Experiments with Baudelaire and a text-to-image GAN.
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Updated
Oct 12, 2021 - HTML
Experiments with Baudelaire and a text-to-image GAN.
Implementing MaskGIT for image inpainting with PyTorch
Doing devious stuff with images
yet another VQGAN-CLIP variation
Multi-Modal Image Generation for News Stories
Branch of the original Project "dome272/VQGAN-pytorch" adding an inference file for the VQGAN (Not for the VQGAN Transformers)
Pipeline to create Paper2Fig dataset, a dataset for text-to-image generation from research papers and figures (e.g., diagrams of architectures or methods in fields like Machine Learning or Computer Vision)
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 c…
VQGAN from LDM without hell of dependencies
Vector-Quantized Generative Adversarial Networks
Text-to-Image Synthesis using Multimodal (VQGAN + CLIP) Architectures
Video generation of anime content based on the first and last frame
An unofficial PyTorch implementation of VQGAN
Colabs for text prompt steered image generators
Implementation of Taming Transformers for High-Resolution Image Synthesis (https://arxiv.org/abs/2012.09841) in PyTorch
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.
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.
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