PyTorch implementation of our paper Road Sign Classification with Denoising Pipeline Approach
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Updated
Nov 5, 2025 - Python
PyTorch implementation of our paper Road Sign Classification with Denoising Pipeline Approach
Deep Learning-based Image Restoration — Implements SwinIR for super-resolution and LaMa for large-mask inpainting, with custom dataset preparation, mask generation, and evaluation metrics (PSNR, SSIM, FID, IS).
All image enhancement and restoration tools
ImageEditor is a PyQt5-based GUI application for advanced AI-powered image processing. It supports operations such as denoising, super-resolution, background removal, canvas resizing, and format conversion. It integrates powerful models such as SCUNet, SwinIR, and U²-Net.
[ECCV] Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration. Advances in Image Manipulation (AIM) workshop ECCV 2022. Try it out! over 3.3M runs https://replicate.com/mv-lab/swin2sr
Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
WindSR Dataset contains more than 22,000 pairs of HR/LR wind speed images, which are processed using the NASA's GEOS-5 Nature Run dataset. This dataset is useful for studying super-resolution for data collected using satellites rather natural RGB images.
Video Frame Interpolation & Super Resolution using NVIDIA's TensorRT & Tencent's NCNN inference, beautifully crafted and packaged into a single app
🌊 A Human-in-the-Loop workflow for creating HD images from text
A repository of models trained by me!
Analysis resources for the Inter IIT Tech Meet 11.0 problem statement by ISRO: The Chandrayaan Moon Mapping Challenge
A High Quality (HD / 2K / 4K) Image Generation Using Stable Diffusion and Real-ESR / SwinIR /GFPGAN
A multistage text to image framework. Built from a inference-reduced set of min-dalle, glid-3-xl, and SwinIR.
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