Search Results for "scale image"
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Showing 64 open source projects for "scale image"
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Z-Image
Image generation model with single-stream diffusion transformer
Z-Image is an efficient, open-source image generation foundation model built to make high-quality image synthesis more accessible. With just 6 billion parameters — far fewer than many large-scale models — it uses a novel “single-stream diffusion Transformer” architecture to deliver photorealistic image generation, demonstrating that excellence does not always require extremely large model sizes. -
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Wan2.1
Wan2.1: Open and Advanced Large-Scale Video Generative Model
...The model supports text-to-video and image-to-video generation tasks with flexible resolution options suitable for various GPU hardware configurations. Wan2.1’s architecture balances generation quality and inference cost, paving the way for later improvements seen in Wan2.2 such as Mixture-of-Experts and enhanced aesthetics. It was trained on large-scale video and image datasets, providing generalization across diverse scenes and motion patterns. -
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pix2pixHD
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD is a PyTorch-based implementation of a conditional generative adversarial network designed for high-resolution image-to-image translation, capable of producing photorealistic outputs at resolutions up to 2048×1024. It is widely used to convert structured inputs such as semantic label maps into realistic images, making it particularly valuable in applications like autonomous driving simulation, face synthesis, and scene generation. The model improves upon earlier GAN approaches by introducing multi-scale generators and discriminators that enable stable training and fine detail generation at large resolutions. ... -
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CogView4
CogView4, CogView3-Plus and CogView3(ECCV 2024)
CogView4 is the latest generation in the CogView series of vision-language foundation models, developed as a bilingual (Chinese and English) open-source system for high-quality image understanding and generation. Built on top of the GLM framework, it supports multimodal tasks including text-to-image synthesis, image captioning, and visual reasoning. Compared to previous CogView versions, CogView4 introduces architectural upgrades, improved training pipelines, and larger-scale datasets, enabling stronger alignment between textual prompts and generated visual content. ... -
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Easy Diffusion
An easy 1-click way to create beautiful artwork on your PC using AI
...It provides a browser-based user interface that runs locally, allowing users to type text prompts and immediately generate images directly within their web browser, democratizing access to powerful text-to-image models for artists and hobbyists alike. The project abstracts away environment setup, dependencies, and model installation — tasks that can be daunting to beginners — and instead lets users focus on creative experimentation with prompt phrasing, model parameters, and image output settings. Because it’s designed to be easy to install and use, EasyDiffusion’s interface includes options for queuing multiple jobs, applying modifiers like upscaling or face correction, and adjusting generation parameters like guidance scale and resolution. -
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Wan2.2
Wan2.2: Open and Advanced Large-Scale Video Generative Model
...The model is trained on significantly larger datasets than its predecessor, greatly enhancing motion complexity, semantic understanding, and aesthetic diversity. Wan2.2 also open-sources a 5-billion parameter high-compression VAE-based hybrid text-image-to-video (TI2V) model that supports 720P video generation at 24fps on consumer-grade GPUs like the RTX 4090. It supports multiple video generation tasks including text-to-video. -
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Final2x
2^x Image Super-Resolution
The tool is available for Windows x64/arm64, MacOS x64/arm64, and Linux x64, allowing users to enjoy the benefits of super-resolution regardless of their operating system. It offers a wide range of models that can be used to achieve different levels of super-resolution, allowing users to choose the one that best suits their specific needs. Users have the flexibility to specify the desired output size for their images, ranging from small enhancements to large-scale super-resolution. The tool... -
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SwarmUI
Modular AI image and video generation web UI with extensible tools
SwarmUI is a modular web-based user interface designed for AI-driven image generation, with a strong focus on usability, performance, and extensibility. It serves as a unified environment for working with multiple AI models, including Stable Diffusion and newer image and video generation systems, allowing users to create and manage outputs through a browser interface. SwarmUI is built to accommodate both beginners and advanced users by offering a simple “Generate” interface alongside more... -
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Hunyuan3D 2.0
High-Resolution 3D Assets Generation with Large Scale Diffusion Models
The Hunyuan3D-2 model, developed by Tencent, is designed for generating high-resolution 3D assets using large-scale diffusion models. This model offers advanced capabilities for creating detailed 3D models, including texture enhancements, multi-view shape generation, and rapid inference for real-time applications. It is particularly useful for industries requiring high-quality 3D content, such as gaming, film, and virtual reality. Hunyuan3D-2 supports various enhancements and is available... -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter counts without linear inference cost explosion. ... -
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ViMax
Director, Screenwriter, Producer, and Video Generator All-in-One
ViMax is an open-source framework for performing large-scale multi-modal vision-language modeling and reasoning by combining powerful image encoders with advanced language models to solve complex visual tasks. It integrates components like visual encoders, cross-modal fusion techniques, and reasoning modules so that users can go beyond simple captioning or classification to perform tasks such as visual question answering, multi-image inference, and structured scene understanding. ... -
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ImageBind
ImageBind One Embedding Space to Bind Them All
ImageBind is a multimodal embedding framework that learns a shared representation space across six modalities—images, text, audio, depth, thermal, and IMU (inertial motion) data—without requiring explicit pairwise training for every modality combination. Instead of aligning each pair independently, ImageBind uses image data as the central binding modality, aligning all other modalities to it so they can interoperate zero-shot. This creates a unified embedding space where representations from any modality can be compared or retrieved against any other (e.g., matching sound to text or depth to image). The model is trained using large-scale contrastive learning, leveraging diverse datasets from natural images, videos, audio clips, and sensor data. ... -
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HunyuanVideo
HunyuanVideo: A Systematic Framework For Large Video Generation Model
HunyuanVideo is a cutting-edge framework designed for large-scale video generation, leveraging advanced AI techniques to synthesize videos from various inputs. It is implemented in PyTorch, providing pre-trained model weights and inference code for efficient deployment. The framework aims to push the boundaries of video generation quality, incorporating multiple innovative approaches to improve the realism and coherence of the generated content. Release of FP8 model weights to reduce GPU... -
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CogVideo
Text and image to video generation: CogVideoX and CogVideo
CogVideo is an open-source family of advanced video generation models that can create videos from text, images, or existing video inputs. Built on large-scale Transformer and diffusion architectures, it enables multimodal generation across text-to-video, image-to-video, and video continuation tasks. The latest CogVideoX models offer higher resolution outputs, longer video durations, and improved controllability through prompt engineering. The project includes tools for inference, fine-tuning, and optimization, making it suitable for both research and production use. ... -
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HunyuanWorld 1.0
Generating Immersive, Explorable, and Interactive 3D Worlds
...The architecture integrates panoramic proxy generation, semantic layering, and hierarchical 3D reconstruction to produce high-quality scene-scale 3D worlds from both text and images. HunyuanWorld-1.0 surpasses existing open-source methods in visual quality and geometric consistency, demonstrated by superior scores in BRISQUE, NIQE, Q-Align, and CLIP metrics. -
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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. -
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Depth Pro
Sharp Monocular Metric Depth in Less Than a Second
Depth Pro is a foundation model for zero-shot metric monocular depth estimation, producing sharp, high-frequency depth maps with absolute scale from a single image. Unlike many prior approaches, it does not require camera intrinsics or extra metadata, yet still outputs metric depth suitable for downstream 3D tasks. Apple highlights both accuracy and speed: the model can synthesize a ~2.25-megapixel depth map in around 0.3 seconds on a standard GPU, enabling near real-time applications. ... -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
...Its inference path is fully feed-forward with optional mixed-precision and memory-efficient modes, making it practical to scale to long image sequences while keeping latency predictable. -
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fastdup
An unsupervised and free tool for image and video dataset analysis
fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale. -
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Large Concept Model
Language modeling in a sentence representation space
Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically from large image–text or weakly supervised corpora. ... -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
HunyuanWorld-Voyager is a next-generation video diffusion framework developed by Tencent-Hunyuan for generating world-consistent 3D scene videos from a single input image. By leveraging user-defined camera paths, it enables immersive scene exploration and supports controllable video synthesis with high realism. The system jointly produces aligned RGB and depth video sequences, making it directly applicable to 3D reconstruction tasks. At its core, Voyager integrates a world-consistent video... -
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clip-retrieval
Easily compute clip embeddings and build a clip retrieval system
...It includes components for inference, indexing, filtering, and serving results through APIs, making it a complete pipeline for building production-ready retrieval systems. The framework also supports querying by image, text, or embedding, enabling flexible use cases such as reverse image search or multimodal content discovery. Additionally, it provides a simple frontend interface and backend services that can be deployed to expose search functionality to users. -
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marqo
Tensor search for humans
A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. It can seamlessly handle image-to-image, image-to-text and... -
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SAHI
A lightweight vision library for performing large object detection
A lightweight vision library for performing large-scale object detection & instance segmentation. Object detection and instance segmentation are by far the most important fields of applications in Computer Vision. However, detection of small objects and inference on large images are still major issues in practical usage. Here comes the SAHI to help developers overcome these real-world problems with many vision utilities. -
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Vearch
A distributed system for embedding-based vector retrieval
Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment. Through the module of the plugin, a complete default visual search system can be deployed just with one click. Otherwise, you can easily customize your own image, video, or text feature extraction algorithm plugin. ...
