vqgan-clip

There are 30 repositories under vqgan-clip topic.

  • rbbrdckybk/ai-art-generator

    For automating the creation of large batches of AI-generated artwork locally.

    Language:Python6331326128

  • MohamadZeina/Disco_Diffusion_Local

    Getting the latest versions of Disco Diffusion to work locally, instead of colab. Including how I run this on Windows, despite some Linux only dependencies ;)

    Language:Jupyter Notebook314144236

  • somewheresy/S2ML-Generators

    Multiple notebooks which allow the use of various machine learning methods to generate or modify multimedia content

    Language:Jupyter Notebook17871750

  • rkhamilton/vqgan-clip-generator

    Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

    Language:Jupyter Notebook11161328

  • pytti-tools/pytti-notebook

    Start here

    Language:Jupyter Notebook11055826

  • tnwei/vqgan-clip-app

    Local image generation using VQGAN-CLIP or CLIP guided diffusion

    Language:Python10161229

  • bes-dev/pytorch_clip_guided_loss

    A simple library that implements CLIP guided loss in PyTorch.

    Language:Python77345
  • ai-atelier

    ryananan/ai-atelier

    Based on the Disco Diffusion, we have developed a Chinese & English version of the AI art creation software "AI Atelier". We offer both Text-To-Image models (Disco Diffusion and VQGAN+CLIP) and Text-To-Text (GPT-J-6B and GPT-NEOX-20B) as options. 在Disco Diffusion模型的基础上，我们开发了一款汉化版AI艺术创作软件“AI聊天画室”。我们同时提供了文本生成图像模型（Disco Diffusion与VQGAN+CLIP）及文本生成文本（GPT-J-6B及GPT-NEOX-20B）可供选择。

    Language:Python45219

  • happy-jihye/Streamlit-Tutorial

    Streamlit Tutorial (ex: stock price dashboard, cartoon-stylegan, vqgan-clip, stylemixing, styleclip, sefa)

    Language:Python402118

  • dughogan/VQGAN_Prompts

    Generates a random prompt for a VQGAN+CLIP

    Language:Python331015
  • VQGAN-CLIP-Video

    robobeebop/VQGAN-CLIP-Video

    Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.

    Language:Python22225

  • overshard/ai-art

    Art generation using VQGAN + CLIP using docker containers. A simplified, updated, and expanded upon version of Kevin Costa's work. This project tries to make generating art as easy as possible for anyone with a GPU by providing a simple web UI.

    Language:Python17302
  • artai

    SilentByte/artai

    ArtAI is an interactive art installation that collects people's ideas in real-time from social media and uses deep learning and AI art generation to curate these ideas into a dynamic display.

    Language:GDScript14202

  • yudhisteer/Generating-Design-Ideas-from-Keywords

    The purpose of the project is to understand a basic GAN from scratch. A WGAN was built to generate people's faces based in the Celeba Dataset. VQGAN + CLIP model was used to generate unique designs that would be used in fashion.

    Language:Jupyter Notebook7311

  • krishnakaushik25/VQGAN-CLIP

    Gradio Web app for running VQGAN-CLIP locally

    Language:Jupyter Notebook5106

  • bharathraj-v/art_project

    Mozart - A Generative Art Platform

    Language:Jupyter Notebook4102
  • gen_ability_icon

    CorvaeOboro/gen_ability_icon

    creates ability icon images utilizing procgen and neural networks

    Language:Python4101
  • gen_item

    CorvaeOboro/gen_item

    creates item images utilizing procgen and neural networks

    Language:Python4100

  • rxchit/AI-art-gen

    AI-powered art generator based on VQGAN+CLIP

    Language:Jupyter Notebook4100

  • Frikallo/YAKbot

    ⚠️ DEVELOPMENT REPO - NOT MAINTAINED OR EASILY DEPLOYABLE ⚠️

    Language:Python3114

  • PRAN20/VQ-GAN

    VQGAN and CLIP are actually two separate machine learning algorithms that can be used together to generate images based on a text prompt. VQGAN is a generative adversarial neural network that is good at generating images that look similar to others (but not from a prompt), and CLIP is another neural network that is able to determine how well a caption (or prompt) matches an image.

    Language:Jupyter Notebook3100

  • pandas9/txt2dream

    machines vivid dreams

    Language:Jupyter Notebook2100

  • Yazdi9/Video-generator

    Video generator using CLIP+VQGAN and sdvm

    Language:Jupyter Notebook2103

  • hululuzhu/cn-text-to-pic

    趣味中文图片生成

    Language:Jupyter Notebook1200

  • LibreCS/vqgarm

    VQGAN+CLIP implementation for aarch64 architecture testing and benchmarking with machine learning workloads

    Language:Python1060

  • mahalrs/newsgen

    Multi-Modal Image Generation for News Stories

    Language:Python02150

  • mohamedsobhi777/COMP4971C---Independent-Study-Project

    COMP4971C Independent Study Project Repository.

    0100

  • OmkarNarvekar001/ART_GENERATION_USING_SPEECH_EMOTIONS

    Translation of speech to image directly without text is an interesting and useful topic due to the potential application in computer-aided design, human to computer interaction, creation of an art form, etc. So we have focused on developing Deep learning and GANs based model which will take speech as an input from the user, analyze the emotions associated with it and accordingly generate the artwork which has been demanded by the user which will in turn provide a personalized experience. The approach used here is convolutional VQGAN to learn a codebook of context-rich visual parts, whose composition is subsequently modeled with autoregressive transformer architecture. Concept of CLIP-Contrastive Language Image-Pre-Training, also uses transformers which is a model trained to determine which caption from a set of captions best fits with a given image is used in our project. The input speech is classified into 8 different emotions using MLP classifier trained of RAVDESS emotional speech audio dataset and this acts as a base filter for the VQGAN model. Text converted from speech plays an important role in producing the final output image using CLIP model. VQGAN+CLIP model together utilizes both emotions and text to generate a more personalized artwork.

    Language:Jupyter Notebook0100

  • Xibanya/VQGAN-CLIP

    yet another VQGAN-CLIP variation

    Language:Python0100

  • benckx/baudelaire-on-vqgan

    Experiments with Baudelaire and a text-to-image GAN.

    Language:HTML10