Unify the way backends are defined and loaded, unify the fs_cleanup function
This commit is contained in:
Roberto Rosario
199
mayan/apps/converter/backends/python.py
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199
mayan/apps/converter/backends/python.py
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from __future__ import absolute_import
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import os
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import tempfile
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import slate
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from PIL import Image
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try:
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import ghostscript
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USE_GHOSTSCRIPT = True
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except RuntimeError:
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USE_GHOSTSCRIPT = False
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from common.utils import fs_cleanup
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from mimetype.api import get_mimetype
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from . import ConverterBase
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from ..exceptions import UnknownFileFormat
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from ..literals import (TRANSFORMATION_RESIZE, TRANSFORMATION_ROTATE,
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TRANSFORMATION_ZOOM, DEFAULT_PAGE_NUMBER, DEFAULT_FILE_FORMAT)
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Image.init()
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class Python(ConverterBase):
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def get_page_count(self, input_filepath):
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page_count = 1
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mimetype, encoding = get_mimetype(open(input_filepath, 'rb'), input_filepath, mimetype_only=True)
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if mimetype == 'application/pdf':
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# If file is a PDF open it with slate to determine the page
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# count
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with open(input_filepath) as fd:
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try:
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pages = slate.PDF(fd)
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except:
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return 1
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# TODO: Maybe return UnknownFileFormat to display proper unknwon file format message in document description
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return len(pages)
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try:
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im = Image.open(input_filepath)
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except IOError: # cannot identify image file
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raise UnknownFileFormat
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try:
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while 1:
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im.seek(im.tell() + 1)
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page_count += 1
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# do something to im
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except EOFError:
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pass # end of sequence
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return page_count
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def convert_file(self, input_filepath, output_filepath, transformations=None, page=DEFAULT_PAGE_NUMBER, file_format=DEFAULT_FILE_FORMAT, **kwargs):
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tmpfile = None
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mimetype = kwargs.get('mimetype', None)
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if not mimetype:
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mimetype, encoding = get_mimetype(open(input_filepath, 'rb'), input_filepath, mimetype_only=True)
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if mimetype == 'application/pdf' and USE_GHOSTSCRIPT:
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# If file is a PDF open it with ghostscript and convert it to
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# TIFF
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first_page_tmpl = '-dFirstPage=%d' % page
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last_page_tmpl = '-dLastPage=%d' % page
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fd, tmpfile = tempfile.mkstemp()
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os.close(fd)
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output_file_tmpl = '-sOutputFile=%s' % tmpfile
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input_file_tmpl = '-f%s' % input_filepath
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args = [
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'gs', '-q', '-dQUIET', '-dSAFER', '-dBATCH',
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'-dNOPAUSE', '-dNOPROMPT',
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first_page_tmpl, last_page_tmpl,
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'-sDEVICE=jpeg', '-dJPEGQ=95',
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'-r150', output_file_tmpl,
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input_file_tmpl,
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'-c "60000000 setvmthreshold"', # use 30MB
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'-dNOGC', # No garbage collection
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'-dMaxBitmap=500000000',
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'-dAlignToPixels=0',
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'-dGridFitTT=0',
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'-dTextAlphaBits=4',
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'-dGraphicsAlphaBits=4',
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]
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ghostscript.Ghostscript(*args)
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page = 1 # Don't execute the following while loop
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input_filepath = tmpfile
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try:
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im = Image.open(input_filepath)
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except Exception:
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# Python Imaging Library doesn't recognize it as an image
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raise UnknownFileFormat
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finally:
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if tmpfile:
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fs_cleanup(tmpfile)
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current_page = 0
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try:
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while current_page == page - 1:
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im.seek(im.tell() + 1)
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current_page += 1
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# do something to im
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except EOFError:
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# end of sequence
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pass
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try:
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if transformations:
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aspect = 1.0 * im.size[0] / im.size[1]
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for transformation in transformations:
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arguments = transformation.get('arguments')
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if transformation['transformation'] == TRANSFORMATION_RESIZE:
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width = int(arguments.get('width', 0))
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height = int(arguments.get('height', 1.0 * width * aspect))
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im = self.resize(im, (width, height))
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elif transformation['transformation'] == TRANSFORMATION_ZOOM:
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decimal_value = float(arguments.get('percent', 100)) / 100
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im = im.transform((int(im.size[0] * decimal_value), int(im.size[1] * decimal_value)), Image.EXTENT, (0, 0, im.size[0], im.size[1]))
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elif transformation['transformation'] == TRANSFORMATION_ROTATE:
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# PIL counter degress counter-clockwise, reverse them
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im = im.rotate(360 - arguments.get('degrees', 0))
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except:
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# Ignore all transformation error
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pass
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if im.mode not in ('L', 'RGB'):
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im = im.convert('RGB')
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im.save(output_filepath, format=file_format)
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def get_format_list(self):
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"""
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Introspect PIL's internal registry to obtain a list of the
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supported file types
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"""
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formats = []
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for format_name in Image.ID:
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if format_name == 'GBR':
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formats.append('GBR_PIL')
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else:
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formats.append(format_name)
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if USE_GHOSTSCRIPT:
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formats.append('PDF')
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formats.append('PS')
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return formats
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def get_available_transformations(self):
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return [
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TRANSFORMATION_RESIZE, TRANSFORMATION_ROTATE,
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TRANSFORMATION_ZOOM
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]
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# From: http://united-coders.com/christian-harms/image-resizing-tips-general-and-for-python
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def resize(self, img, box, fit=False, out=None):
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"""
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Downsample the image.
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@param img: Image - an Image-object
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@param box: tuple(x, y) - the bounding box of the result image
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@param fit: boolean - crop the image to fill the box
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@param out: file-like-object - save the image into the output stream
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"""
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# preresize image with factor 2, 4, 8 and fast algorithm
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factor = 1
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while img.size[0] / factor > 2 * box[0] and img.size[1] * 2 / factor > 2 * box[1]:
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factor *= 2
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if factor > 1:
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img.thumbnail((img.size[0] / factor, img.size[1] / factor), Image.NEAREST)
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# calculate the cropping box and get the cropped part
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if fit:
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x1 = y1 = 0
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x2, y2 = img.size
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wRatio = 1.0 * x2 / box[0]
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hRatio = 1.0 * y2 / box[1]
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if hRatio > wRatio:
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y1 = y2 / 2 - box[1] * wRatio / 2
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y2 = y2 / 2 + box[1] * wRatio / 2
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else:
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x1 = x2 / 2 - box[0] * hRatio / 2
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x2 = x2 / 2 + box[0] * hRatio / 2
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img = img.crop((x1, y1, x2, y2))
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# Resize the image with best quality algorithm ANTI-ALIAS
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img.thumbnail(box, Image.ANTIALIAS)
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if out:
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# save it into a file-like object
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img.save(out, 'JPEG', quality=75)
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else:
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return img
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# if isinstance(self.regex, basestring):
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# self.regex = re.compile(regex)
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