This project part of Efad2 hackathon in Riyadh.
computer vision for Text recognition and clustering words of images that contains Arabic language. This project part of Efad2 hackathon in Riyadh.
EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. they are currently supporting 70+ languages , Arabic language is one of them. #k-means clustering k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster.
Install using pip,
pip install easyocr
we tried Arabic-ocr , tesseract but we did not found a library that read arabic handwritten as we want so we depend on easyocr.import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import cv2
import easyocr
import os
from os import listdir
import random
from PIL import Image , ImageOps
from random import shuffle
from tqdm import tqdm
import glob
from collections import Counter
from sklearn.cluster import KMeans- Define the path of folders contains images.
- change the path of folder that savingthe clustering.
- Run the code easier by colab or JupyterLab.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.