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Pulse is a face image super-resolution tool and self-supervised image enhancer. It functions as a generative model image upsampler and latent space optimization tool designed to increase photo resolution and recover image details. The system differentiates itself by using latent space exploration and spherical constraints to find high-fidelity matches within a generative model. It employs geodesic distance measurement and spherical latent space optimization to regularize representations and maintain parameter radii during the recovery process. The project covers facial image restoration thro
ESRGAN is a deep learning image restoration framework designed for image super-resolution. It uses a generative adversarial network system to upscale low-resolution images into high-quality versions with sharp visual details and recovered fine textures. The framework implements a perceptual super-resolution model that optimizes the trade-off between perceived visual quality and pixel-level signal-to-noise ratio. It includes weight-interpolation blending to allow for the adjustment of visual sharpness and signal-to-noise ratios by mixing weights from different trained models. The system cover
GFPGAN is a generative face restoration model and Python-based image processing tool designed to restore low-resolution facial images. It utilizes generative adversarial networks to recover fine details and increase the clarity of degraded portraits. The system employs a generative facial prior to map degraded images to a high-quality manifold, enabling blind-face restoration without requiring knowledge of the specific degradation process. It utilizes a multi-stage workflow that includes face detection, alignment, and region-specific masking to separate facial areas from the background. Beyo
MochiDiffusion is a local client for Stable Diffusion that functions as an AI image generation studio. It provides a workspace for performing text-to-image, image-to-image, and inpainting tasks, enabling the production of high-resolution images offline using local hardware and neural engine acceleration. The project includes a local model manager for importing, organizing, and converting machine learning models into compatible formats for offline execution. It features a ControlNet integration tool to guide structural composition and spatial layout, alongside a dedicated image upscaler that u
Pulse is a generative model image upscaler and latent space image processor. It functions as a self-supervised photo upsampling tool that increases image resolution by exploring the latent space of pre-trained generative models to synthesize high-quality details.
The main features of adamian98/pulse are: Image Super Resolution Models, Generative Upscalers, Image, Latent Reconstruction, Image Upsampling, Computer Vision Models, Developer Tools.
Open-source alternatives to adamian98/pulse include: alex-damian/pulse — Pulse is a face image super-resolution tool and self-supervised image enhancer. It functions as a generative model… xinntao/esrgan — ESRGAN is a deep learning image restoration framework designed for image super-resolution. It uses a generative… tencentarc/gfpgan — GFPGAN is a generative face restoration model and Python-based image processing tool designed to restore… mochidiffusion/mochidiffusion — MochiDiffusion is a local client for Stable Diffusion that functions as an AI image generation studio. It provides a… eriklindernoren/keras-gan — Keras-GAN is a collection of generative adversarial network implementations built with Keras for synthetic data… dmitryulyanov/deep-image-prior — This project is an unsupervised image restoration tool that uses a convolutional neural network as a structural prior…