Generative Handwriting using LSTM Mixture Density Network with TensorFlow

Related tags

Deep Learningwrite-rnn-tensorflow
Overview

Generative Handwriting Demo using TensorFlow

example

example

An attempt to implement the random handwriting generation portion of Alex Graves' paper.

See my blog post at blog.otoro.net for more information.

How to use

I tested the implementation on TensorFlow r0.11 and Pyton 3. I also used the following libraries to help:

svgwrite
IPython.display.SVG
IPython.display.display
xml.etree.ElementTree
argparse
pickle

Training

You will need permission from these wonderful people people to get the IAM On-Line Handwriting data. Unzip lineStrokes-all.tar.gz into the data subdirectory, so that you end up with data/lineStrokes/a01, data/lineStrokes/a02, etc. Afterwards, running python train.py will start the training process.

A number of flags can be set for training if you wish to experiment with the parameters. The default values are in train.py

--rnn_size RNN_SIZE             size of RNN hidden state
--num_layers NUM_LAYERS         number of layers in the RNN
--model MODEL                   rnn, gru, or lstm
--batch_size BATCH_SIZE         minibatch size
--seq_length SEQ_LENGTH         RNN sequence length
--num_epochs NUM_EPOCHS         number of epochs
--save_every SAVE_EVERY         save frequency
--grad_clip GRAD_CLIP           clip gradients at this value
--learning_rate LEARNING_RATE   learning rate
--decay_rate DECAY_RATE         decay rate for rmsprop
--num_mixture NUM_MIXTURE       number of gaussian mixtures
--data_scale DATA_SCALE         factor to scale raw data down by
--keep_prob KEEP_PROB           dropout keep probability

Generating a Handwriting Sample

I've included a pretrained model in /save so it should work out of the box. Running python sample.py --filename example_name --sample_length 1000 will generate 4 .svg files for each example, with 1000 points.

IPython interactive session.

If you wish to experiment with this code interactively, just run %run -i sample.py in an IPython console, and then the following code is an example on how to generate samples and show them inside IPython.

[strokes, params] = model.sample(sess, 800)
draw_strokes(strokes, factor=8, svg_filename = 'sample.normal.svg')
draw_strokes_random_color(strokes, factor=8, svg_filename = 'sample.color.svg')
draw_strokes_random_color(strokes, factor=8, per_stroke_mode = False, svg_filename = 'sample.multi_color.svg')
draw_strokes_eos_weighted(strokes, params, factor=8, svg_filename = 'sample.eos.svg')
draw_strokes_pdf(strokes, params, factor=8, svg_filename = 'sample.pdf.svg')

example1a example1b example1c example1d example1e

Have fun-

License

MIT

Owner
hardmaru
I make simple things with neural networks.
hardmaru
GitHub Repository
Audio Visual Emotion Recognition using TDA

Audio Visual Emotion Recognition using TDA RAVDESS database with two datasets analyzed: Video and Audio dataset: Audio-Dataset: https://www.kaggle.com

Combinatorial Image Analysis research group 3 May 11, 2022
CLDF dataset derived from Robbeets et al.'s "Triangulation Supports Agricultural Spread" from 2021

CLDF dataset derived from Robbeets et al.'s "Triangulation Supports Agricultural Spread" from 2021 How to cite If you use these data please cite the o

Digital Linguistics 2 Dec 20, 2021
Code for our paper "Sematic Representation for Dialogue Modeling" in ACL2021

AMR-Dialogue An implementation for paper "Semantic Representation for Dialogue Modeling". You may find our paper here. Requirements python 3.6 pytorch

xfbai 45 Dec 26, 2022
Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

MI-AOD Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection (The PDF is not available tem

Tianning Yuan 269 Dec 21, 2022
Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic [Paper] [Colab is coming soon] Approach Example Usage To r

170 Jan 03, 2023
Pytorch implementation for Patient Knowledge Distillation for BERT Model Compression

Patient Knowledge Distillation for BERT Model Compression Knowledge distillation for BERT model Installation Run command below to install the environm

Siqi 180 Dec 19, 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
TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors

TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors This package provides a simulator for vision-based

Facebook Research 255 Dec 27, 2022
Implementation of Stochastic Image-to-Video Synthesis using cINNs.

Stochastic Image-to-Video Synthesis using cINNs Official PyTorch implementation of Stochastic Image-to-Video Synthesis using cINNs accepted to CVPR202

CompVis Heidelberg 135 Dec 28, 2022
PSTR: End-to-End One-Step Person Search With Transformers (CVPR2022)

PSTR (CVPR2022) This code is an official implementation of "PSTR: End-to-End One-Step Person Search With Transformers (CVPR2022)". End-to-end one-step

Jiale Cao 28 Dec 13, 2022
Deep universal probabilistic programming with Python and PyTorch

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

7.7k Dec 30, 2022
Heart Arrhythmia Classification

This program takes and input of an ECG in European Data Format (EDF) and outputs the classification for heartbeats into normal vs different types of arrhythmia . It uses a deep learning model for cla

4 Nov 02, 2022
TensorFlow Metal Backend on Apple Silicon Experiments (just for fun)

tf-metal-experiments TensorFlow Metal Backend on Apple Silicon Experiments (just for fun) Setup This is tested on M1 series Apple Silicon SOC only. Te

Timothy Liu 161 Jan 03, 2023
This repository contains the code for "Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP".

Self-Diagnosis and Self-Debiasing This repository contains the source code for Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based

Timo Schick 62 Dec 12, 2022
DARTS-: Robustly Stepping out of Performance Collapse Without Indicators

[ICLR'21] DARTS-: Robustly Stepping out of Performance Collapse Without Indicators [openreview] Authors: Xiangxiang Chu, Xiaoxing Wang, Bo Zhang, Shun

55 Nov 01, 2022
Autonomous racing with the Anki Overdrive

Anki Autonomous Racing Autonomous racing with the Anki Overdrive. Using the Overdrive-Python API (https://github.com/xerodotc/overdrive-python) develo

3 Dec 11, 2022
Code for Massive-scale Decoding for Text Generation using Lattices

Massive-scale Decoding for Text Generation using Lattices Jiacheng Xu, Greg Durrett TL;DR: a new search algorithm to construct lattices encoding many

Jiacheng Xu 37 Dec 18, 2022
Fast, Attemptable Route Planner for Navigation in Known and Unknown Environments

FAR Planner uses a dynamically updated visibility graph for fast replanning. The planner models the environment with polygons and builds a global visi

Fan Yang 346 Dec 30, 2022
Contrastive Learning Inverts the Data Generating Process

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

71 Nov 25, 2022
Synthetic Humans for Action Recognition, IJCV 2021

SURREACT: Synthetic Humans for Action Recognition from Unseen Viewpoints Gül Varol, Ivan Laptev and Cordelia Schmid, Andrew Zisserman, Synthetic Human

Gul Varol 59 Dec 14, 2022