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This is a PyTorch-based implementation of diffusion models for synthesizing photorealistic images and video. It provides a framework for text-to-image and text-to-video generation, as well as unconditional image synthesis. The system utilizes a cascading diffusion pipeline to produce high-resolution imagery by passing low-resolution outputs through a sequence of super-resolution models. It also includes capabilities for image inpainting, allowing the reconstruction of masked or missing regions of visual media guided by surrounding context and text prompts. The project includes tools for diff
Primitive is an algorithmic art generator and geometric image reconstruction tool that transforms raster images into stylized vector compositions. It functions as an iterative shape optimizer and raster-to-vector converter, approximating pixel-based photos by layering geometric primitives such as triangles, circles, and rectangles. The project utilizes a search algorithm to determine the optimal position, size, and color for each shape to minimize the visual difference from the source image. Users can apply shape constraint definitions to control the properties and orientations of the geometr
The main features of taoxugit/attngan are: Image Generation and Synthesis, Image Synthesis.
Open-source alternatives to taoxugit/attngan include: reedscot/nips2016 — Learning What and Where to Draw. hanzhanggit/stackgan — Pytorch implementation. lucidrains/imagen-pytorch — This is a PyTorch-based implementation of diffusion models for synthesizing photorealistic images and video. It… kwai-kolors/kolors — Kolors is a generative model implementation for synthesizing photorealistic images from natural language descriptions… hojonathanho/diffusion — This project is a diffusion model training framework and image synthesis pipeline. It provides the tools necessary to… fogleman/primitive — Primitive is an algorithmic art generator and geometric image reconstruction tool that transforms raster images into…
