5 مستودعات
The use of latent diffusion processes to increase the pixel density and clarity of an image.
Distinct from Latent Diffusion Models: Specifically applies the latent diffusion process to resolution enhancement rather than initial synthesis
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Sygil-webui is a web interface for Stable Diffusion latent diffusion models, providing a creative suite for text-to-image and text-to-video synthesis. It functions as an image generation tool and a latent diffusion image editor, allowing users to create visuals and video sequences from textual descriptions. The project includes a dedicated model training interface for creating custom textual inversion embeddings, which introduces specific new concepts or styles into the diffusion models. It also features specialized tools for generative image editing, including mask-based inpainting, image-to
Increases image resolution and removes visual artifacts by leveraging the latent diffusion denoising process.
This is a classifier-guided diffusion framework for high-fidelity image generation. It implements a cascaded diffusion pipeline that chains a base diffusion model with a dedicated upsampler to progressively increase image resolution in stages, and uses classifier-guided diffusion sampling to steer the reverse diffusion process toward higher-quality outputs. The framework provides tools for training diffusion models from scratch using distributed processes with gradient accumulation, as well as training classifier models that provide gradient-based guidance during sampling. It supports both un
Increases image resolution by passing low-resolution inputs through a dedicated diffusion upsampler.
هذا المشروع هو إطار عمل للتعلم العميق لتحسين دقة صور الذكاء الاصطناعي وتوليف الوجوه. يوفر نموذج انتشار (Diffusion model) لرفع دقة الصور ومولداً توليدياً لصور الوجوه قادراً على تحويل الصور منخفضة الدقة إلى مخرجات عالية الدقة باستخدام أوزان نماذج مدربة مسبقاً. يستخدم النظام تحسين الانتشار التكراري وأخذ العينات الموجه منخفض الدقة لاستعادة التفاصيل الدقيقة والحدة. يدعم كلاً من توليد الصور غير المشروط، حيث يتم إنشاء الصور من الصفر، وتحسين الدقة الموجه لإعادة بناء الوجوه بدقة عالية. يتضمن المستودع خط معالجة لتدريب نموذج الانتشار مع تدريب موزع متعدد الـ GPU وتهيئة الأوزان المدربة مسبقاً. يتم دعم هذه البيئة من خلال تتبع تجارب النموذج، وتسجيل المقاييس الخارجية، واستئناف النموذج القائم على نقاط التحقق (Checkpoints).
Increases image resolution and clarity using iterative latent diffusion processes.
Discoart is a diffusion model orchestration framework and distributed GPU generation engine designed to automate and scale image generation workflows across hardware clusters. It functions as a generative AI model API, providing HTTP and gRPC endpoints to trigger and retrieve images from diffusion models as a network service. The system distinguishes itself through a comprehensive task management layer that includes timeline-based prompt and parameter scheduling. It manages the generative art lifecycle by supporting state-based session serialization for recovery, YAML-based configuration mana
Increases image resolution and clarity by applying latent diffusion processes to sliding windows.
Hallo2 is an AI video generation tool and audio-driven portrait animation framework designed to transform static images into speaking videos. It functions as a portrait image animator that synchronizes a single photo with an audio track to produce high-resolution talking head videos. The system includes a distributed animation trainer for fine-tuning deep learning models using custom datasets and distributed computing resources. It employs hierarchical video generation and temporal consistency modeling to produce long-form character animations that remain stable over extended durations. The
Applies latent diffusion processes to increase the pixel density and visual clarity of the generated animations.