Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train.

Overview

Handwritten Line Text Recognition using Deep Learning with Tensorflow

Description

Use Convolutional Recurrent Neural Network to recognize the Handwritten line text image without pre segmentation into words or characters. Use CTC loss Function to train. More read this Medium Post

Why Deep Learning?

Why Deep Learning

Deep Learning self extracts features with a deep neural networks and classify itself. Compare to traditional Algorithms it performance increase with Amount of Data.

Basic Intuition on How it Works.

Step_wise_detail

  • First Use Convolutional Recurrent Neural Network to extract the important features from the handwritten line text Image.
  • The output before CNN FC layer (512x100x8) is passed to the BLSTM which is for sequence dependency and time-sequence operations.
  • Then CTC LOSS Alex Graves is used to train the RNN which eliminate the Alignment problem in Handwritten, since handwritten have different alignment of every writers. We just gave the what is written in the image (Ground Truth Text) and BLSTM output, then it calculates loss simply as -log("gtText"); aim to minimize negative maximum likelihood path.
  • Finally CTC finds out the possible paths from the given labels. Loss is given by for (X,Y) pair is: Ctc_Loss
  • Finally CTC Decode is used to decode the output during Prediction.

Detail Project Workflow

Architecture of Model

  • Project consists of Three steps:
    1. Multi-scale feature Extraction --> Convolutional Neural Network 7 Layers
    2. Sequence Labeling (BLSTM-CTC) --> Recurrent Neural Network (2 layers of LSTM) with CTC
    3. Transcription --> Decoding the output of the RNN (CTC decode) DetailModelArchitecture

Requirements

  1. Tensorflow 1.8.0
  2. Flask
  3. Numpy
  4. OpenCv 3
  5. Spell Checker autocorrect >=0.3.0 pip install autocorrect

Dataset Used

  • IAM dataset download from here
  • Only needed the lines images and lines.txt (ASCII).
  • Place the downloaded files inside data directory
The Trained model is available and download from this link. The trained model CER=8.32% and trained on IAM dataset with some additional created dataset.

To Train the model from scratch

$ python main.py --train

To validate the model

$ python main.py --validate

To Prediction

$ python main.py

Run in Web with Flask

$ python upload.py
Validation character error rate of saved model: 8.654728%
Python: 3.6.4 
Tensorflow: 1.8.0
Init with stored values from ../model/snapshot-24
Without Correction clothed leaf by leaf with the dioappoistmest
With Correction clothed leaf by leaf with the dioappoistmest

Prediction output on IAM Test Data PredictionOutput

Prediction output on Self Test Data PredictionOutput

See the project Devnagari Handwritten Word Recognition with Deep Learning for more insights.

Further Improvement

  • Using MDLSTM to recognize whole paragraph at once Scan, Attend and Read: End-to-End Handwritten Paragraph Recognition with MDLSTM Attention
  • Line segementation can be added for full paragraph text recognition. For line segmentation you can use A* path planning algorithm or CNN model to seperate paragraph into lines.
  • Better Image preprocessing such as: reduce backgoround noise to handle real time image more accurately.
  • Better Decoding approach to improve accuracy. Some of the CTC Decoder found here

Feel Free to improve this project with pull Request.

This is part of my last semester project of Computer Engineering From Tribhuvan University. July 2019

Owner
sushant097
Machine Learning Engineer | Computer Vision Developer. Working in the field of Research, development of Machine learning and Computer Vision .
sushant097
Motion detector, Full body detection, Upper body detection, Cat face detection, Smile detection, Face detection (haar cascade), Silverware detection, Face detection (lbp), and Sending email notifications

Security camera running OpenCV for object and motion detection. The camera will send email with image of any objects it detects. It also runs a server that provides web interface with live stream vid

Peace 10 Jun 30, 2021
Document Image Dewarping

Document image dewarping using text-lines and line Segments Abstract Conventional text-line based document dewarping methods have problems when handli

Taeho Kil 268 Dec 23, 2022
Convert Text-to Handwriting Using Python

Convert Text-to Handwriting Using Python Description In this project we'll use python library that's "pywhatkit" for converting text to handwriting. t

8 Nov 19, 2022
Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.

Omdena-abuja-anpd - Automatic Number Plate Detection for the security of lives and properties using Computer Vision.

Abdulazeez Jimoh 1 Jan 01, 2022
learn how to use Gesture Control to change the volume of a computer

Volume-Control-using-gesture In this project we are going to learn how to use Gesture Control to change the volume of a computer. We first look into h

Diwas Pandey 49 Sep 22, 2022
Code for the paper: Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution

Fusformer Code for the paper: "Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution" Plateform Python 3.8.5 + Pytor

Jin-Fan Hu (胡锦帆) 11 Dec 12, 2022
M-LSDを用いて四角形を検出し、射影変換を行うサンプルプログラム

M-LSD-warpPerspective-Example M-LSDを用いて四角形を検出し、射影変換を行うサンプルプログラムです。 Requirements OpenCV 3.4.2 or Later tensorflow 2.4.1 or Later Usage 実行方法は以下です。 pytho

KazuhitoTakahashi 9 Oct 14, 2022
MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition

MORAN: A Multi-Object Rectified Attention Network for Scene Text Recognition Python 2.7 Python 3.6 MORAN is a network with rectification mechanism for

Canjie Luo 595 Dec 27, 2022
This repository contains the code for the paper "SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks"

SCANimate: Weakly Supervised Learning of Skinned Clothed Avatar Networks (CVPR 2021 Oral) This repository contains the official PyTorch implementation

Shunsuke Saito 235 Dec 18, 2022
Forked from argman/EAST for the ICPR MTWI 2018 CHALLENGE

EAST_ICPR: EAST for ICPR MTWI 2018 CHALLENGE Introduction This is a repository forked from argman/EAST for the ICPR MTWI 2018 CHALLENGE. Origin Reposi

Haozheng Li 157 Aug 23, 2022
Unofficial implementation of "TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from Scanned Document Images"

TableNet Unofficial implementation of ICDAR 2019 paper : TableNet: Deep Learning model for end-to-end Table detection and Tabular data extraction from

Jainam Shah 243 Dec 30, 2022
Hiiii this is the Spanish for Linux and win 10 and in the near future the english version of PortScan my new tool on which you can see what ports are Open only with the IP adress.

PortScanner-by-IIT PortScanner es una herramienta programada en Python3. Como su nombre indica esta herramienta escanea los primeros 150 puertos de re

5 Sep 19, 2022
A collection of resources (including the papers and datasets) of OCR (Optical Character Recognition).

OCR Resources This repository contains a collection of resources (including the papers and datasets) of OCR (Optical Character Recognition). Contents

Zuming Huang 363 Jan 03, 2023
Qrcode Attendence System with Opencv and Pyzbar

Setup process Creates a virtual environment (Scripts that ensure executed Python code uses the Python interpreter and site packages installed inside t

Ganesh 5 Aug 01, 2022
Code for CVPR 2022 paper "SoftGroup for Instance Segmentation on 3D Point Clouds"

SoftGroup We provide code for reproducing results of the paper SoftGroup for 3D Instance Segmentation on Point Clouds (CVPR 2022) Author: Thang Vu, Ko

Thang Vu 231 Dec 27, 2022
Repository collecting all the submodules for the new PyTorch-based OCR System.

OCRopus3 is being replaced by OCRopus4, which is a rewrite using PyTorch 1.7; release should be soonish. Please check github.com/tmbdev/ocropus for up

NVIDIA Research Projects 138 Dec 09, 2022
TextBoxes re-implement using tensorflow

TextBoxes-TensorFlow TextBoxes re-implementation using tensorflow. This project is greatly inspired by slim project And many functions are modified ba

Gu Xiaodong 44 Dec 29, 2022
(CVPR 2021) ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

ST3D Code release for the paper ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection, CVPR 2021 Authors: Jihan Yang*, Shaoshu

CVMI Lab 224 Dec 28, 2022
Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and limited )

GTA-5-Lane-detection Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and

Danciu Georgian 4 Aug 01, 2021
graph learning code for ogb

The final code for OGB Installation Requirements: ogb=1.3.1 torch=1.7.0 torch-geometric=1.7.0 torch-scatter=2.0.6 torch-sparse=0.6.9 Baseline models T

PierreHao 20 Nov 10, 2022