optimize: solve monochrome by converting to G4
This commit is contained in:
James R. Barlow
+78
-60
@@ -384,7 +384,11 @@ def transcode_pngs(pike, images, image_name_fn, root, log, options):
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for xref in modified:
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im_obj = pike.get_object(xref, 0)
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try:
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compdata = leptonica.CompressedData.open(png_name(root, xref))
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pix = leptonica.Pix.open(png_name(root, xref))
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if pix.mode == '1':
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compdata = pix.generate_pdf_ci_data(leptonica.lept.L_G4_ENCODE, 0)
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else:
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compdata = leptonica.CompressedData.open(png_name(root, xref))
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except leptonica.LeptonicaError as e:
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# Most likely this means file not found, i.e. quantize did not
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# produce an improved version
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@@ -400,69 +404,83 @@ def transcode_pngs(pike, images, image_name_fn, root, log, options):
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f"{len(compdata)} > {int(im_obj.stream_dict.Length)}"
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)
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continue
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if compdata.type == leptonica.lept.L_FLATE_ENCODE:
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return rewrite_png(pike, im_obj, compdata, log)
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elif compdata.type == leptonica.lept.L_G4_ENCODE:
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return rewrite_png_as_g4(pike, im_obj, compdata, log)
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if compdata.bps == 1:
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# Discard 1bpp images due to issues with preserving the photometric
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# interpretation. In particular Leptonica changed behavior in
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# version 1.77.0, such that it transcodes 1bpp.
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log.debug(f"discarded optimized image {xref} because it was 1bpp")
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continue
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# When a PNG is inserted into a PDF, we more or less copy the IDAT section from
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# the PDF and transfer the rest of the PNG headers to PDF image metadata.
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# One thing we have to do is tell the PDF reader whether a predictor was used
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# on the image before Flate encoding. (Typically one is.)
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# According to Leptonica source, PDF readers don't actually need us
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# to specify the correct predictor, they just need a value of either:
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# 1 - no predictor
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# 10-14 - there is a predictor
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# Leptonica's compdata->predictor only tells TRUE or FALSE
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# 10-14 means the actual predictor is specified in the data, so for any
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# number >= 10 the PDF reader will use whatever the PNG data specifies.
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# In practice Leptonica should use Paeth, 14, but 15 seems to be the
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# designated value for "optimal". So we will use 15.
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# See:
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# - PDF RM 7.4.4.4 Table 10
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# - https://github.com/DanBloomberg/leptonica/blob/master/src/pdfio2.c#L757
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predictor = 15 if compdata.predictor > 0 else 1
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dparms = Dictionary(Predictor=predictor)
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if predictor > 1:
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dparms.BitsPerComponent = compdata.bps # Yes, this is redundant
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dparms.Colors = compdata.spp
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dparms.Columns = compdata.w
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def rewrite_png_as_g4(pike, im_obj, compdata, log):
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im_obj.BitsPerComponent = 1
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im_obj.Width = compdata.w
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im_obj.Height = compdata.h
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im_obj.BitsPerComponent = compdata.bps
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im_obj.Width = compdata.w
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im_obj.Height = compdata.h
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im_obj.write(compdata.read())
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log.debug(
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f"PNG {xref}: palette={compdata.ncolors} spp={compdata.spp} bps={compdata.bps}"
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)
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if compdata.ncolors > 0:
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# .ncolors is the number of colors in the palette, not the number of
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# colors used in a true color image. The palette string is always
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# given as RGB tuples even when the image is grayscale; see
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# https://github.com/DanBloomberg/leptonica/blob/master/src/colormap.c#L2067
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palette_pdf_string = compdata.get_palette_pdf_string()
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palette_data = pikepdf.Object.parse(palette_pdf_string)
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palette_stream = pikepdf.Stream(pike, bytes(palette_data))
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palette = [
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Name.Indexed,
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Name.DeviceRGB,
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compdata.ncolors - 1,
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palette_stream,
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]
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cs = palette
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else:
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# ncolors == 0 means we are using a colorspace without a palette
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if compdata.spp == 1:
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cs = Name.DeviceGray
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elif compdata.spp == 3:
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cs = Name.DeviceRGB
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elif compdata.spp == 4:
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cs = Name.DeviceCMYK
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im_obj.ColorSpace = cs
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im_obj.write(compdata.read(), filter=Name.FlateDecode, decode_parms=dparms)
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log.debug(f"PNG to G4 {im_obj.objgen}")
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if Name.Predictor in im_obj:
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del im_obj.Predictor
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if Name.DecodeParms in im_obj:
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del im_obj.DecodeParms
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im_obj.DecodeParms = Dictionary(
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K=-1, BlackIs1=bool(compdata.minisblack), Columns=compdata.w
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)
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im_obj.Filter = Name.CCITTFaxDecode
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return
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def rewrite_png(pike, im_obj, compdata, log):
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# When a PNG is inserted into a PDF, we more or less copy the IDAT section from
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# the PDF and transfer the rest of the PNG headers to PDF image metadata.
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# One thing we have to do is tell the PDF reader whether a predictor was used
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# on the image before Flate encoding. (Typically one is.)
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# According to Leptonica source, PDF readers don't actually need us
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# to specify the correct predictor, they just need a value of either:
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# 1 - no predictor
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# 10-14 - there is a predictor
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# Leptonica's compdata->predictor only tells TRUE or FALSE
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# 10-14 means the actual predictor is specified in the data, so for any
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# number >= 10 the PDF reader will use whatever the PNG data specifies.
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# In practice Leptonica should use Paeth, 14, but 15 seems to be the
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# designated value for "optimal". So we will use 15.
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# See:
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# - PDF RM 7.4.4.4 Table 10
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# - https://github.com/DanBloomberg/leptonica/blob/master/src/pdfio2.c#L757
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predictor = 15 if compdata.predictor > 0 else 1
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dparms = Dictionary(Predictor=predictor)
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if predictor > 1:
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dparms.BitsPerComponent = compdata.bps # Yes, this is redundant
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dparms.Colors = compdata.spp
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dparms.Columns = compdata.w
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im_obj.BitsPerComponent = compdata.bps
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im_obj.Width = compdata.w
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im_obj.Height = compdata.h
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log.debug(
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f"PNG {im_obj.objgen}: palette={compdata.ncolors} spp={compdata.spp} bps={compdata.bps}"
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)
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if compdata.ncolors > 0:
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# .ncolors is the number of colors in the palette, not the number of
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# colors used in a true color image. The palette string is always
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# given as RGB tuples even when the image is grayscale; see
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# https://github.com/DanBloomberg/leptonica/blob/master/src/colormap.c#L2067
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palette_pdf_string = compdata.get_palette_pdf_string()
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palette_data = pikepdf.Object.parse(palette_pdf_string)
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palette_stream = pikepdf.Stream(pike, bytes(palette_data))
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palette = [Name.Indexed, Name.DeviceRGB, compdata.ncolors - 1, palette_stream]
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cs = palette
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else:
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# ncolors == 0 means we are using a colorspace without a palette
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if compdata.spp == 1:
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cs = Name.DeviceGray
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elif compdata.spp == 3:
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cs = Name.DeviceRGB
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elif compdata.spp == 4:
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cs = Name.DeviceCMYK
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im_obj.ColorSpace = cs
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im_obj.write(compdata.read(), filter=Name.FlateDecode, decode_parms=dparms)
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def optimize(input_file, output_file, context, save_settings):
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