/
optimize.py
590 lines (498 loc) · 21 KB
/
optimize.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
# © 2018 James R. Barlow: github.com/jbarlow83
#
# This file is part of OCRmyPDF.
#
# OCRmyPDF is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OCRmyPDF is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with OCRmyPDF. If not, see <http://www.gnu.org/licenses/>.
import concurrent.futures
import sys
import tempfile
from collections import defaultdict
from os import fspath
from pathlib import Path
import pikepdf
from pikepdf import Dictionary, Name
from PIL import Image
from tqdm import tqdm
from . import leptonica
from ._jobcontext import PDFContext
from .exceptions import OutputFileAccessError
from .exec import jbig2enc, pngquant
from .helpers import safe_symlink
DEFAULT_JPEG_QUALITY = 75
DEFAULT_PNG_QUALITY = 70
def img_name(root, xref, ext):
return fspath(root / f'{xref:08d}{ext}')
def png_name(root, xref):
return img_name(root, xref, '.png')
def jpg_name(root, xref):
return img_name(root, xref, '.jpg')
def tif_name(root, xref):
return img_name(root, xref, '.tif')
def extract_image_filter(pike, root, log, image, xref):
if image.Subtype != Name.Image:
return None
if image.Length < 100:
log.debug("Skipping small image, xref %s", xref)
return None
pim = pikepdf.PdfImage(image)
if len(pim.filter_decodeparms) > 1:
log.debug("Skipping multiply filtered, xref %s", xref)
return None
filtdp = pim.filter_decodeparms[0]
if pim.bits_per_component > 8:
return None # Don't mess with wide gamut images
if filtdp[0] == Name.JPXDecode:
return None # Don't do JPEG2000
if Name.Decode in image:
return None # Don't mess with custom Decode tables
return pim, filtdp
def extract_image_jbig2(*, pike, root, log, image, xref, options):
result = extract_image_filter(pike, root, log, image, xref)
if result is None:
return None
pim, filtdp = result
if (
pim.bits_per_component == 1
and filtdp != Name.JBIG2Decode
and jbig2enc.available()
):
try:
imgname = Path(root / f'{xref:08d}')
with imgname.open('wb') as f:
ext = pim.extract_to(stream=f)
imgname.rename(imgname.with_suffix(ext))
except pikepdf.UnsupportedImageTypeError:
return None
return xref, ext
return None
def extract_image_generic(*, pike, root, log, image, xref, options):
result = extract_image_filter(pike, root, log, image, xref)
if result is None:
return None
pim, filtdp = result
# Don't try to PNG-optimize 1bpp images, since JBIG2 does it better.
if pim.bits_per_component == 1:
return None
try:
pim.indexed # pikepdf 1.6.3 can't handle [/Indexed [/Array...]]
except NotImplementedError:
return None
if filtdp[0] == Name.DCTDecode and options.optimize >= 2:
# This is a simple heuristic derived from some training data, that has
# about a 70% chance of guessing whether the JPEG is high quality,
# and possibly recompressible, or not. The number itself doesn't mean
# anything.
# bytes_per_pixel = int(raw_jpeg.Length) / (w * h)
# jpeg_quality_estimate = 117.0 * (bytes_per_pixel ** 0.213)
# if jpeg_quality_estimate < 65:
# return None
# We could get the ICC profile here, but there's no need to look at it
# for quality transcoding
# if icc:
# stream = BytesIO(raw_jpeg.read_raw_bytes())
# iccbytes = icc.read_bytes()
# with Image.open(stream) as im:
# im.save(jpg_name(root, xref), icc_profile=iccbytes)
try:
imgname = Path(root / f'{xref:08d}')
with imgname.open('wb') as f:
ext = pim.extract_to(stream=f)
imgname.rename(imgname.with_suffix(ext))
except pikepdf.UnsupportedImageTypeError:
return None
return xref, ext
elif (
pim.indexed
and pim.colorspace in pim.SIMPLE_COLORSPACES
and options.optimize >= 3
):
# Try to improve on indexed images - these are far from low hanging
# fruit in most cases
pim.as_pil_image().save(png_name(root, xref))
return xref, '.png'
elif not pim.indexed and pim.colorspace in pim.SIMPLE_COLORSPACES:
# An optimization opportunity here, not currently taken, is directly
# generating a PNG from compressed data
pim.as_pil_image().save(png_name(root, xref))
return xref, '.png'
return None
def extract_images(pike, root, log, options, extract_fn):
"""Extract image using extract_fn
Enumerate images on each page, lookup their xref/ID number in the PDF.
Exclude images that are soft masks (i.e. alpha transparency related).
Record the page number on which an image is first used, since images may be
used on multiple pages (or multiple times on the same page).
Current we do not check Form XObjects or other objects that may contain
images, and we don't evaluate alternate images or thumbnails.
extract_fn must decide if wants to extract the image in this context. If
it does a tuple should be returned: (xref, ext) where .ext is the file
extension. extract_fn must also extract the file it finds interesting.
"""
include_xrefs = set()
exclude_xrefs = set()
pageno_for_xref = {}
errors = 0
for pageno, page in enumerate(pike.pages):
try:
xobjs = page.Resources.XObject
except AttributeError:
continue
for _imname, image in dict(xobjs).items():
if image.objgen[1] != 0:
continue # Ignore images in an incremental PDF
xref = image.objgen[0]
if hasattr(image, 'SMask'):
# Ignore soft masks
smask_xref = image.SMask.objgen[0]
exclude_xrefs.add(smask_xref)
include_xrefs.add(xref)
if xref not in pageno_for_xref:
pageno_for_xref[xref] = pageno
working_xrefs = include_xrefs - exclude_xrefs
for xref in working_xrefs:
image = pike.get_object((xref, 0))
try:
result = extract_fn(
pike=pike, root=root, log=log, image=image, xref=xref, options=options
)
except Exception as e:
log.debug("Image xref %s, error %s", xref, repr(e))
errors += 1
else:
if result:
_, ext = result
yield pageno_for_xref[xref], xref, ext
def extract_images_generic(pike, root, log, options):
"""Extract any >=2bpp image we think we can improve"""
jpegs = []
pngs = []
for _, xref, ext in extract_images(pike, root, log, options, extract_image_generic):
log.debug('xref = %s ext = %s', xref, ext)
if ext == '.png':
pngs.append(xref)
elif ext == '.jpg':
jpegs.append(xref)
log.debug("Optimizable images: JPEGs: %s PNGs: %s", len(jpegs), len(pngs))
return jpegs, pngs
def extract_images_jbig2(pike, root, log, options):
"""Extract any bitonal image that we think we can improve as JBIG2"""
jbig2_groups = defaultdict(list)
for pageno, xref, ext in extract_images(
pike, root, log, options, extract_image_jbig2
):
group = pageno // options.jbig2_page_group_size
jbig2_groups[group].append((xref, ext))
# Elide empty groups
jbig2_groups = {
group: xrefs for group, xrefs in jbig2_groups.items() if len(xrefs) > 0
}
log.debug("Optimizable images: JBIG2 groups: %s", (len(jbig2_groups),))
return jbig2_groups
def _produce_jbig2_images(jbig2_groups, root, log, options):
"""Produce JBIG2 images from their groups"""
def jbig2_group_futures(executor, root, groups):
for group, xref_exts in groups.items():
prefix = f'group{group:08d}'
future = executor.submit(
jbig2enc.convert_group,
cwd=fspath(root),
infiles=(img_name(root, xref, ext) for xref, ext in xref_exts),
out_prefix=prefix,
)
yield future
def jbig2_single_futures(executor, root, groups):
for group, xref_exts in groups.items():
prefix = f'group{group:08d}'
# Second loop is to ensure multiple images per page are unpacked
for n, xref_ext in enumerate(xref_exts):
xref, ext = xref_ext
future = executor.submit(
jbig2enc.convert_single,
cwd=fspath(root),
infile=img_name(root, xref, ext),
outfile=root / f'{prefix}.{n:04d}',
)
yield future
if options.jbig2_page_group_size > 1:
jbig2_futures = jbig2_group_futures
else:
jbig2_futures = jbig2_single_futures
with concurrent.futures.ThreadPoolExecutor(max_workers=options.jobs) as executor:
futures = jbig2_futures(executor, root, jbig2_groups)
with tqdm(
total=len(jbig2_groups),
desc="JBIG2",
unit='item',
disable=not options.progress_bar,
) as pbar:
for future in concurrent.futures.as_completed(futures):
proc = future.result()
if proc.stderr:
log.debug(proc.stderr.decode())
pbar.update()
def convert_to_jbig2(pike, jbig2_groups, root, log, options):
"""Convert images to JBIG2 and insert into PDF.
When the JBIG2 page group size is > 1 we do several JBIG2 images at once
and build a symbol dictionary that will span several pages. Each JBIG2
image must reference to its symbol dictionary. If too many pages shared the
same dictionary JBIG2 encoding becomes more expensive and less efficient.
The default value of 10 was determined through testing. Currently this
must be lossy encoding since jbig2enc does not support refinement coding.
When the JBIG2 symbolic coder is not used, each JBIG2 stands on its own
and needs no dictionary. Currently this must be lossless JBIG2.
"""
_produce_jbig2_images(jbig2_groups, root, log, options)
for group, xref_exts in jbig2_groups.items():
prefix = f'group{group:08d}'
jbig2_symfile = root / (prefix + '.sym')
if jbig2_symfile.exists():
jbig2_globals_data = jbig2_symfile.read_bytes()
jbig2_globals = pikepdf.Stream(pike, jbig2_globals_data)
jbig2_globals_dict = Dictionary(JBIG2Globals=jbig2_globals)
elif options.jbig2_page_group_size == 1:
jbig2_globals_dict = None
else:
raise FileNotFoundError(jbig2_symfile)
for n, xref_ext in enumerate(xref_exts):
xref, _ = xref_ext
jbig2_im_file = root / (prefix + f'.{n:04d}')
jbig2_im_data = jbig2_im_file.read_bytes()
im_obj = pike.get_object(xref, 0)
im_obj.write(
jbig2_im_data, filter=Name.JBIG2Decode, decode_parms=jbig2_globals_dict
)
def transcode_jpegs(pike, jpegs, root, log, options):
for xref in tqdm(
jpegs, desc="JPEGs", unit='image', disable=not options.progress_bar
):
in_jpg = Path(jpg_name(root, xref))
opt_jpg = in_jpg.with_suffix('.opt.jpg')
# This produces a debug warning from PIL
# DEBUG:PIL.Image:Error closing: 'NoneType' object has no attribute
# 'close'. Seems to be mostly harmless
# https://github.com/python-pillow/Pillow/issues/1144
with Image.open(fspath(in_jpg)) as im:
im.save(fspath(opt_jpg), optimize=True, quality=options.jpeg_quality)
if opt_jpg.stat().st_size > in_jpg.stat().st_size:
log.debug("xref %s, jpeg, made larger - skip", xref)
continue
compdata = leptonica.CompressedData.open(opt_jpg)
im_obj = pike.get_object(xref, 0)
im_obj.write(compdata.read(), filter=Name.DCTDecode)
def transcode_pngs(pike, images, image_name_fn, root, log, options):
modified = set()
if options.optimize >= 2:
png_quality = (
max(10, options.png_quality - 10),
min(100, options.png_quality + 10),
)
with concurrent.futures.ThreadPoolExecutor(
max_workers=options.jobs
) as executor:
futures = []
for xref in images:
log.debug(image_name_fn(root, xref))
futures.append(
executor.submit(
pngquant.quantize,
image_name_fn(root, xref),
png_name(root, xref),
png_quality[0],
png_quality[1],
)
)
modified.add(xref)
with tqdm(
desc="PNGs",
total=len(futures),
unit='image',
disable=not options.progress_bar,
) as pbar:
for _future in concurrent.futures.as_completed(futures):
pbar.update()
for xref in modified:
im_obj = pike.get_object(xref, 0)
try:
pix = leptonica.Pix.open(png_name(root, xref))
if pix.mode == '1':
compdata = pix.generate_pdf_ci_data(leptonica.lept.L_G4_ENCODE, 0)
else:
compdata = leptonica.CompressedData.open(png_name(root, xref))
except leptonica.LeptonicaError as e:
# Most likely this means file not found, i.e. quantize did not
# produce an improved version
log.error(e)
continue
# If re-coded image is larger don't use it - we test here because
# pngquant knows the size of the temporary output file but not the actual
# object in the PDF
if len(compdata) > int(im_obj.stream_dict.Length):
log.debug(
f"pngquant: pngquant did not improve over original image "
f"{len(compdata)} > {int(im_obj.stream_dict.Length)}"
)
continue
if compdata.type == leptonica.lept.L_FLATE_ENCODE:
return rewrite_png(pike, im_obj, compdata, log)
elif compdata.type == leptonica.lept.L_G4_ENCODE:
return rewrite_png_as_g4(pike, im_obj, compdata, log)
def rewrite_png_as_g4(pike, im_obj, compdata, log):
im_obj.BitsPerComponent = 1
im_obj.Width = compdata.w
im_obj.Height = compdata.h
im_obj.write(compdata.read())
log.debug(f"PNG to G4 {im_obj.objgen}")
if Name.Predictor in im_obj:
del im_obj.Predictor
if Name.DecodeParms in im_obj:
del im_obj.DecodeParms
im_obj.DecodeParms = Dictionary(
K=-1, BlackIs1=bool(compdata.minisblack), Columns=compdata.w
)
im_obj.Filter = Name.CCITTFaxDecode
return
def rewrite_png(pike, im_obj, compdata, log):
# When a PNG is inserted into a PDF, we more or less copy the IDAT section from
# the PDF and transfer the rest of the PNG headers to PDF image metadata.
# One thing we have to do is tell the PDF reader whether a predictor was used
# on the image before Flate encoding. (Typically one is.)
# According to Leptonica source, PDF readers don't actually need us
# to specify the correct predictor, they just need a value of either:
# 1 - no predictor
# 10-14 - there is a predictor
# Leptonica's compdata->predictor only tells TRUE or FALSE
# 10-14 means the actual predictor is specified in the data, so for any
# number >= 10 the PDF reader will use whatever the PNG data specifies.
# In practice Leptonica should use Paeth, 14, but 15 seems to be the
# designated value for "optimal". So we will use 15.
# See:
# - PDF RM 7.4.4.4 Table 10
# - https://github.com/DanBloomberg/leptonica/blob/master/src/pdfio2.c#L757
predictor = 15 if compdata.predictor > 0 else 1
dparms = Dictionary(Predictor=predictor)
if predictor > 1:
dparms.BitsPerComponent = compdata.bps # Yes, this is redundant
dparms.Colors = compdata.spp
dparms.Columns = compdata.w
im_obj.BitsPerComponent = compdata.bps
im_obj.Width = compdata.w
im_obj.Height = compdata.h
log.debug(
f"PNG {im_obj.objgen}: palette={compdata.ncolors} spp={compdata.spp} bps={compdata.bps}"
)
if compdata.ncolors > 0:
# .ncolors is the number of colors in the palette, not the number of
# colors used in a true color image. The palette string is always
# given as RGB tuples even when the image is grayscale; see
# https://github.com/DanBloomberg/leptonica/blob/master/src/colormap.c#L2067
palette_pdf_string = compdata.get_palette_pdf_string()
palette_data = pikepdf.Object.parse(palette_pdf_string)
palette_stream = pikepdf.Stream(pike, bytes(palette_data))
palette = [Name.Indexed, Name.DeviceRGB, compdata.ncolors - 1, palette_stream]
cs = palette
else:
# ncolors == 0 means we are using a colorspace without a palette
if compdata.spp == 1:
cs = Name.DeviceGray
elif compdata.spp == 3:
cs = Name.DeviceRGB
elif compdata.spp == 4:
cs = Name.DeviceCMYK
im_obj.ColorSpace = cs
im_obj.write(compdata.read(), filter=Name.FlateDecode, decode_parms=dparms)
def optimize(input_file, output_file, context, save_settings):
log = context.log
options = context.options
if options.optimize == 0:
safe_symlink(input_file, output_file)
return
if options.jpeg_quality == 0:
options.jpeg_quality = DEFAULT_JPEG_QUALITY if options.optimize < 3 else 40
if options.png_quality == 0:
options.png_quality = DEFAULT_PNG_QUALITY if options.optimize < 3 else 30
if options.jbig2_page_group_size == 0:
options.jbig2_page_group_size = 10 if options.jbig2_lossy else 1
with pikepdf.Pdf.open(input_file) as pike:
root = Path(output_file).parent / 'images'
root.mkdir(exist_ok=True)
jpegs, pngs = extract_images_generic(pike, root, log, options)
transcode_jpegs(pike, jpegs, root, log, options)
# if options.optimize >= 2:
# Try pngifying the jpegs
# transcode_pngs(pike, jpegs, jpg_name, root, log, options)
transcode_pngs(pike, pngs, png_name, root, log, options)
jbig2_groups = extract_images_jbig2(pike, root, log, options)
convert_to_jbig2(pike, jbig2_groups, root, log, options)
target_file = Path(output_file).with_suffix('.opt.pdf')
pike.remove_unreferenced_resources()
pike.save(target_file, **save_settings)
input_size = Path(input_file).stat().st_size
output_size = Path(target_file).stat().st_size
if output_size == 0:
raise OutputFileAccessError(
f"Output file not created after optimizing. We probably ran "
f"out of disk space in the temporary folder: {tempfile.gettempdir()}."
)
ratio = input_size / output_size
savings = 1 - output_size / input_size
log.info(f"Optimize ratio: {ratio:.2f} savings: {(100 * savings):.1f}%")
if savings < 0:
log.info("Image optimization did not improve the file - discarded")
# We still need to save the file
with pikepdf.open(input_file) as pike:
pike.remove_unreferenced_resources()
pike.save(output_file, **save_settings)
else:
safe_symlink(target_file, output_file)
def main(infile, outfile, level, jobs=1):
from tempfile import TemporaryDirectory
from shutil import copy
class OptimizeOptions:
"""Emulate ocrmypdf's options"""
def __init__(
self, input_file, jobs, optimize_, jpeg_quality, png_quality, jb2lossy
):
self.input_file = input_file
self.jobs = jobs
self.optimize = optimize_
self.jpeg_quality = jpeg_quality
self.png_quality = png_quality
self.jbig2_page_group_size = 0
self.jbig2_lossy = jb2lossy
self.quiet = True
self.progress_bar = False
options = OptimizeOptions(
input_file=infile,
jobs=jobs,
optimize_=int(level),
jpeg_quality=0, # Use default
png_quality=0,
jb2lossy=False,
)
with TemporaryDirectory() as td:
context = PDFContext(options, td, infile, None)
tmpout = Path(td) / 'out.pdf'
optimize(
infile,
tmpout,
context,
dict(
compress_streams=True,
preserve_pdfa=True,
object_stream_mode=pikepdf.ObjectStreamMode.generate,
),
)
copy(fspath(tmpout), fspath(outfile))
if __name__ == '__main__':
main(sys.argv[1], sys.argv[2], sys.argv[3])