Search Results for "image" - Page 10
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Showing 1099 open source projects for "image"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MDCx
Movie metadata scraper and organizer for media libraries and NFO
...MDCx can download information such as titles, cast data, artwork, and other metadata, then generate standardized NFO files compatible with media management systems. It also supports image processing tasks such as downloading and cropping artwork used by media centers. It includes several interfaces, allowing users to operate it through a graphical desktop application, a browser-based web interface, or command-line utilities depending on their workflow. Its architecture separates core scraping logic from the user interfaces, allowing the same metadata processing system to be reused across different modes. -
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Jupyter Docker Stacks
Ready-to-run Docker images containing Jupyter applications
...These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run consistently across machines. Users can pull a particular stack image and launch a Jupyter server without worrying about installing Python, R, or complex dependencies themselves — everything needed is baked into the container. This makes the stacks especially useful for education, demos, collaborative coding, and CI/CD workflows where consistent environments are crucial, and it integrates smoothly with cloud platforms, JupyterHub deployments, and Binder for interactive sharing. -
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MiniCPM-o
A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming
MiniCPM-o 2.6 is a cutting-edge multimodal large language model (MLLM) designed for high-performance tasks across vision, speech, and video. Capable of running on end-side devices such as smartphones and tablets, it provides powerful features like real-time speech conversation, video understanding, and multimodal live streaming. With 8 billion parameters, MiniCPM-o 2.6 surpasses its predecessors in versatility and efficiency, making it one of the most robust models available. It supports... -
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Factorio
Factorio headless server in a Docker container
...Factorio is a factory-building simulation game in which players automate production lines, research technologies, and manage complex industrial systems, and the repository focuses specifically on hosting the game server in a containerized environment. By packaging the server into a Docker image, the project simplifies the process of deploying and maintaining multiplayer servers across different operating systems and cloud environments. The container automatically handles dependencies, configuration, and updates, making it easier for system administrators and hobbyists to run dedicated Factorio servers. Users can configure server settings, maps, mods, and saved games through mounted volumes and environment variables within the container. -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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SageMaker Spark Container
Docker image used to run data processing workloads
...It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker. -
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AutoPkg
Automating packaging and software distribution on macOS
AutoPkg is a system that automatically prepares software for distribution to managed clients. Recipes allow you to specify a series of simple actions which combined together can perform complex tasks, similar to Automator workflows or Unix pipes. -
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wikmd
A file based wiki that uses markdown
It’s a file-based wiki that aims to simplicity. Instead of storing the data in a database I chose to have a file-based system. The advantage of this system is that every file is directly readable inside a terminal etc. Also when you have direct access to the system you can export the files to anything you like. -
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Gemma
Gemma open-weight LLM library, from Google DeepMind
Gemma, developed by Google DeepMind, is a family of open-weights large language models (LLMs) built upon the research and technology behind Gemini. This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for... -
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folderify
Generate pixel-perfect macOS folder icons in the native style
...You can only assign one version of an icon to a folder. Dark color scheme is only supported for macOS 11.0 (and later) right now. Make sure the corner pixels of the mask image are transparent. They are used for empty margins. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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Keras Hub
Pretrained model hub for Keras 3
Keras Hub is a repository of pre-trained models for Keras 3, offering a collection of ready-to-use models for various machine-learning tasks. KerasHub is an extension of the core Keras API; KerasHub components are provided as Layer and Model implementations. If you are familiar with Keras, congratulations. You already understand most of KerasHub. -
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Transparent Background
This is a background removing tool powered by InSPyReNet
This is a background-removing tool powered by InSPyReNet (ACCV 2022). You can easily remove the background from the image or video or bunch of other stuffs when you can make the background transparent! We basically follow the virtual camera settings from pyvirtualcam. If you do not choose to install virtual camera, it will visualize real-time output with cv2.imshow. Use another checkpoint file. Default is trained with composite dataset and will be automatically downloaded if not available. -
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Vision Transformer Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA
This repository provides a from-scratch, minimalist implementation of the Vision Transformer (ViT) in PyTorch, focusing on the core architectural pieces needed for image classification. It breaks down the model into patch embedding, positional encoding, multi-head self-attention, feed-forward blocks, and a classification head so you can understand each component in isolation. The code is intentionally compact and modular, which makes it easy to tinker with hyperparameters, depth, width, and attention dimensions. ... -
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Android Emulator Container Scripts
Minimal scripts to run the emulator in a container for various systems
...A built-in WebRTC bridge lets you stream the emulator screen to a browser with interactive input, which is ideal for CI dashboards, remote debugging, or demo environments. The project focuses on reproducibility and scale: you define which system image to boot, how to persist or reset data, and how many instances to run, then schedule them like any other workload. GPU acceleration, audio, and sensors can be enabled depending on your host and cluster capabilities, while fallbacks like SwiftShader keep things usable when no GPU is available. -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
...This makes learning focus on semantics and structure, yielding features that transfer well with simple linear probes and minimal fine-tuning. The repository provides training recipes, data pipelines, and evaluation utilities for image JEPA variants and often includes ablations that illuminate which masking and architectural choices matter. Because the objective is non-autoregressive and operates in embedding space, JEPA tends to be compute-efficient and stable at scale. The approach has become a strong alternative to contrastive or pixel-reconstruction methods for representation learning. -
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Convert images to chords.
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supervision
We write your reusable computer vision tools
We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us. -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
...It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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Qwen-MM-Plugins
Make any agent harness multimodal-native
Qwen-MM-Plugins is a collection of native multimodal capabilities that can extend Qwen-powered agent harnesses beyond text-only workflows. Each capability combines an instructional skill with an optional MCP server that exposes specialized tools. The core package can inspect images, videos, documents, and 3D models while providing OCR, grounding, segmentation, transcription, and visual question answering. Additional modules support long-video memory, audio-video analysis, media generation,... -
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VLMEvalKit
Open-source evaluation toolkit of large multi-modality models (LMMs)
VLMEvalKit is an open-source evaluation toolkit designed for benchmarking large vision-language models that combine visual understanding with natural language reasoning. The toolkit provides a unified framework that allows researchers and developers to evaluate multimodal models across a wide range of datasets and standardized benchmarks with minimal setup. Instead of requiring complex data preparation pipelines or multiple repositories for each benchmark, the system enables evaluation... -
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PaddleX
PaddlePaddle End-to-End Development Toolkit
PaddleX is a deep learning full-process development tool based on the core framework, development kit, and tool components of Paddle. It has three characteristics opening up the whole process, integrating industrial practice, and being easy to use and integrate. Image classification and labeling is the most basic and simplest labeling task. Users only need to put pictures belonging to the same category in the same folder. When the model is trained, we need to divide the training set, the validation set and the test set. Therefore, we need to divide the above data. Using the paddlex command, the data set can be randomly divided into 70% training set, 20% validation set and 10% test set. ... -
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LingBot-World
Advancing Open-source World Models
LingBot-World is an open-source, high-fidelity world simulator designed to advance the state of world models through video generation. Built on top of Wan2.2, it enables realistic, dynamic environment simulation across diverse styles, including real-world, scientific, and stylized domains. LingBot-World supports long-term temporal consistency, maintaining coherent scenes and interactions over minute-level horizons. With real-time interactivity and sub-second latency at 16 FPS, it is... -
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ModelScope
Bring the notion of Model-as-a-Service to life
ModelScope is built upon the notion of “Model-as-a-Service” (MaaS). It seeks to bring together most advanced machine learning models from the AI community, and streamlines the process of leveraging AI models in real-world applications. The core ModelScope library open-sourced in this repository provides the interfaces and implementations that allow developers to perform model inference, training and evaluation. In particular, with rich layers of API abstraction, the ModelScope library offers... -
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VT.ai
Multimodal AI chat app with dynamic conversation routing
VT.ai is a minimal multimodal AI chat application designed to provide a simple and efficient interface for interacting with large language models. It focuses on delivering a clean user experience with support for both text and multimodal inputs, allowing users to engage with models in a flexible way. The application is lightweight and designed to run with minimal overhead, making it suitable for quick interactions and experimentation. It integrates with local model providers such as Ollama,... -
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Unstructured.IO
Open source libraries and APIs to build custom preprocessing pipelines
The unstructured library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of unstructured revolve around streamlining and optimizing the data processing workflow for LLMs. unstructured modular bricks and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and is efficient in transforming unstructured data into... -
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Formatix Image Converter is a free batch image converter and resizer for Windows. Supports HEIC, AVIF, WebP, SVG, JPEG, PNG, BMP, TIFF, GIF and ICO. Works 100% offline — no uploads, no internet required, no file limits, no ads. Key Features: - Batch conversion — hundreds of images in one operation - Multi-threaded processing for fast performance - 5 resize modes including smart crop - Adjustable quality (JPEG, WebP, AVIF, HEIC) - Drag & Drop support - 6 interface languages: English, Русский, Українська, Deutsch, Suomi, 中文 - Light / Dark theme - Built-in side-by-side image comparison - No installation needed — just run the .exe Input Formats: JPEG, PNG, WebP, AVIF, HEIC/HEIF, SVG, BMP, TIFF, GIF, ICO Output Formats: AVIF, WebP, JPEG, HEIC, PNG, BMP, TIFF, ICO
