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image-encoding

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JPEG XL in JavaScript & WebAssembly with WebGPU acceleration for high effort. Gzip modules: ~35 KB exact capture, ~50 KB complete capture & ~190 KB upload. Rapier’s full image encoder is ~300 KB with lossless, lossy, HDR, exact alpha, and parallel workers. Separate modules for JPEG transcoding, decoding, serving & animation. Zero dependencies. MIT.

  • Updated Nov 2, 2026
  • JavaScript

A Light weight deep learning model with with a web application to answer image-based questions with a non-generative approach for the VizWiz grand challenge 2023 by carefully curating the answer vocabulary and adding linear layer on top of Open AI's CLIP model as image and text encoder

  • Updated Jun 27, 2023
  • Jupyter Notebook

This repository is the implementation of the paper: ViT2 - Pre-training Vision Transformers for Visual Times Series Forecasting. ViT2 is a framework designed to address generalization & transfer learning limitations of Time-Series-based forecasting models by encoding the time-series to images using GAF and a modified ViT architecture.

  • Updated Apr 8, 2024
  • Jupyter Notebook

Remige is an advanced image compression framework, built as a fork of libSquoosh. By integrating Squoosh's powerful image codecs directly into JavaScript applications, Remige offers unparalleled compression performance and file size reduction. Designed for compatibility with the latest Node.js versions, Remige enhances image processing with modern

  • Updated Nov 10, 2024
  • TypeScript
fsi-server-docker-v22

FSI Server Installation Repository - Standalone web server for high-speed automatic image resizing, manipulation and conversion from various formats to JPEG, WebP, PNG or GIF in real time.

  • Updated Jul 8, 2026
  • Shell

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