• Stars
    star
    598
  • Rank 74,328 (Top 2 %)
  • Language
    Python
  • Created almost 8 years ago
  • Updated over 3 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Generative Adversarial Text to Image Synthesis / Please Star -->

Text To Image Synthesis

This is a tensorflow implementation of synthesizing images. The images are synthesized using the GAN-CLS Algorithm from the paper Generative Adversarial Text-to-Image Synthesis. This implementation is built on top of the excellent DCGAN in Tensorflow.

Plese star https://github.com/tensorlayer/tensorlayer

Model architecture

Image Source : Generative Adversarial Text-to-Image Synthesis Paper

Requirements

Datasets

  • The model is currently trained on the flowers dataset. Download the images from here and save them in 102flowers/102flowers/*.jpg. Also download the captions from this link. Extract the archive, copy the text_c10 folder and paste it in 102flowers/text_c10/class_*.

N.B You can downloads all data files needed manually or simply run the downloads.py and put the correct files to the right directories.

python downloads.py

Codes

  • downloads.py download Oxford-102 flower dataset and caption files(run this first).
  • data_loader.py load data for further processing.
  • train_txt2im.py train a text to image model.
  • utils.py helper functions.
  • model.py models.

References

Results

  • the flower shown has yellow anther red pistil and bright red petals.
  • this flower has petals that are yellow, white and purple and has dark lines
  • the petals on this flower are white with a yellow center
  • this flower has a lot of small round pink petals.
  • this flower is orange in color, and has petals that are ruffled and rounded.
  • the flower has yellow petals and the center of it is brown
  • this flower has petals that are blue and white.
  • these white flowers have petals that start off white in color and end in a white towards the tips.

License

Apache 2.0

More Repositories

1

deep-learning-book

《Deep Learning》《深度学习》 by Ian Goodfellow, Yoshua Bengio and Aaron Courville
557
star
2

u-net-brain-tumor

U-Net Brain Tumor Segmentation
Python
496
star
3

research-and-coding

研究资源列表 A curated list of research resources
164
star
4

Image-Captioning

TensorFlow (TensorLayer) Implementation of Image Captioning
Python
115
star
5

Unsup-Im2Im

Unsupervised Image to Image Translation with Generative Adversarial Networks
Python
73
star
6

Imitation-Learning-Dagger-Torcs

A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
Python
71
star
7

Spatial-Transformer-Nets

Spatial Transformer Nets in TensorFlow/ TensorLayer
Python
35
star
8

im2txt2im

I2T2I: Text-to-Image Synthesis with textual data augmentation
Python
30
star
9

U-Net

U-Net: Convolutional Networks for Image Segmentation by TensorFlow
Python
19
star
10

deep-learning-note

Slides and codes
Python
19
star
11

ChatServerTCP

保密型聊天软件服务器 /Private Chat Server
Python
17
star
12

EmotivEPOC

Emotiv EPOC 脑电仪代码 / Code for Emotiv EPOC
C++
13
star
13

pybluez

How to use pybluez
Python
12
star
14

zsdonghao.github.io

Click this --> https://zsdonghao.github.io
HTML
8
star
15

stackednet

轻量、易于修改、可组层训练的神经网络 / Lightweight Greedy Layer-Wise Training Neural Network
Python
7
star
16

practice-lesson

6
star
17

ImageMosaic

手动图像拼接工具 / Manual Image Mosaic Tool
MATLAB
5
star
18

lego-zoo

LEGO MOC DIY COLLECTION
3
star
19

DL-course

Python
2
star
20

DropNeuron

DropNeuron (DropFilter) : Simplify Convolutional Neural Network
Python
2
star
21

pix2pix

Python
2
star
22

hdmlp

几乎集成所有功能的多层神经网络 / A powerful and easy-to-use Multi-Layer Perceptron (MLP)
2
star
23

pyedfreader

Read EDF and EDF+ File by using Python
Python
1
star
24

oldwatch

古典电子手表表:进入21世纪10年代,电子工业发展迅猛;2010年后,智能手表更是迎来飞速的发展,这唤起了作者对八九十年代传统电子工程的怀恋,于是作者决定使用最老的单片机之一 “MCU-51” 来手工制作一款万年历电子表。
C
1
star
25

python_with_other_language

How to use Python and Other languages together
C
1
star