Package: craft-text-detection
CRAFT: Character-Region Awareness For Text detectionOfficial Pytorch implementation of CRAFT text detector |Paper|Pretrained Model|SupplementaryYoungmin Baek, Bado Lee, Dongyoon Han, Sangdoo Yun, Hwalsuk Lee.Clova AI Research, NAVER Corp.Packaged byAshish JhaSample ResultsOverviewPyTorch implementation for CRAFT text detector that effectively detect text area by exploring each character region and affinity between characters. The bounding box of texts are obtained by simply finding minimum bounding rectangles on binary map after thresholding character region and affinity scores.Updates13 Jun, 2019: Initial update20 Jul, 2019: Added post-processing for polygon result28 Sep, 2019: Added the trained model on IC15 and the link refiner25 Jan, 2020: Put it together as a PyPI packageGetting startedUse it straight from PyPIInstallationpip install craft-text-detectionUsageimport craft
import cv2
img = cv2.imread('/path/to/image/file')

# run the detector
bboxes, polys, heatmap = craft.detect_text(img)

# view the image with bounding boxes
img_boxed = craft.show_bounding_boxes(img, bboxes)
cv2.imshow('fig', img_boxed)

# view detection heatmap
cv2.imshow('fig', heatmap)Use from source - install dependenciesRequirementsPyTorch>=0.4.1torchvision>=0.2.1opencv-python>=3.4.2check requiremetns.txtpip install -r requirements.txtTrainingThe code for training is not included in this repository, and we cannot release the full training code for IP reason.Arguments for detect_text--text_threshold: text confidence threshold--low_text: text low-bound score--link_threshold: link confidence threshold--canvas_size: max image size for inference--mag_ratio: image magnification ratio--refine: use link refiner for sentence-level dataset--refiner_model: pretrained refiner modelLinksWebDemo :https://demo.ocr.clova.ai/Repo of recognition :https://github.com/clovaai/deep-text-recognition-benchmarkCitation@inproceedings{baek2019character,
  title={Character Region Awareness for Text Detection},
  author={Baek, Youngmin and Lee, Bado and Han, Dongyoon and Yun, Sangdoo and Lee, Hwalsuk},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  pages={9365--9374},
  year={2019}
}LicenseCopyright (c) 2019-present NAVER Corp.

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