A cross-platform framework for deep learning based text detection, recoginition and parsing
Project description
deeptext
A cross-platform framework for deep learning based text detection, recoginition and parsing
Getting started
Installation
- Install using conda for Linux, Mac and Windows (preferred):
conda install -c fcakyon deeptext
- Install using pip for Linux and Mac:
pip install deeptext
Install teserract-ocr for text recognition.
Basic Usage
# import package
import deeptext
# set image path and export folder directory
image_path = 'idcard.png'
output_dir = 'outputs/'
# apply text detection and export detected regions to output directory
detection_result = deeptext.detect_text(image_path, output_dir)
# apply text recognition to detected texts
recognition_result = deeptext.recognize_text(image_path=detection_result["text_crop_paths"])
Advanced Usage
You can pass filter parameters if you want to scrap texts from image by predefined regions.
# import package
import deeptext
# set image path and export folder directory
image_path = 'idcard.png'
output_dir = 'outputs/'
# define regions that you want to scrap, by quad (box) points
filter_params = {"type": "box"
"boxes": [[[0.1460 , 0.0395],
[0.8417, 0.0535],
[0.8412, 0.1099],
[0.1455, 0.0959]],
[[0.3467, 0.3398],
[0.5417, 0.3535],
[0.5412, 0.4099],
[0.3455, 0.3959]]],
"marigin_x": 0.05,
"marigin_y": 0.05,
"min_intersection_ratio": 0.9}
# or define regions that you want to scrap, by centroids
filter_params = {"type":"centroid",
"centers": [[0.44, 0.49],[0.49, 0.08]],
"marigin_x": 0.03,
"marigin_y": 0.05}
# apply craft text detection in predefined regions and export detected regions to output directory
detection_result = deeptext.detect_text(image_path,
output_dir,
detector="craft",
filter_params=filter_params)
# apply tesseract (eng) text recognition to detected texts
recognition_result = deeptext.recognize_text(image_path=detection_result["text_crop_paths"],
recognizer="tesseract-eng")
Updates
6 April, 2020: Conda package release
3 April, 2020: Tesseract text recoginition and positional text scraping support
30 March, 2020: Craft text detector support
TODO
- Craft text detection (inference)
- Ctpn text detection (inference)
- Psenet text detection (inference)
- Tesseract text recoginition (inference)
- Aster text recognition (training and inference)
- Moran text recognition (training and inference)
- Positional text scraping
Project details
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