Sergio's repositories
bootstrap-table
An extended Bootstrap table with radio, checkbox, sort, pagination, and other added features. (supports twitter bootstrap v2 and v3)
clipseg
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
clip-interrogator-ext
Stable Diffusion WebUI extension for CLIP Interrogator
DeforumStableDiffusionLocal
Local version of Deforum Stable Diffusion, supports txt settings file input and animation features!
diffusion-ui
Frontend for deeplearning Image generation
diffusion-ui-backend
Backend for the diffusion-ui frontend
docker-diffusers-api
Diffusers / Stable Diffusion in docker with a REST API, supporting various models, pipelines & schedulers.
EveryDream
Advanced fine tuning tools for vision models
EveryDream-trainer
General fine tuning for Stable Diffusion
glid-3
combination of OpenAI GLIDE and Latent Diffusion
ritm_interactive_segmentation
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
ruby-applicants-test-master
ADTsys Ruby Application
stable-diffusion-tensorflow
Stable Diffusion in TensorFlow / Keras
stable-diffusion-webui
Stable Diffusion web UI
stable-diffusion-webui-1
Stable Diffusion web UI
stable-diffusion-webui-docker
Easy Docker setup for Stable Diffusion with user-friendly UI
svoice
We provide a PyTorch implementation of the paper Voice Separation with an Unknown Number of Multiple Speakers In which, we present a new method for separating a mixed audio sequence, in which multiple voices speak simultaneously. The new method employs gated neural networks that are trained to separate the voices at multiple processing steps, while maintaining the speaker in each output channel fixed. A different model is trained for every number of possible speakers, and the model with the largest number of speakers is employed to select the actual number of speakers in a given sample. Our method greatly outperforms the current state of the art, which, as we show, is not competitive for more than two speakers.
testedesenvolvedorrubyjava
Teste Desenvolvedor Ruby/Java
Text-To-Video-Finetuning
Finetune ModelScope's Text To Video model using Diffusers 🧨