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This repository has been archived by the owner on Dec 2, 2022. It is now read-only.

Releases: fcakyon/craft-text-detector

v0.4.3

09 May 10:55
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New Contributors

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v0.4.2

06 Jan 11:28
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v0.4.1

20 Dec 11:39
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v0.4.0

30 Jul 10:45
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enhancement

  • fix boxes outside image boundaries (#37)

breaking changes

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

v0.3.5

12 May 13:17
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  • Rebuild conda binaries.

v0.3.4

07 Apr 14:37
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  • add support for PIL and numpy images in addition to filepath. #28
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)

v0.3.3

02 Mar 21:43
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  • Relax requirements for OpenCV (#25)

v0.3.2

02 Mar 05:32
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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")

release 0.3.1

14 May 19:23
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release 0.3.0

14 May 17:54
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  • 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