Projects

I write about almost all of my projects, which you can find either among my blog posts or in my WandB reports. You can also follow me on Github to stay up-to-date with the numerous open-source projects I’m continuously working on. That said, I want to mention some specific projects I’ve undertaken in the past or ones that I’m still working on.

Work-in-Progress Projects

Hemm: Holistic Evaluation of Multi-modal Generative Models [Repository | Website]

Hemm is a library for performing comprehensive benchmark of text-to-image diffusion models on image quality and prompt comprehension integrated with Weights & Biases and Weave.

Weights & Biases Addons [Repository | Website]

Weights & Biases Addons is a repository that provides of integrations and utilities that will supercharge your Weights & Biases workflows. Its a repositpry built and maintained by WandB users for WandB users. The library hosts experimental utilities and integrations built using Weights & Biases. I am currently actively working on this project.

Restorers

Restorers is a library provide out-of-the-box TensorFlow implementations of SoTA image and video restoration models for tasks such as low-light enhancement, denoising, deblurring, super-resolution, etc. You can read more about it in this WandB report.

Deep Learning examples published on keras.io

• Multiclass semantic segmentation using DeepLabV3+
• Low-light image enhancement using MIRNet
• Zero-DCE for low-light image enhancement
• Large-scale multi-label text classification in colaboration with Sayak Paul
• Point cloud segmentation with PointNet in colaboration with Sayak Paul
• GauGAN for conditional image generation in colaboration with Sayak Paul

Other Interesting Projects

• Radium: A small and lightweight Ray Tracing Engine written in C++ that runs on the CPU using shared-memory multiprocessing.
• Colorization using Optimization: Python and C++ implementations of a user-guided image/video colorization technique as proposed by the paper Colorization Using Optimization. The algorithm is based on a simple premise; neighboring pixels in space-time that have similar intensities should have similar colors. This premise is formalized using a quadratic cost function that obtains an optimization problem that can be solved efficiently using standard techniques. While using this alogorithm, an artist only needs to annotate the image with a few color scribbles or visual clues, and the indicated colors are automatically propagated in both space and time to produce a fully colorized image or sequence. The annotation can be done using any drawing tool such as JSPaint or Gimp.
• Deep Deterministic Policy Gradients: Pytorch implementation of the Deep Deterministic Policy Gradients Algorithm for Continuous Control as described by the paper Continuous control with deep reinforcement learning.
• Twin Delayed DDGP: Pytorch Implementation of Twin Delayed Deep Deterministic Policy Gradients Algorithm for Continuous Control as described by the paper Addressing Function Approximation Error in Actor-Critic Methods.
• Arxiv2Kindle: Arxiv2Kindle is a simple script written in python that converts LaTeX source downloaded from Arxiv and recompiles it to better fit a reading device (such as a Kindle).
• Manga Scraper: A a python package that downloads Manga into chapterwise PDF files or a single PDF file from various sources. It basically adds a post-processing layer on top of the basic functionality by mangadl-bash created by Akianonymus in order to convert the downloaded manga into chapter-wise PDF files or a single giant PDF file.