Search Results for "image + segmentation"
Sort By:
Showing 19 open source projects for "image + segmentation"
View related business solutions-
Red Hat Enterprise Linux on Microsoft AzureRed Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
-
Secure remote access solution to your private network, in the cloud or on-prem.OpenVPN is here to bring simple, flexible, and cost-effective secure remote access to companies of all sizes, regardless of where their resources are located.
-
1
MatImage
Image Processing library for Matlab
matImage is an open-source MATLAB library for image processing and analysis. It provides a variety of tools for image enhancement, segmentation, and feature extraction. It’s especially useful for users working on biomedical images or those needing detailed image analysis in MATLAB. -
2
ncnn
High-performance neural network inference framework for mobile
... Classical CNN (VGG AlexNet GoogleNet Inception), Face Detection (MTCNN RetinaFace), Segmentation (FCN PSPNet UNet YOLACT), and more. ncnn is currently being used in a number of Tencent applications, namely: QQ, Qzone, WeChat, and Pitu. -
3
Albumentations
Fast image augmentation library and an easy-to-use wrapper
Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations... -
4
ML.NET
Open source and cross-platform machine learning framework for .NET
... that automates the process of building best performing models for your Machine Learning scenario. All you have to do is load your data, and AutoML takes care of the rest of the model building process. ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more. -
Payroll Services for Small Businesses | QuickBooksEasily pay your team and access powerful tools, employee benefits, and supportive experts with the #1 online payroll service provider. Manage payroll and access HR and employee services in one place. Pay your team automatically once your payroll setup is complete. We'll calculate, file, and pay your payroll taxes automatically.
-
5
BlenderProc
Blender pipeline for photorealistic training image generation
A procedural Blender pipeline for photorealistic training image generation. BlenderProc has to be run inside the blender python environment, as only there we can access the blender API. Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance... -
6
Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement... -
7
Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll open... -
8
Gluon CV Toolkit
Gluon CV Toolkit
GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection... -
9
Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
... on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. It has an internal queue and can process websites in parallel depending on the amount of RAM and CPUs (or GPUs) available. -
The #1 Embedded Analytics Solution for SaaS Teams.Qrvey’s comprehensive embedded analytics software enables you to design more customizable analytics experiences for your end users.
-
10
DETR
End-to-end object detection with transformers
... global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture. Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient. -
11
SwiftOCR
Fast and simple OCR library written in Swift
SwiftOCR is a fast and simple OCR library written in Swift. It uses a neural network for image recognition. As of now, SwiftOCR is optimized for recognizing short, one-line long alphanumeric codes (e.g. DI4C9CM). We currently support iOS and OS X. If you want to recognize normal text like a poem or a news article, go with Tesseract, but if you want to recognize short, alphanumeric codes (e.g. gift cards), I would advise you to choose SwiftOCR because that's where it exceeds. Tesseract... -
12
TensorFlow Object Counting API
The TensorFlow Object Counting API is an open source framework
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the... -
13
cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE... -
14
WrapImaJ
Multi-platform API for Image Processing systems in Life Sciences
WrapImaJ purposes to be a multi-platform wrapper for different Image Processing systems for: - using the Java programming language. The purpose of WrapImaJ is not to combine an exhaustive collection of all functionalities of different imaging system, but to offer a simple, concise Application Programming Interface (API) - allowing to develop imaging software, the source code of which is independent from the underlying imaging system on which it relies. In it's current form, it only... -
15
The Medical Imaging Interaction Toolkit (MITK) is a C++ class library for the development of medical imaging software with a high degree of interaction. The example application features DICOM viewing, measurement, image segmentation and registration.
-
16
DRAMMS
A Deformable Medical Image Registration Toolbox
DRAMMS is a software package designed for 2D-to-2D and 3D-to-3D deformable medical image registration tasks. Released by Section of Biomedical Image Analysis (SBIA) at the University of Pennsylvania. Some typical applications of DRAMMS include, -- Cross-subject registration of the same organ (can be brain, breast, cardiac, etc); -- Mono- and Multi-modality registration (MRI, CT, histology); -- Longitudinal registration (pediatric brain growth, cancer development, mouse brain... -
17
MDSTk is a collection of 2D/3D image processing tools aimed at medical images. It contains routines for volume data processing (3D filtering, segmentation, etc.) as well as fast low-level vector graphics library for surface and tetrahedral meshing. MDSTk has been forked by 3Dim Laboratory s.r.o. to provide better support and further push its development forward. Please check VPL (Voxel Processing Library) project available on Bitbucket (https://bitbucket.org/3dimlab/vpl).
-
18
Theba is a plugin-based image analysis framework for segmentation of and measurements on 3D and 2D images. Theba has a nice GUI that allows inspection and manipulation of the image and a wide range of plugins including segmentation.
-
19
- Previous
- You're on page 1
- Next