Generate images from texts. In Russian. In PaddlePaddle

Overview

ruDALL-E PaddlePaddle

ruDALL-E in PaddlePaddle.

Install:

pip install rudalle_paddle==0.0.1rc1

Run with free v100 on AI Studio.

Original Pytorch version Readme:

ruDALL-E

Generate images from texts

Apache license Coverage Status pipeline pre-commit.ci status

🤗 HF Models:

ruDALL-E Malevich (XL)

Minimal Example:

Open In Colab Kaggle

generation by ruDALLE:

from rudalle_paddle.pipelines import generate_images, show, super_resolution, cherry_pick_by_clip
from rudalle_paddle import get_rudalle_model, get_tokenizer, get_vae, get_realesrgan, get_ruclip
from rudalle_paddle.utils import seed_everything

# prepare models
device = 'cuda'
dalle = get_rudalle_model('Malevich', pretrained=True, fp16=True, device=device)
realesrgan = get_realesrgan('x4', device=device)
tokenizer = get_tokenizer()
vae = get_vae().to(device)
ruclip, ruclip_processor = get_ruclip('ruclip-vit-base-patch32-v5')
ruclip = ruclip.to(device)

text = 'изображение радуги на фоне ночного города'

seed_everything(42)
pil_images = []
scores = []
for top_k, top_p, images_num in [
    (2048, 0.995, 3),
    (1536, 0.99, 3),
    (1024, 0.99, 3),
    (1024, 0.98, 3),
    (512, 0.97, 3),
    (384, 0.96, 3),
    (256, 0.95, 3),
    (128, 0.95, 3), 
]:
    _pil_images, _scores = generate_images(text, tokenizer, dalle, vae, top_k=top_k, images_num=images_num, top_p=top_p)
    pil_images += _pil_images
    scores += _scores

show(pil_images, 6)

auto cherry-pick by ruCLIP:

top_images, clip_scores = cherry_pick_by_clip(pil_images, text, ruclip, ruclip_processor, device=device, count=6)
show(top_images, 3)

super resolution:

sr_images = super_resolution(top_images, realesrgan)
show(sr_images, 3)

text, seed = 'красивая тян из аниме', 6955

Image Prompt

see jupyters/ruDALLE-image-prompts-A100.ipynb

text, seed = 'Храм Василия Блаженного', 42
skyes = [red_sky, sunny_sky, cloudy_sky, night_sky]

🚀 Contributors 🚀

  • @neverix thanks a lot for contributing for speed up of inference
  • @oriBetelgeuse thanks a lot for easy API of generation using image prompt
You might also like...
Large-scale open domain KNOwledge grounded conVERsation system based on PaddlePaddle

Knover Knover is a toolkit for knowledge grounded dialogue generation based on PaddlePaddle. Knover allows researchers and developers to carry out eff

🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Classical OCR DCNN reproduction based on PaddlePaddle framework.

Paddle-SVHN Classical OCR DCNN reproduction based on PaddlePaddle framework. This project reproduces Multi-digit Number Recognition from Street View I

A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.
A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation.

TiSASRec.paddle A PaddlePaddle implementation of Time Interval Aware Self-Attentive Sequential Recommendation. Introduction 论文:Time Interval Aware Sel

buildseg is a building extraction plugin of QGIS based on PaddlePaddle.
buildseg is a building extraction plugin of QGIS based on PaddlePaddle.

buildseg buildseg is a building extraction plugin of QGIS based on PaddlePaddle. TODO Extract building on 512x512 remote sensing images. Extract build

YOLOv5🚀 reproduction by Guo Quanhao using PaddlePaddle
YOLOv5🚀 reproduction by Guo Quanhao using PaddlePaddle

YOLOv5-Paddle YOLOv5 🚀 reproduction by Guo Quanhao using PaddlePaddle 支持AutoBatch 支持AutoAnchor 支持GPU Memory 快速开始 使用AIStudio高性能环境快速构建YOLOv5训练(PaddlePa

A PaddlePaddle implementation of STGCN with a few modifications in the model architecture in order to forecast traffic jam.
A PaddlePaddle implementation of STGCN with a few modifications in the model architecture in order to forecast traffic jam.

About This repository contains the code of a PaddlePaddle implementation of STGCN based on the paper Spatio-Temporal Graph Convolutional Networks: A D

buildseg is a building extraction plugin of QGIS based on PaddlePaddle.
buildseg is a building extraction plugin of QGIS based on PaddlePaddle.

buildseg buildseg is a Building Extraction plugin for QGIS based on PaddlePaddle. How to use Download and install QGIS and clone the repo : git clone

Comments
  • Other playable models-Text2Image

    Other playable models-Text2Image

    playable models

    1. dalle-mini & craiyon https://github.com/borisdayma/dalle-mini

    2. CogView2 https://github.com/THUDM/CogView2

    待添加


    No pretrained models

    1. imagen https://github.com/lucidrains/imagen-pytorch

    2. 文心 ERNIE-ViLG https://wenxin.baidu.com/wenxin/modelbasedetail/ernie_vilg/

    待添加

    opened by Wulx2050 3
Owner
AgentMaker
Focus on deep learning tools
AgentMaker
UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac protocols on unmanned aerial vehicle networks.

UAV-Networks Simulator - Autonomous Networking - A.A. 20/21 UAV-Networks-Routing is a Python simulator for experimenting routing algorithms and mac pr

0 Nov 13, 2021
Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”

Graph-to-Graph Transformers Self-attention models, such as Transformer, have been hugely successful in a wide range of natural language processing (NL

Idiap Research Institute 40 Aug 14, 2022
FLSim a flexible, standalone library written in PyTorch that simulates FL settings with a minimal, easy-to-use API

Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such a

Meta Research 162 Jan 02, 2023
An official implementation of the paper Exploring Sequence Feature Alignment for Domain Adaptive Detection Transformers

Sequence Feature Alignment (SFA) By Wen Wang, Yang Cao, Jing Zhang, Fengxiang He, Zheng-jun Zha, Yonggang Wen, and Dacheng Tao This repository is an o

WangWen 79 Dec 24, 2022
Cross-media Structured Common Space for Multimedia Event Extraction (ACL2020)

Cross-media Structured Common Space for Multimedia Event Extraction Table of Contents Overview Requirements Data Quickstart Citation Overview The code

Manling Li 49 Nov 21, 2022
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks

DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura

AutoML Research 24 Nov 29, 2022
An Unsupervised Detection Framework for Chinese Jargons in the Darknet

An Unsupervised Detection Framework for Chinese Jargons in the Darknet This repo is the Python 3 implementation of 《An Unsupervised Detection Framewor

7 Nov 08, 2022
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Zhao Jian 3.1k Jan 02, 2023
Negative Interactions for Improved Collaborative Filtering:

Negative Interactions for Improved Collaborative Filtering: Don’t go Deeper, go Higher This notebook provides an implementation in Python 3 of the alg

Harald Steck 21 Mar 05, 2022
Code and Data for NeurIPS2021 Paper "A Dataset for Answering Time-Sensitive Questions"

Time-Sensitive-QA The repo contains the dataset and code for NeurIPS2021 (dataset track) paper Time-Sensitive Question Answering dataset. The dataset

wenhu chen 35 Nov 14, 2022
Sequence Modeling with Structured State Spaces

Structured State Spaces for Sequence Modeling This repository provides implementations and experiments for the following papers. S4 Efficiently Modeli

HazyResearch 896 Jan 01, 2023
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

Giacomo Arcieri 1 Mar 21, 2022
CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY

M-BERT-Study CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY Motivation Multilingual BERT (M-BERT) has shown surprising cross lingual a

CogComp 1 Feb 28, 2022
MIMO-UNet - Official Pytorch Implementation

MIMO-UNet - Official Pytorch Implementation This repository provides the official PyTorch implementation of the following paper: Rethinking Coarse-to-

Sungjin Cho 248 Jan 02, 2023
Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks

Spontaneous Facial Micro Expression Recognition using 3D Spatio-Temporal Convolutional Neural Networks Abstract Facial expression recognition in video

Bogireddy Sai Prasanna Teja Reddy 103 Dec 29, 2022
More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval

More Photos are All You Need: Semi-Supervised Learning for Fine-Grained Sketch Based Image Retrieval, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdh

Ayan Kumar Bhunia 22 Aug 27, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
Code release of paper "Deep Multi-View Stereo gone wild"

Deep MVS gone wild Pytorch implementation of "Deep MVS gone wild" (Paper | website) This repository provides the code to reproduce the experiments of

François Darmon 53 Dec 24, 2022
Pseudo lidar - (CVPR 2019) Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving This paper has been accpeted by Conference o

Yan Wang 881 Dec 27, 2022
Repository for the paper "From global to local MDI variable importances for random forests and when they are Shapley values"

From global to local MDI variable importances for random forests and when they are Shapley values Antonio Sutera ( Antonio Sutera 3 Feb 23, 2022