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3b98a1a04b | ||
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fcb89b0c58 |
+3
-1
@@ -63,9 +63,11 @@ RUN chmod 644 /usr/share/tesseract-ocr/tessdata/pdf.ttf
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# Install application and dependencies
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# In this arrangement Pillow and reportlab will be provided by the system
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# Even though ocrmypdf is locally present, pull from PyPI because
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# Dockerhub and setuptools_scm clash
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RUN . /appenv/bin/activate; \
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pip install --upgrade pip \
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&& pip install /application \
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&& pip install ocrmypdf \
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&& pip install --no-cache-dir -r /application/test_requirements.txt
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# Remove the junk
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+4
-4
@@ -15,15 +15,15 @@ New features
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- Automatic page rotation (``-r``) is now available. It uses ignores any prior rotation information
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on PDFs and sets rotation based on the dominant orientation of detectable text. This feature is
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fairly reliable but some false positives occur especially if there is not much text to work with. (#4)
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- Deskewing is now performed using Leptonica instead of unpaper. Leptonica deskews images faster and
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more reliably than unpaper.
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- Deskewing is now performed using Leptonica instead of unpaper. Leptonica is faster and more reliable
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at image deskewing than unpaper.
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Fixes
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-----
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- Fixed an issue where lossless reconstruction could cause some pages to be appear incorrectly
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rotated in the page had a /Rotate tag applied (#50)
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if the page was rotated by the user in Acrobat after being scanned (specifically if it a /Rotate tag)
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- Fixed an issue where lossless reconstruction could misalign the graphics layer with respect to
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text layer if the page had been cropped such that its origin is not (0, 0) (#49)
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@@ -31,7 +31,7 @@ Fixes
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Changes
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-------
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- Logging output much is now better
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- Logging output is now much easier to read
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- ``--deskew`` is now performed by Leptonica instead of unpaper (#25)
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- libffi is now required
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- Some changes were made to the Docker and Travis build environments to support libffi
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@@ -107,8 +107,8 @@ def get_orientation(input_file, language: list, timeout: float, log):
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osd[parts[0].strip()] = parts[1].strip()
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oc = OrientationConfidence(
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angle=int(osd['Orientation in degrees']),
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confidence=float(osd['Orientation confidence']))
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angle=int(osd.get('Orientation in degrees', 0)),
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confidence=float(osd.get('Orientation confidence', 0)))
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return oc
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