Search Results for "mongo-vision" - Page 2
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Showing 386 open source projects for "mongo-vision"
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GoCV
Go package for computer vision using OpenCV 4 and beyond
GoCV gives programmers who use the Go programming language access to the OpenCV 4 computer vision library. The GoCV package supports the latest releases of Go and OpenCV v4.5.4 on Linux, macOS, and Windows. Our mission is to make the Go language a “first-class” client compatible with the latest developments in the OpenCV ecosystem. Computer Vision (CV) is the ability of computers to process visual information, and perform tasks normally associated with those performed by humans. CV software... -
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Open-CD
A Change Detection Repo Standing on the Shoulders of Giants
Open-CD is an open source change detection toolbox based on a series of open source general vision task tools. -
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HARFANG 3D engine
HARFANG 3D source code public repository
HARFANG 3D builds real-time 3D tools for industry professionals. Its software suite is tailored to developers, designers and engineers aiming to efficiently and seamlessly develop, implement & deploy 3D solutions (HMI, VR/AR, simulation, interactive 3D), regardless of development language or platform constraints. HARFANG Studio is the ideal 3D editor for creating real-time scenes & animations that match your design vision. It can manage the entire 3D graphics production workflow in a simple... -
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Covalent
Teradata UI Platform built on Angular Material
Reusable tested tools to build robust Angular Material & Angular applications. Vision: To build an atomic, reusable component platform for Teradata to consume, while collaborating in an open-source model. Covalent is a reusable UI platform from Teradata for building web applications with common standards and tooling. It is based on Angular and Material Design. Visualize your data easily. ECharts is an extensive "tried and true" charting library brought to Angular as Covalent Charts. td-chart-x... -
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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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KMongo
[deprecated] KMongo - a Kotlin toolkit for Mongo
KMongo was created in 2016, when there was no official MongoDB Kotlin driver. KMongo features are available via Kotlin extensions - you use transparently the core MongoDB java driver API (both sync and reactive streams (ie async) drivers are supported). -
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FiftyOne
The open-source tool for building high-quality datasets
The open-source tool for building high-quality datasets and computer vision models. Nothing hinders the success of machine learning systems more than poor-quality data. And without the right tools, improving a model can be time-consuming and inefficient. FiftyOne supercharges your machine learning workflows by enabling you to visualize datasets and interpret models faster and more effectively. Improving data quality and understanding your model’s failure modes are the most impactful ways... -
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Arctic TimeSeries and Tick store
High performance datastore for time series and tick data
Arctic is a timeseries/dataframe database that sits atop MongoDB. Arctic supports serialization of a number of datatypes for storage in the mongo document model. Serializes a number of data types eg. Pandas DataFrames, Numpy arrays, Python objects via pickling etc. so you don't have to handle different datatypes manually. Uses LZ4 compression by default on the client side to get big savings on network / disk. Allows you to version different stages of an object and snapshot the state (In some... -
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AWS IoT FleetWise Edge
AWS IoT FleetWise Edge Agent
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CV-CUDA
CV-CUDA™ is an open-source, GPU accelerated library
CV-CUDA is an open-source project that enables building efficient cloud-scale Artificial Intelligence (AI) imaging and computer vision (CV) applications. It uses graphics processing unit (GPU) acceleration to help developers build highly efficient pre- and post-processing pipelines. CV-CUDA originated as a collaborative effort between NVIDIA and ByteDance. -
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DuckDuckGo for macOS
DuckDuckGo macOS Browser
We are excited to engage the community in development. DuckDuckGo is growing fast and we continue to expand our fully distributed team. We embrace diverse perspectives and seek out passionate, self-motivated people, committed to our shared vision of raising the standard of trust online. -
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LLaVA
Visual Instruction Tuning: Large Language-and-Vision Assistant
Visual instruction tuning towards large language and vision models with GPT-4 level capabilities. -
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference... -
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graceful
Gracefully exit HTTP servers (Express/Koa/Fastify/etc), databases
Gracefully exit HTTP servers (Express/Koa/Fastify/etc), databases (Mongo/Mongoose), Redis clients, Bree job schedulers, and custom handlers. See the Express, Koa, Fastify, or Other code snippet examples and Instance Options. You can pass Instance Options to customize your graceful handler (e.g. if you have more than one server, or wish to close both a Redis connection and a server at the same time). -
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Qmgo
The Go driver for MongoDB. It‘s based on mongo-go-driver
Qmgo is a Go driver for MongoDB . It is based on MongoDB driver, but easier to use like mgo (such as the chain call). Qmgo allows users to use the new features of MongoDB in a more elegant way. Qmgo is the first choice for migrating from mgo to the new MongoDB driver with minimal code changes. If your connection points to a fixed database and collection, recommend using the following way to initialize the connection. All operations can be based on cli. Qmgo supports two ways to make specific... -
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Tarsier
Vision utilities for web interaction agents
... as buttons, links, or input fields that are visible on the page; Tarsier can also tag all textual elements if you pass tag_text_elements=True. Furthermore, we've developed an OCR algorithm to convert a page screenshot into a whitespace-structured string (almost like ASCII art) that an LLM even without vision can understand. Since current vision-language models still lack fine-grained representations needed for web interaction tasks, this is critical. -
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CleanVision
Automatically find issues in image datasets
CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset! The quality of machine learning models hinges on the quality of the data used... -
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Metalhead.jl
Computer vision models for Flux
Metalhead.jl provides standard machine learning vision models for use with Flux.jl. The architectures in this package make use of pure Flux layers, and they represent the best practices for creating modules like residual blocks, inception blocks, etc. in Flux. Metalhead also provides some building blocks for more complex models in the Layers module. -
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OpenFlamingo
An open-source framework for training large multimodal models
.... We also welcome contributions! We provide an initial OpenFlamingo 9B model using a CLIP ViT-Large vision encoder and a LLaMA-7B language model. In general, we support any CLIP vision encoder. For the language model, we support LLaMA, OPT, GPT-Neo, GPT-J, and Pythia models. OpenFlamingo is a multimodal language model that can be used for a variety of tasks. It is trained on a large multimodal dataset. -
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TorchIO
Medical imaging toolkit for deep learning
TorchIO is an open-source Python library for efficient loading, preprocessing, augmentation and patch-based sampling of 3D medical images in deep learning, following the design of PyTorch. It includes multiple intensity and spatial transforms for data augmentation and preprocessing. These transforms include typical computer vision operations such as random affine transformations and also domain-specific ones such as simulation of intensity artifacts due to MRI magnetic field inhomogeneity (bias... -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment. However... -
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create-t3-app
The best way to start a full-stack, typesafe Next.js app
... offers a lightly opinionated, heavily optimized approach to creating applications using React. It's the industry standard and we're proud to build on top of it :) Prisma is the best way to work with databases in TypeScript. It provides a simple, type-safe API to query your database, and it can be used with most SQL dialects (and Mongo too!). We firmly believe TypeScript will help you be a better web developer. -
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DenoDB
MySQL, SQLite, MariaDB, PostgreSQL and MongoDB ORM for Deno
Supports PostgreSQL, MySQL, MariaDB, SQLite and MongoDB. Setting up your database with DenoDB is a four-step process. Create models, extending Model. table and fields are both required static attributes. Link your models, to add them to your database instance. Optional, create tables in your database, by using sync. Query your models! Using Mongo means adapting your models to its standards, one being the use of _id for identifying records. The only change on your side is to add an _id field... -
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thumbor
An open-source photo thumbnail service by globo.com
... the best image crop possible. Everytime a face is detected, it will crop the image around it, making sure the most important parts of the picture are preserved. Thumbor allows users to store and load images from anywhere needed. It's really simple to implement a new loader or storage. It comes packaged with file, http, redis and mongo implementations for loaders and storages. Just pick what makes sense for you or implement your own. -
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FFCV
Fast Forward Computer Vision (and other ML workloads!)
ffcv is a drop-in data loading system that dramatically increases data throughput in model training. From gridding to benchmarking to fast research iteration, there are many reasons to want faster model training. Below we present premade codebases for training on ImageNet and CIFAR, including both (a) extensible codebases and (b) numerous premade training configurations.