Calibration - Estimates intrinsic and extrinsic camera parameters from a set of calibration pattern images.
  • Multi-Camera Calibration Systems - Computes camera parameters using chessboard or circle grid patterns captured from different angles.
  • Pattern Corner Detection - Locates internal corners of a chessboard pattern for camera calibration.
  • Corner Feature Detections - Identifies corner features using AGAST or FAST algorithms for keypoint detection.
  • Stereo Calibration - Estimates the geometric relationship between two cameras from paired chessboard images.
  • Adaptive Thresholding Methods - Implements adaptive thresholding that computes local thresholds from pixel neighborhoods.
  • Cascade Classifier Object Detectors - Detects objects by scanning image regions with pre-trained Haar or LBP cascade classifiers.
  • Background Segmentation - Separates moving objects from static scenes using Gaussian mixture and K-nearest neighbors models.
  • Epipolar Geometry Estimators - Estimates the geometric relationship between two views from matching point pairs.
  • Flood Fill Algorithms - Fills connected regions of an image starting from a seed pixel with a specified color.
  • Geometric Shape Detection - Finds geometric primitives like circles and lines in images using the Hough transform algorithm.
  • Histogram Analysis - Calculates pixel intensity distributions and measures histogram similarity using chi-squared or Earth Mover's Distance.
  • Adaptive Contrast Enhancers - Enhances local contrast using Contrast Limited Adaptive Histogram Equalization.
  • Video Frame Capture - Captures frames from cameras or video files and writes processed frames to output video streams.
  • Video Foreground Segmentation Models - Ships Gaussian mixture and K-nearest neighbours models to separate foreground from static scenes.
  • Image Frequency Domain Transforms - Applies discrete cosine and Fourier transforms to convert images between spatial and frequency domains.
  • Binary Image Distance Transforms - Computes distance transforms on binary images to measure pixel proximity to background regions.
  • Pixel Connectivity Analysis - Labels connected regions of foreground pixels in binary images and returns blob properties.
  • Luminance Thresholders - Binarizes images using locally computed thresholds that adapt to varying illumination conditions.
  • Edge-Preserving Filters - Smooths images while preserving sharp edges using edge-preserving decomposition methods.
  • Managed Pixel Buffer Conversions - Converts OpenCV Mat pixel data to GDI+ Bitmap or WPF WriteableBitmap for .NET UI display.
  • Application Frameworks - Wrapper for the OpenCV computer vision library.
  • Image Processing - Cross-platform wrapper for OpenCV.

    • Star history

    Star history chart for shimat/opencvsharpStar history chart for shimat/opencvsharp

    How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

    Frequently asked questions

    What does shimat/opencvsharp do?

    OpenCVSharp is a .NET library that wraps native OpenCV functions, providing C# developers with access to OpenCV's computer vision capabilities through an API that mirrors the native C/C++ style. It serves as a managed wrapper for image processing, feature detection, object detection, and image manipulation tasks, while also handling automatic disposal of unmanaged OpenCV resources like Mat objects to prevent memory leaks in .NET applications.

    What are the main features of shimat/opencvsharp?

    The main features of shimat/opencvsharp are: Computer Vision Libraries, .NET Wrappers, Cascade Classifier Detections, Keypoint Descriptor Matchers, .NET Feature Matching, Multi-Channel Pixel Vectors, Mat-to-Bitmap Converters, Image File IO.

    Which projects share features with shimat/opencvsharp?

    Projects with overlapping indexed features include: hybridgroup/gocv — GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and… open-mmlab/mmcv — mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing… accord-net/framework — This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries… dlemstra/magick.net — Magick.NET is a C# image processing library that serves as a .NET wrapper for ImageMagick. It provides a raster… kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… realsenseai/librealsense — The Intel RealSense SDK is a software development kit providing drivers and libraries for interfacing with depth…

    Projects sharing features with Opencvsharp

    These projects share indexed features with Opencvsharp. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
    • hybridgroup/gocvhybridgroup avatar

      hybridgroup/gocv

      7,463View on GitHub↗

      GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and deep learning inference engine, providing programmatic access to a wide range of algorithms for image manipulation, object detection, and video analysis. The project differentiates itself through high-performance native bindings and hardware acceleration. It utilizes a foreign function interface to map Go calls to C++ functions and includes a hardware-agnostic backend dispatch to route neural network tasks to computation engines such as CUDA and OpenVINO. The library covers a br

      Go
      View on GitHub↗7,463
    • open-mmlab/mmcvopen-mmlab avatar

      open-mmlab/mmcv

      6,446View on GitHub↗

      mmcv is a foundation library for computer vision based on PyTorch. It provides a comprehensive system for constructing convolutional neural networks, a toolkit for image and video preprocessing, and a collection of high-performance deep learning vision operators. The project is distinguished by its hardware-accelerated kernels for complex operations such as deformable convolutions and region pooling. It features a configuration-driven framework that allows for the dynamic instantiation of network layers and the registration of custom modules without modifying code. The library covers a broad

      Python
      View on GitHub↗6,446
    • accord-net/frameworkaccord-net avatar

      accord-net/framework

      4,540View on GitHub↗

      This project is a scientific computing framework for the .NET ecosystem, providing a comprehensive suite of libraries for numerical analysis, statistics, and mathematical optimization. It serves as a foundational toolkit for developing applications in machine learning, digital signal processing, and computer vision. The framework provides specialized toolkits for training and deploying predictive models, including neural networks, support vector machines, and decision trees. It further distinguishes itself with deep integrations for real-time visual analysis, such as object tracking and facia

      C#
      View on GitHub↗4,540
    • dlemstra/magick.netdlemstra avatar

      dlemstra/Magick.NET

      3,907View on GitHub↗

      Magick.NET is a C# image processing library that serves as a .NET wrapper for ImageMagick. It provides a raster graphics engine for rendering text, drawing graphics, and manipulating images using a native interface. The library handles the conversion of vector files, such as PDF, EPS, and PostScript, into raster formats. It also includes tools for extracting image metadata, such as EXIF data and raw thumbnails. The system covers a wide range of image manipulation capabilities, including resizing, format conversion, watermarking, and the merging of multiple images into static or animated file

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