qurator-spk/sbb_binarization
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# Conflicts:
#	README.md
#	sbb_binarize/cli.py
#	sbb_binarize/sbb_binarize.py
This commit is contained in:
Alexander Pacha 2022-11-22 16:10:22 +01:00
commit 9ef8259677
5 changed files with 45 additions and 10 deletions
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7
CHANGELOG.md
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@ -4,6 +4,12 @@ Versioned according to [Semantic Versioning](http://semver.org/).
## Unreleased
## [0.0.10] - 2022-10-24
Added:
* Trained models listed in ocrd-tool.json for download with OCR-D resource manager, #53
## [0.0.10] - 2022-07-21
Fixed:
@ -71,6 +77,7 @@ Fixed:
Initial release
<!-- link-labels -->
[0.0.11]: ../../compare/v0.0.11...v0.0.10
[0.0.10]: ../../compare/v0.0.10...v0.0.9
[0.0.9]: ../../compare/v0.0.9...v0.0.8
[0.0.8]: ../../compare/v0.0.8...v0.0.7

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README.md
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@ -8,7 +8,7 @@
## Introduction
This tool performs document image binarization using trained models. The method is based on [Calvo-Zaragoza and Gallego, 2018](https://arxiv.org/abs/1706.10241).
This tool performs document image binarization using a trained ResNet50-UNet model.
## Installation
@ -18,10 +18,14 @@ Clone the repository, enter it and run
### Models
Pre-trained models can be downloaded from here:
Pre-trained models in `HDF5` format can be downloaded from here:
https://qurator-data.de/sbb_binarization/
We also provide a Tensorflow `saved_model` via Huggingface:
https://huggingface.co/SBB/sbb_binarization
## Usage
```sh
@ -31,7 +35,9 @@ sbb_binarize \
<output image>
```
Example
Images containing a lot of border noise (black pixels) should be cropped beforehand to improve the quality of results.
### Example
```sh
sbb_binarize -m /path/to/models/ myimage.tif myimage-bin.tif

2
requirements.txt
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@ -1,6 +1,6 @@
numpy
setuptools >= 41
opencv-python-headless
ocrd >= 2.22.3
ocrd >= 2.38.0
tensorflow >= 2.4.0
mpire

24
sbb_binarize/ocrd-tool.json
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@ -1,5 +1,5 @@
{
"version": "0.0.10",
"version": "0.0.11",
"git_url": "https://github.com/qurator-spk/sbb_binarization",
"tools": {
"ocrd-sbb-binarize": {
@ -17,13 +17,31 @@
"description": "PAGE XML hierarchy level to operate on"
},
"model": {
"description": "Directory containing HDF5 models. Can be an absolute path or a path relative to the current working directory or $SBB_BINARIZE_DATA environment variable (if set)",
"description": "Directory containing HDF5 or SavedModel/ProtoBuf models. Can be an absolute path or a path relative to the OCR-D resource location, the current working directory or the $SBB_BINARIZE_DATA environment variable (if set)",
"type": "string",
"format": "uri",
"content-type": "text/directory",
"required": true
}
}
},
"resources": [
{
"url": "https://github.com/apacha/sbb_binarization/releases/download/pre-trained-models/model_2020_01_16.zip",
"name": "default",
"type": "archive",
"path_in_archive": "model_2020_01_16",
"size": 562917559,
"description": "default models provided by github.com/qurator-spk"
},
{
"url": "https://github.com/apacha/sbb_binarization/releases/download/pre-trained-models/model_2021_03_09.zip",
"name": "default-2021-03-09",
"type": "archive",
"path_in_archive": ".",
"size": 133693693,
"description": "updated default models provided by github.com/qurator-spk"
}
]
}
}
}

10
sbb_binarize/ocrd_cli.py
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@ -30,6 +30,10 @@ def cv2pil(img):
def pil2cv(img):
# from ocrd/workspace.py
if img.mode in ('LA', 'RGBA'):
newimg = Image.new(img.mode[:-1], img.size, 'white')
newimg.paste(img, mask=img.getchannel('A'))
img = newimg
color_conversion = cv2.COLOR_GRAY2BGR if img.mode in ('1', 'L') else cv2.COLOR_RGB2BGR
pil_as_np_array = np.array(img).astype('uint8') if img.mode == '1' else np.array(img)
return cv2.cvtColor(pil_as_np_array, color_conversion)
@ -106,7 +110,7 @@ class SbbBinarizeProcessor(Processor):
if oplevel == 'page':
LOG.info("Binarizing on 'page' level in page '%s'", page_id)
bin_image = cv2pil(self.binarizer.run(image=pil2cv(page_image), use_patches=True))
bin_image = cv2pil(self.binarizer.run(image=pil2cv(page_image)))
# update METS (add the image file):
bin_image_path = self.workspace.save_image_file(bin_image,
file_id + '.IMG-BIN',
@ -120,7 +124,7 @@ class SbbBinarizeProcessor(Processor):
LOG.warning("Page '%s' contains no text/table regions", page_id)
for region in regions:
region_image, region_xywh = self.workspace.image_from_segment(region, page_image, page_xywh, feature_filter='binarized')
region_image_bin = cv2pil(binarizer.run(image=pil2cv(region_image), use_patches=True))
region_image_bin = cv2pil(binarizer.run(image=pil2cv(region_image)))
region_image_bin_path = self.workspace.save_image_file(
region_image_bin,
"%s_%s.IMG-BIN" % (file_id, region.id),
@ -135,7 +139,7 @@ class SbbBinarizeProcessor(Processor):
LOG.warning("Page '%s' contains no text lines", page_id)
for region_id, line in region_line_tuples:
line_image, line_xywh = self.workspace.image_from_segment(line, page_image, page_xywh, feature_filter='binarized')
line_image_bin = cv2pil(binarizer.run(image=pil2cv(line_image), use_patches=True))
line_image_bin = cv2pil(binarizer.run(image=pil2cv(line_image)))
line_image_bin_path = self.workspace.save_image_file(
line_image_bin,
"%s_%s_%s.IMG-BIN" % (file_id, region_id, line.id),