Arabic Handwritten Document Data-Listing Solution

How To Install

conda create -n ahdoc python=3.10
conda activate ahdoc

conda install ipython pip

# python dependencies
pip install -r requirement.txt

# clone repo
git clone https://github.com/Hedrax/AHDoc.git
cd AHDoc/

Data

Text-Detection

• Arabic Documents OCR Dataset

Evaluation

• Custom Data

OCR ENGINE

• Raw Data

Model Best-Weights

• Text Detecion
• OCR - Model

Data Preparation

Text-Detection

• Datasets must follow the format of the custom Data format provided above
• utils.py has all functions needed to migrate from JSON with Pascal and txt with Yolo format
• utils.py also has all functions needed to list image names and get corresponding label files to list in .txt file

OCR Engine

• Datasets must follow the format all images in png in the same directory with labels.txt labels must be in the form imageNameWithoutExtension_groundTruth
• utils.py has all functions needed for dataset preparation

Train

• Follow instructions in train.py
• All training configurations are saved in config.py

Test

• put the weights files downloaded from the above reference to ./Text Detection/weights/ and ./OCR Engine/weights/
• Follow instructions in inference.py and evaluation.py in terms of OCR Engine
• All test configurations are saved in config.py

Results

Text-Detection

We compare best-weights of universal model performance on our custom evaluation Arabic handwritten data

Weights	Precision (%)	Recall (%)	F-measure (%)
Universal Model	61.53	34.60	41.33
Our-Model	81.66	78.82	79.07

OCR Module Performance Results

our results on the TEST set of 18-fonts

#	Number of Words	Solid Accuracy%		Salted Accuracy%		Bolded Accuracy%		Notes
		CRR	WRR	CRR	WRR	CRR	WRR
1	1	94.28	70.05	91.85	57.08	77.25	17.81	Tested on 7-Character Words
2	1	94.24	54.06	91.42	50.94	90.19	46.04	-
3	2	89.81	39.38	87.11	34.84	86.75	33.85	-
4	3	89.64	35.63	88.23	37.39	87.79	35.59	-
5	4	82.23	28.59	80.41	24.61	80.25	24.61	-
6	5	73.17	20.25	71.88	17.225	70.25	16.62	-
7	6	66.01	18.78	64.95	13.48	63.50	14.39	-

Demo

Text-Detection

OCR-ENGINE

reference

1. https://arxiv.org/abs/1911.08947
2. https://github.com/zonasw/DBNet
3. https://github.com/MhLiao/DB