Search Results for "image recognition"
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Showing 173 open source projects for "image recognition"
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Tesseract OCR
Open Source OCR Engine
Tesseract is an open source OCR or optical character recognition engine and command line program. OCR is a technology that allows for the recognition of text characters within a digital image. With the latest version of Tesseract, there is a greater focus on line recognition, however it still supports the legacy Tesseract OCR engine which recognizes character patterns. Tesseract can recognize over 100 languages out-of-the-box, and can be trained to recognize other languages. ... -
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scikit-image
Image processing in Python
scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image builds on scipy.ndimage to provide a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! Read about our mission, vision, and values and how we govern the project. Major proposals... -
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Image Crop Picker
iOS/Android image picker with support for camera, video, etc.
Image Crop Picker is an iOS/Android image picker with support for camera, video, configurable compression, multiple images and cropping. Module is creating tmp images which are going to be cleaned up automatically somewhere in the future. If you want to force cleanup, you can use clean to clean all tmp files, or cleanSingle(path) to clean single tmp file. Some of these types may not be available on all iOS versions. -
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labelme Image Polygonal Annotation
Image polygonal annotation with Python
Labelme is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Image annotation for polygon, rectangle, circle, line and point. Image flag annotation for classification and cleaning. Video annotation. (video annotation). GUI customization (predefined labels / flags, auto-saving, label validation, etc). Exporting VOC-format dataset for semantic/instance segmentation. (semantic segmentation, instance segmentation). Exporting COCO-format dataset... -
Rezku Point of SaleRezku is an all-inclusive ordering platform and management solution for all types of restaurant and bar concepts. You can now get a fully custom branded downloadable smartphone ordering app for your restaurant exclusively from Rezku.
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OpenFace Face Recognition
Face recognition with deep neural networks
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google,... -
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Tesseract.js
A pure Javascript Multilingual OCR
Tesseract.js is a pure Javascript port of the popular Tesseract OCR engine. Tesseract.js' library supports more than 100 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browser and on a server with NodeJS. Tesseract.js is a javascript library that gets words in almost any spoken language out of images. The main Tesseract.js functions (ex. recognize, detect) take an image... -
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NSFWJS
Client-side indecent content checking powered by TensorFlow.js
NSFWJS is a simple JavaScript library that can quickly and quite accurately identify NSFW images, all in the client's browser. It is powered by TensorFlow.js and the NSFW detection model, and delivers around 90% accuracy that is improving each time. NSFWJS classifies images with percentages under five categories, namely: drawing and neutral, which are both safe for work; sexy, which includes sexually explicit images; and hentai and porn, which are pornographic drawings and images.... -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. ... -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
Collect! is a highly configurable debt collection softwareThe flexible & scalable debt collection software built to automate your workflow. From startup to enterprise, we have the solution for you.
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Color Thief
Grab the color palette from an image using just Javascript
The Color Thief package includes multiple distribution files to support different environments and build processes. Gets the dominant color from the image. Color is returned as an array of three integers representing red, green, and blue values. When called in the browser, the image argument expects an HTML image element, not a URL. When run in Node, this argument expects a path to the image. quality is an optional argument that must be an Integer of value 1 or greater, and defaults to 10.... -
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Caire
Content aware image resize library
Caire is a content aware image resize library based on Seam Carving for Content-Aware Image Resizing paper. An energy map (edge detection) is generated from the provided image. The algorithm tries to find the least important parts of the image taking into account the lowest energy values. Using a dynamic programming approach the algorithm will generate individual seams across the image from top to down, or from left to right (depending on the horizontal or vertical resizing) and will... -
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Computer Vision Annotation Tool (CVAT)
Interactive video and image annotation tool for computer vision
Computer Vision Annotation Tool (CVAT) is a free and open source, interactive online tool for annotating videos and images for Computer Vision algorithms. It offers many powerful features, including automatic annotation using deep learning models, interpolation of bounding boxes between key frames, LDAP and more. It is being used by its own professional data annotation team to annotate millions of objects with different properties. The UX and UI were also specially developed by the team for... -
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Jimp
An image processing library written entirely in JavaScript for Node
An image processing library for Node written entirely in JavaScript, with zero native dependencies. If you're using this library with TypeScript the method of importing slightly differs from JavaScript. Instead of using require, you must import it with ES6 default import scheme. If you're using a web bundles (webpack, rollup, parcel) you can benefit from using the module build of jimp. Using the module build will allow your bundler to understand your code better and exclude things you aren't... -
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pixelmatch
The smallest, simplest JavaScript pixel-level image comparison library
The smallest, simplest and fastest JavaScript pixel-level image comparison library, originally created to compare screenshots in tests. Features accurate anti-aliased pixels detection and perceptual color difference metrics. Inspired by Resemble.js and Blink-diff. Unlike these libraries, pixelmatch is around 150 lines of code, has no dependencies, and works on raw typed arrays of image data, so it's blazing fast and can be used in any environment (Node or browsers). Compares two images,... -
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OCRmyPDF
OCRmyPDF adds an OCR text layer to scanned PDF files
OCRmyPDF adds an optical character recognition (OCR) text layer to scanned PDF files, allowing them to be searched. PDF is the best format for storing and exchanging scanned documents. Unfortunately, PDFs can be difficult to modify. OCRmyPDF makes it easy to apply image processing and OCR (recognized, searchable text) to existing PDFs. -
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Gemini Next Chat
Deploy your private Gemini application for free with one click
Gemini Next Chat is an open-source web application that allows you to deploy your own private chat interface powered by Google’s Gemini models (e.g., Gemini 1.5, Gemini 2.0, etc.). It is built with Next.js/TypeScript and targets developers and hobbyists who want a self-hosted solution for interacting with advanced multimodal models (text, image, voice). It supports features like image recognition, voice-based conversation, plugins (web search, ArXiv search, weather, etc.), and client apps (tray app) for greater convenience. The project emphasizes “one-click” deployment, aiming to make it easy to spin up a custom chat front end without deep infra-setup. It’s licensed under MIT and has an active community of contributors; documentation and release notes note support for newer features like mixed image+text generation. ... -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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Qwen-VL
Chat & pretrained large vision language model
Qwen-VL is Alibaba Cloud’s vision-language large model family, designed to integrate visual and linguistic modalities. It accepts image inputs (with optional bounding boxes) and text, and produces text (and sometimes bounding boxes) as output. The model variants (VL-Plus, VL-Max, etc.) have been upgraded for better visual reasoning, text recognition from images, fine-grained understanding, and support for high image resolutions / extreme aspect ratios. Qwen-VL supports multilingual inputs and conversation (e.g. ... -
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Transformers
State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX
...Text, for tasks like text classification, information extraction, question answering, summarization, translation, text generation, in over 100 languages. Images, for tasks like image classification, object detection, and segmentation. Audio, for tasks like speech recognition and audio classification. Transformers provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community on our model hub. At the same time, each python module defining an architecture is fully standalone and can be modified to enable quick research experiments. -
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EasyOCR
Ready-to-use OCR with 80+ supported languages
...Model weights for the chosen language will be automatically downloaded or you can download them manually from the model hub. The idea is to be able to plug-in any state-of-the-art model into EasyOCR. There are a lot of geniuses trying to make better detection/recognition models, but we are not trying to be geniuses here. We just want to make their works quickly accessible to the public. -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively... -
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Python Client For NLP Cloud
NLP Cloud serves high performance pre-trained or custom models for NER
NLP Cloud serves high performance pre-trained or custom models for NER, sentiment-analysis, classification, summarization, dialogue summarization, paraphrasing, intent classification, product description and ad generation, chatbot, grammar and spelling correction, keywords and keyphrases extraction, text generation, image generation, blog post generation, source code generation, question answering, automatic speech recognition, machine translation, language detection, semantic search, semantic similarity, tokenization, POS tagging, embeddings, and dependency parsing. It is ready for production, served through a REST API. You can either use the NLP Cloud pre-trained models, fine-tune your own models, or deploy your own models. -
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Google AI Edge Gallery
A gallery that showcases on-device ML/GenAI use cases
...The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. Each sample is intended to be both a learning aid and a practical starting point: code is organized to show model loading, pre/post-processing, performance measurement, and common optimization knobs (quantization, NNAPI/Delegate usage, and hardware accelerators). ... -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. ... -
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Qwen2.5-Omni
Capable of understanding text, audio, vision, video
...It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds state-of-the-art performance in many multimodal benchmarks, particularly spoken language understanding, audio reasoning, image/video understanding, etc. Very strong benchmark performance across modalities (audio understanding, speech recognition, image/video reasoning) and often outperforming or matching single-modality models at a similar scale. Real-time streaming responses, including natural speech synthesis (text-to-speech) and chunked inputs for low latency interaction.
