Search Results for "image steganography code" - Page 2
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Showing 202 open source projects for "image steganography code"
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Step1X-Edit
A SOTA open-source image editing model
Step1X-Edit is a state-of-the-art open-source image editing model/framework that uses a multimodal large language model (LLM) together with a diffusion-based image decoder to let users edit images simply via natural-language instructions plus a reference image. You supply an existing image and a textual command — e.g. “add a ruby pendant on the girl’s neck” or “make the background a sunset over mountains” — and the model interprets the instruction, computes a latent embedding combining the... -
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Aider
Aider is AI pair programming in your terminal
Aider is an AI pair programming tool that runs directly in your terminal, helping developers build new projects or extend existing codebases faster and more confidently. It works alongside you like a coding partner, using powerful large language models to understand your code and implement precise changes. Aider creates a structured map of your entire repository, allowing it to handle large and complex projects effectively. It supports over 100 programming languages, making it flexible for... -
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CycleGAN and pix2pix in PyTorch
Image-to-Image Translation in PyTorch
...The code supports standard training and inference pipelines, and as of recent updates, compatibility with the latest Python and PyTorch versions (e.g. Python 3.11, PyTorch 2.4) as well as support for distributed/multi-GPU training for scalable workflows. Because of its flexibility, users can apply it to many tasks: e.g. style transfer between domains (e.g. season changes, art-to-photo, etc.), mapping sketches/edges to real images, image colorization, day-to-night, photo enhancement, and more. -
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OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. -
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ML Sharp
Sharp Monocular View Synthesis in Less Than a Second
ML Sharp is a research code release that turns a single 2D photograph into a photorealistic 3D representation that can be rendered from nearby viewpoints. Instead of requiring multi-view input, it predicts the parameters of a 3D Gaussian scene representation directly from one image using a single forward pass through a neural network. The core idea is speed: the 3D representation is produced in under a second on a standard GPU, and then the resulting scene can be rendered in real time to generate new views interactively. ... -
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1D Visual Tokenization and Generation
This repo contains the code for 1D tokenizer and generator
The 1D Visual Tokenization and Generation project from ByteDance introduces a novel “one-dimensional” tokenizer designed for images: instead of representing images with large grids of 2D tokens (as in many prior generative/image-modeling systems), it compresses images into as few as 32 discrete tokens (or more, optionally) — thereby achieving a very compact, efficient representation that drastically speeds up generation and reconstruction while retaining strong fidelity. This compact... -
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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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Ralph
Ralph is the CMDB / Asset Management system for data center
Ralph is built on top of Django and Python 3 and is easy to extend and customize without writing boilerplate code. REST API, Workflows code extensions allow for easy customization. We've chosen the best features of DCIM, Asset Mgmt and CMDB systems to create one, easy and well-integrated system. One interface is easier than 3. Keep track of assets purchases and their life cycle. Flexible flow system for assets life cycle. Data center and back office support. DC visualization built-in. Ralph... -
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AWS Lambda Python Runtime Interf Client
Seamlessly extend your preferred base images to be Lambda compatible
We have open-sourced a set of software packages, Runtime Interface Clients (RIC), that implement the Lambda Runtime API, allowing you to seamlessly extend your preferred base images to be Lambda compatible. The Lambda Runtime Interface Client is a lightweight interface that allows your runtime to receive requests from and send requests to the Lambda service. The Lambda Python Runtime Interface Client is vended through pip. You can include this package in your preferred base image to make... -
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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MedGemma
Collection of Gemma 3 variants that are trained for performance
MedGemma is a collection of specialized open-source AI models created by Google as part of its Health AI Developer Foundations initiative, built on the Gemma 3 family of transformer models and trained for medical text and image comprehension tasks that help accelerate the development of healthcare-focused AI applications. It includes multiple variants such as a 4 billion-parameter multimodal model that can process both medical images and text and a 27 billion-parameter text-only (and... -
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Milvus Bootcamp
Dealing with all unstructured data, such as reverse image search
Milvus Bootcamp is a collection of tutorials, examples, and best practices for using Milvus, an open-source vector database designed for AI-powered similarity search and retrieval applications. -
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AI Runner
Offline inference engine for art, real-time voice conversations
AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. -
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Depth Anything 3
Recovering the Visual Space from Any Views
Depth Anything 3 is a research-driven project that brings accurate and dense depth estimation to any input image or video, enabling foundational understanding of 3D structure from 2D visual content. Designed to work across diverse scenes, lighting conditions, and image types, it uses advanced neural networks trained on large, heterogeneous datasets, producing depth maps that reveal scene depth relationships and object surfaces with strong fidelity. The model can be applied to photography,... -
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Lightweight' GAN
Implementation of 'lightweight' GAN, proposed in ICLR 2021
Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before... -
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AutoGluon
AutoGluon: AutoML for Image, Text, and Tabular Data
AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning, model selection/ensembling, architecture search, and data processing. ... -
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HunyuanDiT
Diffusion Transformer with Fine-Grained Chinese Understanding
HunyuanDiT is a high-capability text-to-image diffusion transformer with bilingual (Chinese/English) understanding and multi-turn dialogue capability. It trains a diffusion model in latent space using a transformer backbone and integrates a Multimodal Large Language Model (MLLM) to refine captions and support conversational image generation. It supports adapters like ControlNet, IP-Adapter, LoRA, and can run under constrained VRAM via distillation versions. LoRA, ControlNet (pose, depth,... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and production-ready usage. ... -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. MiniMind-V combines techniques from modern vision-language modeling but focuses on efficiency and simplicity so that individuals or small teams can explore multimodal learning without massive GPU clusters. ... -
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DreamO
A Unified Framework for Image Customization
DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations —... -
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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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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. ... -
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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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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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GraalPy
A Python 3 implementation built on GraalVM
GraalPy is a high-performance implementation of the Python language for the JVM built on GraalVM. GraalPy is a Python 3.11 compliant runtime. It has first-class support for embedding in Java and can turn Python applications into fast, standalone binaries. GraalPy is ready for production running pure Python code and has experimental support for many popular native extension modules. -
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Nano PDF Editor
Edit PDF files with Nano Banana
Nano PDF Editor is a minimalist, portable PDF viewer and toolkit that focuses on simplicity, speed, and ease of integration for applications that need basic PDF rendering without heavy dependencies. It provides core functionality such as page navigation, zooming, text selection, and rendering directly to native graphics surfaces, making it suitable for lightweight PDF viewing scenarios on desktop or embedded platforms. Designed to be easily embedded into larger software projects, Nano-PDF...
