Craft Text Detector Versions Save

Packaged, Pytorch-based, easy to use, cross-platform version of the CRAFT text detector

0.4.3

2 years ago

What's Changed

New Contributors

Full Changelog: https://github.com/fcakyon/craft-text-detector/compare/0.4.2...0.4.3

0.4.2

2 years ago

0.4.1

2 years ago

0.4.0

2 years ago

enhancement

  • fix boxes outside image boundaries (#37)

breaking changes

  • drop conda support, update python version (#38)

0.3.5

3 years ago
  • Rebuild conda binaries.

0.3.4

3 years ago
from PIL import Image
import numpy

# can be filepath, PIL image or numpy array
image = 'figures/idcard.png' 
image = Image.open("figures/idcard.png")
image = numpy.array(Image.open("figures/idcard.png"))

# apply craft text detection
prediction_result = craft.detect_text(image)

0.3.3

3 years ago
  • Relax requirements for OpenCV (#25)

0.3.2

3 years ago

path for the weight file can be specified by:

load_craftnet_model(weight_path="path/to/weight")
load_refinenet_model(weight_path="path/to/weight")

v0.3.1

4 years ago

v0.3.0

4 years ago
  • updated basic usage for better device handling, now Craft instance should be created before calling detect_text:
# import Craft class
from craft_text_detector import Craft

# set image path and export folder directory
image_path = 'figures/idcard.png'
output_dir = 'outputs/'

# create a craft instance
craft = Craft(output_dir=output_dir, crop_type="poly", cuda=False)

# apply craft text detection and export detected regions to output directory
prediction_result = craft.detect_text(image_path)

# unload models from ram/gpu
craft.unload_craftnet_model()
craft.unload_refinenet_model()
  • some internal naming and styling changes