Spaces:
Sleeping
title: IndicPhotoOCR
colorFrom: purple
colorTo: pink
sdk: gradio
python_version: '3.9'
sdk_version: 4.44.0
app_file: app.py
pinned: true
CPU: cpu-basic
suggested_storage: small
app_port: 7865
IndicPhotoOCR - Comprehensive Scene Text Recognition Toolkit
across 13 Indian Languages
IndicPhotoOCR is an advanced OCR toolkit designed for detecting, identifying, and recognizing text across 13 Indian languages, including Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Meitei Odia, Punjabi, Tamil, Telugu, Urdu, and English. Built to handle the unique scripts and complex structures of Indian languages, IndicPhotoOCR provides robust detection and recognition capabilities, making it a valuable tool for processing multilingual documents and enhancing document analysis in these diverse scripts.
Table of Content
Updates
Installation
How to use
Acknowledgement
Contact us
Updates
[November 2024]: Try demo in huggingface space.
[November 2024]: Use this package in Google Colab.
[November 2024]: Added support for 10 languages in the recognition module.
[September 2024]: Private repository created.
Installation
Currently we need to manually create virtual environemnt.
conda create -n indicphotoocr python=3.9 -y
conda activate indicphotoocr
git clone https://github.com/Bhashini-IITJ/IndicPhotoOCR.git
cd IndicPhotoOCR
CPU Installation
python setup.py sdist bdist_wheel
pip install dist/IndicPhotoOCR-1.1.0-py3-none-any.whl[cpu]
CUDA 11.8 Installation
python setup.py sdist bdist_wheel
pip install ./dist/IndicPhotoOCR-1.1.0-py3-none-any.whl[cu118] --extra-index-url https://download.pytorch.org/whl/cu118
CUDA 12.1 Installation
python setup.py sdist bdist_wheel
pip install ./dist/IndicPhotoOCR-1.1.0-py3-none-any.whl[cu121] --extra-index-url https://download.pytorch.org/whl/cu121
If you find any trouble with the above installation use the setup.sh script.
chmod +x setup.sh
./setup.sh
Config
Currently this model works for hindi v/s english script identification and thereby hindi and english recognition.
Detection Model: EAST
ScripIndetification Model: Hindi v/s English
Recognition Model: Hindi, English, Assamese, Bengali, Gujarati, Marathi, Odia, Punjabi, Tamil, Telugu.
How to use
Detection
>>> from IndicPhotoOCR.ocr import OCR
# Create an object of OCR
>>> ocr_system = OCR(verbose=True) # for CPU --> OCR(device="cpu")
# Get detections
>>> detections = ocr_system.detect("test_images/image_141.jpg")
# Running text detection...
# 4334 text boxes before nms
# 1.027989387512207
# Save and visualize the detection results
>>> ocr_system.visualize_detection("test_images/image_141.jpg", detections)
# Image saved at: test.png
Cropped Word Recognition
>>> from IndicPhotoOCR.ocr import OCR
# Create an object of OCR
>>> ocr_system = OCR(verbose=True) # for CPU --> OCR(device="cpu")
# Get recognitions
>>> ocr_system.recognise("test_images/cropped_image/image_141_0.jpg", "hindi")
# Recognizing text in detected area...
# 'मण्डी'
End-to-end Scene Text Recognition
>>> from IndicPhotoOCR.ocr import OCR
# Create an object of OCR
>>> ocr_system = OCR(verbose=True) # for CPU --> OCR(device="cpu")
# Complete pipeline
>>> ocr_system.ocr("test_images/image_141.jpg")
# Running text detection...
# 4334 text boxes before nms
# 0.9715704917907715
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: रोड
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: बाराखम्ब
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: barakhaml
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: हाऊस
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: mandi
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: chowk
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: मण्डी
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: road
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: house
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Using cache found in /DATA1/ocrteam/.cache/torch/hub/baudm_parseq_main
# Recognized word: rajiv
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: राजीव
# Identifying script for the cropped area...
# Recognizing text in detected area...
# Recognized word: चौक
Acknowledgement
Text Recognition - PARseq
EAST re-implemenation repository.
National Language Translation Mission Bhashini.
Contact us
For any queries, please contact us at: