First, subscribe on Microsoft Azure. Microsoft gives a 7-day trial Subscription Key https://azure.microsoft.com/en-us/try/cognitive-services/ . We can use that Subscription key for testing purposes. you need to log into the Azure Portal with our Azure credentials. Then we need to create an Azure Computer Vision Subscription Key in the Azure portal.
IronOcr.Extensions.AdvancedScan is an Extension Package to IronOCR: https://www.nuget.org/packages/IronOcr This package is not stand-alone. The IronOcr package must also be installed first, and a IronOcr License or Trial Key must be applied. More information: https://ironsoftware.com/csharp/ocr/licensing/ Supported .NET Versions: * .NET 8 * .NET 7 * .NET 6 * .NET 5 * .NET Core 2.0 - 3.1 * .NET Framework 4.6.2 + * .NET Standard 2.0 + Features: * Support for Advanced ML Model to Read and Decode more advanced image templates * License Plate Reading * Passport (MRZ) Reading * Noisy Image and Screenshot Reading * Data Table Reading * Locate Text Regions using Computer Vision
Native binaries of MaaFramework Embedded for win-arm64.
Native binaries of MaaFramework Embedded for win-x64.
Native binaries of MaaFramework Embedded for linux-x64.
Native binaries of MaaFramework Embedded for linux-arm64.
Native binaries of MaaFramework Embedded for osx-arm64.
Native binaries of MaaFramework Embedded for osx-x64.
A .NET library for running Segment Anything Model (SAM) and SAM2 using ONNX Runtime. Provides high-performance image segmentation capabilities with support for both SAM and MobileSAM models. Features include point-based prompting, bounding box prompts, and video frame tracking with temporal memory for SAM2.
PIV-compliant facial processing library for .NET with FIPS 201-3 compliance and JPEG 2000 ROI encoding
IronOcr.Extensions.AdvancedScan is an Extension Package to IronOCR: https://www.nuget.org/packages/IronOcr This package is not stand-alone. The IronOcr package must also be installed first, and a IronOcr License or Trial Key must be applied. More information: https://ironsoftware.com/csharp/ocr/licensing/ Supported .NET Versions: * .NET 8 * .NET 7 * .NET 6 * .NET 5 * .NET Core 2.0 - 3.1 * .NET Framework 4.6.2 + * .NET Standard 2.0 + Features: * Support for Advanced ML Model to Read and Decode more advanced image templates * License Plate Reading * Passport (MRZ) Reading * Noisy Image and Screenshot Reading * Data Table Reading * Locate Text Regions using Computer Vision
IronOcr.Extensions.AdvancedScan is an Extension Package to IronOCR: https://www.nuget.org/packages/IronOcr This package is not stand-alone. The IronOcr package must also be installed first, and a IronOcr License or Trial Key must be applied. More information: https://ironsoftware.com/csharp/ocr/licensing/ Supported .NET Versions: * .NET 8 * .NET 7 * .NET 6 * .NET 5 * .NET Core 2.0 - 3.1 * .NET Framework 4.6.2 + * .NET Standard 2.0 + Features: * Support for Advanced ML Model to Read and Decode more advanced image templates * License Plate Reading * Passport (MRZ) Reading * Noisy Image and Screenshot Reading * Data Table Reading * Locate Text Regions using Computer Vision
TorchImage seamlessly integrates powerful image processing capabilities into TorchSharp using SixLabors.ImageSharp
TorchImage.WinForms provides a default WinForms ImageViewer for TorchSharp with TorchImage
YoloDotNet is a blazing-fast, modern C# library for real-time object detection, classification, segmentation, OBB, pose estimation — and tracking. Powered by ONNX Runtime, CUDA acceleration, and now NVIDIA TensorRT, it effortlessly handles images and video streams with ultra-low latency. Supports a wide range of cutting-edge models including YOLOv5u, YOLOv8, YOLOv9, YOLOv10, YOLOv11, YOLOv12, Yolo-World, and YOLO-E. Whether you’re building smart cameras, analytics dashboards, or unlocking real-time machine vision, YoloDotNet has you covered.
.NET for Android and MAUI bindings for the Android Java library 'androidx.camera:camera-mlkit-vision'. Library description: MLKit vision components for the Jetpack Camera Library, a library providing a seamless integration that enables camera driven computer vision features across all of Android.
Implementing the Florence-2-base model for image understanding. Supports captioning, OCR, and object detection with optional phrase grounding. Uses ONNX models from huggingface.co/onnx-community/Florence-2-base. Enables various output tasks including detailed captioning, region-based OCR, and flexible object detection.
The C# SDK for EyesOnIt. EyesOnIt is a computer vision product based on a Large Vision Model. The EyesOnIt model was trained on 2 billion images. It detects thousands of types of objects and events based on natural language descriptions. Using this SDK, EyesOnIt can be easily integrated into existing products or projects by those without advanced computer vision or data science skills. EyesOnIt is container based software that can easily be deployed at the edge, on-premises or in cloud environments.