6 रिपॉजिटरी
AI-based algorithms that enlarge anime still images while preserving sharpness and reducing artifacts.
Distinct from Anime Upscaling Shaders: Distinct from Anime Upscaling Shaders: focuses on static image upscaling rather than video frame processing.
Explore 6 awesome GitHub repositories matching graphics & multimedia · Static Image Upscalers. Refine with filters or upvote what's useful.
waifu2x-caffe is a deep learning image upscaler and denoiser that uses the Caffe framework to increase image resolution and remove noise from illustrations and photographs. It functions as a neural network image processor that reduces compression artifacts and pixelation while maintaining visual clarity. The project provides specialized neural network weights optimized separately for 2D illustrations and real-world photographs. It includes distinct processing for alpha channels to preserve transparency and employs test-time augmentation to improve output precision. The tool supports both a c
Implements AI-based algorithms that enlarge static images while preserving sharpness and reducing artifacts.
Final2x is an AI image super-resolution tool and neural network inference engine designed to increase image resolution and reconstruct missing details while reducing noise. It functions as a cross-platform image upscaler that executes consistent super-resolution logic across different operating systems. The project serves as a custom model inference engine and upscaling interface, allowing for the import and application of user-defined super-resolution weights and architectures to tailor the visual output of enlarged images. The system utilizes hardware-accelerated processing to offload comp
Provides a system for importing and applying user-defined super-resolution models to tailor the visual output of enlarged images.
A free and open-source inpainting & image-upscaling tool powered by webgpu and wasm on the browser。| 基于 Webgpu 技术和 wasm 技术的免费开源 inpainting & image-upscaling 工具, 纯浏览器端实现。
Uses WebGPU and WASM to increase pixel dimensions while preserving detail, processed locally on the client.
ailab is a deep learning tool designed to upscale anime-style images, increasing their resolution while preserving fine details. It is built around a cascade U-Net architecture, a multi-stage neural network model that refines image quality through successive stages, and uses PyTorch for inference. The tool specializes in enhancing anime and cartoon-style artwork, applying super-resolution techniques to boost pixel dimensions without sacrificing visual fidelity. It processes images through a pipeline that includes tensor preprocessing, model inference, and post-processing pixel reconstruction,
Uses a deep-learning cascade U-Net model to increase the resolution of anime-style images while preserving fine details.
picacg-qt रिमोट सेवाओं से डिजिटल मंगा और कॉमिक्स ब्राउज़ करने और पढ़ने के लिए एक क्रॉस-प्लेटफ़ॉर्म डेस्कटॉप क्लाइंट है। यह रिमोट लाइब्रेरी को नेविगेट करने, विशिष्ट शीर्षकों को खोजने और Windows, Linux व MacOS पर मीडिया कंटेंट देखने के लिए एक समर्पित इंटरफेस प्रदान करता है। एप्लिकेशन में कॉमिक इमेज के रिज़ॉल्यूशन और विजुअल क्वालिटी को अपस्केल करने के लिए एक एकीकृत आर्टिफिशियल इंटेलिजेंस टूल शामिल है। यह एक ऑफलाइन डाउनलोडर के रूप में भी कार्य करता है, जो उपयोगकर्ताओं को रिमोट प्रोवाइडर्स से कॉमिक सेट और इमेज को लोकल स्टोरेज में आर्काइव करने की अनुमति देता है। सिस्टम ऑफलाइन एक्सेस का समर्थन करने के लिए एसिंक्रोनस मीडिया डाउनलोडिंग और लोकल इमेज कैशिंग को हैंडल करता है।
Integrates AI-based algorithms to enlarge manga still images while preserving sharpness and reducing artifacts.
This PyTorch-based image super-resolution tool provides a deep learning pipeline for upscaling low-resolution images. It utilizes generative adversarial networks to increase pixel density and reconstruct high-resolution image details. The system includes a GAN-based image upscaler and a training pipeline that optimizes neural network weights using paired datasets and custom loss functions. To manage hardware resources, a patch-based image processor splits high-resolution files into smaller segments to prevent memory allocation errors and system crashes. Additional capabilities include the ap
Implements a system using generative adversarial networks to reconstruct high-resolution image details.