GANs demonstrating the efficiency of factorising transposed convolution layers – performance is comparable to conventional model architectures, but with ~15-40% less parameters.
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Updated
Aug 1, 2022 - Python
GANs demonstrating the efficiency of factorising transposed convolution layers – performance is comparable to conventional model architectures, but with ~15-40% less parameters.
Generating images using the most famous model, DALL.E, by integrating OpenAI API.
This repository contains a Telegram chatbot that leverages OpenAI's GPT-3 and Celery for task queue management. The chatbot can respond to messages, store the last 10 conversations for each user, and efficiently process messages using Celery. A great starting point for building your own AI-powered Telegram chatbot.
PyTorch Implementation of Denoising Diffusion Probabilistic Models (DDPMs)
An app that generates ai images based on user text. Built to consume OpenAI DALL.E 2 API
Application to generate background image for meeting (ex. Zoom, Meet, Teams).
WordPress plugin for creating and managing additional image sizes
AI generates illustrations for poetry, lyrics, songs, music, etc。用 Bing Image Creator、Leonardo.AI、Midjourney等 AI 工具为优美的诗、词、歌、赋、曲生成的配图集
Easy to use Discord bot for generating images using OpenAIs DALL·E 2 image generation API.
AIMAGE app
Generates the minecraft background youtube videos that we all know and regret wasting time over.
Image Generator using a diffusion model with components from NodeJS, Javascript, CSS and HTML. Using the MERN stack to make an interactive website for generating images based on user prompts.
This project, developed by Anshuman Pattnaik, explores image processing techniques using Python libraries such as pandas, numpy, matplotlib, and cv2 (OpenCV). The primary objective of the project was to delve into image processing with a focus on creating a unique dataset and algorithm for image generation.
Descriptor and Generator components of CoopNet
Neural network from scratch; image input optimize == image generation
A tool to generate image by provided palette colors.
In this project, I defined and trained a DCGAN on a dataset of faces aiming to get a generator network to generate new images of faces that look as realistic as possible!
A simple variational autoencoder
This repository hosts the different DL models I've written from scratch with the help of YouTube tutorials from Valerio, Sundog Education, Tensorflow guides, and many other online resources. I've enjoyed creating these models for image generation from scratch and I hope these are helpful learning tools for everyone. Please feel free to take the …
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