How to use EasyOCR tool to recognize image text in Python

What is EasyOCR?

Description: EasyOCR is a python module for extracting text from images. It is a general-purpose OCR that can read both natural scene text and documents. Dense text in . Currently supports over 80 languages ​​and all popular writing scripts including: Latin, Chinese, Arabic, Sanskrit, Cyrillic, and more.

EasyOCR is an optical character recognition (OCR) tool implemented in PyTorch.

Q: What can you do with EasyOCR?

Description: EasyOCR supports two ways to run, one is a commonly used CPU, and the other requires GPU support and the CUDA environment needs to be installed. We use It can perform language and text recognition in pictures, such as picture recognition in mini programs and vehicle license plate recognition (i.e., car debt management system).

Install EasyOCR

In the command window, use pip to install the stable version of EasyOCR.

pip install easyocr

When you use EasyOCR

import easyocr

reader = easyocr.Reader(
    ['ch_sim', 'en'],
    gpu=False,
    model_storage_directory='model/.',
    user_network_directory='model/.',
)
result = reader.readtext('examples/chinese.jpg')

to execute the above code, the detection and recognition model will be automatically downloaded to the specified directory through the network.

• ['ch_sim', 'en'],: Specify the recognized language

• gpu=False,: Set whether to use GPU (EasyOCR It runs more efficiently on GPU. Set False when there is no GPU or insufficient GPU memory)

• model_storage_directory='model/.',: Detect and identify the storage path of the model (when not set) Stored in the ~/.EasyOCR/model directory by default)

The recognition resultresult is a list, and each item in the list is a length of 3 recognition results, for example ([[189, 75], [469, 75], [469, 165], [189, 165]], 'Yuyuan Road', 0.3754989504814148) , which are bounding box, detected text and confidence values ​​respectively.

easyocr-server

EasyOCR server is a server for extracting text from images. It is a general-purpose OCR that can read both natural scene text and dense text in documents. Currently 80 languages ​​are supported and growing.

Installation steps

Step 0. Download easyocr-server from GitHub and install it.

git clone https://github.com/hekaiyou/easyocr-server.git

Step 1. Install easyocr, bottle and gevent modules using PyPI.

cd easyocr-server
pip install -r requirements.txt

Verify installation

python main.py

• Browser: http://localhost:8080/ocr/

• CMD: curl http://localhost:8080/ocr/ -F "language=en" -F "img_file=@examples/english.png"

After successful verification, you should be able to see the printed inference results in the browser.

Deployment service through Docker

We provide a Dockerfile to build the image.

docker build -t easyocr-server:latest .

Run it.

docker run -it -v {DATA_DIR}:/workspace/model -p 8083:8080 easyocr-server:latest

Language	Code Name
Abaza	abq
Adyghe	ady
Afrikaans	af
Angika	ang
Arabic	ar
Assamese	as
Avar	ava
Azerbaijani	az
Belarusian	be
Bulgarian	bg
Bihari	bh
Bhojpuri	bho
Bengali	bn
Bosnian	bs
Simplified Chinese	ch_sim
Traditional Chinese	ch_tra
Chechen	che
Czech	cs
Welsh	cy
Danish	da
Dargwa	dar
German	de
English	en
Spanish	es
Estonian	et
Persian (Farsi)	fa
French	fr
Irish	ga
Goan Konkani	gom
Hindi	hi
Croatian	hr
Hungarian	hu
Indonesian	id
Ingush	inh
Icelandic	is
Italian	it
Japanese	ja
Kabardian	kbd
Kannada	kn
Korean	ko
Kurdish	ku
Latin	la
Lak	lbe
Lezghian	lez
Lithuanian	lt
Latvian	lv
Magahi	mah
Maithili	mai
Maori	mi
Mongolian	mn
Marathi	mr
Malay	ms
Maltese	mt
Nepali	ne
Newari	new
Dutch	nl
Norwegian	no
Occitan	oc
Pali	pi
Polish	pl
Portuguese	pt
Romanian	ro
Russian	ru
Serbian (cyrillic)	rs_cyrillic
Serbian (latin)	rs_latin
Nagpuri	sck
Slovak	sk
Slovenian	sl
Albanian	sq
Swedish	sv
Swahili	sw
Tamil	ta
Tabassaran	tab
Telugu	te
Thai	th
Tajik	tjk
Tagalog	tl
Turkish	tr
Uyghur	ug
Ukranian	uk
Urdu	ur
Uzbek	uz
Vietnamese	vi

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