Metadata-Version: 2.1 Name: img2pdf Version: 0.3.2 Summary: Convert images to PDF via direct JPEG inclusion. Home-page: https://gitlab.mister-muffin.de/josch/img2pdf Author: Johannes 'josch' Schauer Author-email: josch@mister-muffin.de License: LGPL Download-URL: https://gitlab.mister-muffin.de/josch/img2pdf/repository/archive.tar.gz?ref=0.3.2 Description: img2pdf ======= Lossless conversion of raster images to PDF. You should use img2pdf if your priorities are (in this order): 1. **always lossless**: the image embedded in the PDF will always have the exact same color information for every pixel as the input 2. **small**: if possible, the difference in filesize between the input image and the output PDF will only be the overhead of the PDF container itself 3. **fast**: if possible, the input image is just pasted into the PDF document as-is without any CPU hungry re-encoding of the pixel data Conventional conversion software (like ImageMagick) would either: 1. not be lossless because lossy re-encoding to JPEG 2. not be small because using wasteful flate encoding of raw pixel data 3. not be fast because input data gets re-encoded Another advantage of not having to re-encode the input (in most common situations) is, that img2pdf is able to handle much larger input than other software, because the raw pixel data never has to be loaded into memory. The following table shows how img2pdf handles different input depending on the input file format and image color space. | Format | Colorspace | Result | | -------------------- | ------------------------------ | ------------- | | JPEG | any | direct | | JPEG2000 | any | direct | | PNG (non-interlaced) | any | direct | | TIFF (CCITT Group 4) | monochrome | direct | | any | any except CMYK and monochrome | PNG Paeth | | any | monochrome | CCITT Group 4 | | any | CMYK | flate | For JPEG, JPEG2000, non-interlaced PNG and TIFF images with CCITT Group 4 encoded data, img2pdf directly embeds the image data into the PDF without re-encoding it. It thus treats the PDF format merely as a container format for the image data. In these cases, img2pdf only increases the filesize by the size of the PDF container (typically around 500 to 700 bytes). Since data is only copied and not re-encoded, img2pdf is also typically faster than other solutions for these input formats. For all other input types, img2pdf first has to transform the pixel data to make it compatible with PDF. In most cases, the PNG Paeth filter is applied to the pixel data. For monochrome input, CCITT Group 4 is used instead. Only for CMYK input no filter is applied before finally applying flate compression. Usage ----- The images must be provided as files because img2pdf needs to seek in the file descriptor. If no output file is specified with the `-o`/`--output` option, output will be done to stdout. A typical invocation is: $ img2pdf img1.png img2.jpg -o out.pdf The detailed documentation can be accessed by running: $ img2pdf --help Bugs ---- - If you find a JPEG, JPEG2000, PNG or CCITT Group 4 encoded TIFF file that, when embedded into the PDF cannot be read by the Adobe Acrobat Reader, please contact me. - I have not yet figured out how to determine the colorspace of JPEG2000 files. Therefore JPEG2000 files use DeviceRGB by default. For JPEG2000 files with other colorspaces, you must explicitly specify it using the `--colorspace` option. - Input images with alpha channels are not allowed. PDF doesn't support alpha channels in images and thus, the alpha channel of the input would have to be discarded. But img2pdf will always be lossless and thus, input images must not carry transparency information. - img2pdf uses PIL (or Pillow) to obtain image meta data and to convert the input if necessary. To prevent decompression bomb denial of service attacks, Pillow limits the maximum number of pixels an input image is allowed to have. If you are sure that you know what you are doing, then you can disable this safeguard by passing the `--pillow-limit-break` option to img2pdf. This allows one to process even very large input images. Installation ------------ On a Debian- and Ubuntu-based systems, img2pdf can be installed from the official repositories: $ apt install img2pdf If you want to install it using pip, you can run: $ pip3 install img2pdf If you prefer to install from source code use: $ cd img2pdf/ $ pip3 install . To test the console script without installing the package on your system, use virtualenv: $ cd img2pdf/ $ virtualenv ve $ ve/bin/pip3 install . You can then test the converter using: $ ve/bin/img2pdf -o test.pdf src/tests/test.jpg The package can also be used as a library: import img2pdf # opening from filename with open("name.pdf","wb") as f: f.write(img2pdf.convert('test.jpg')) # opening from file handle with open("name.pdf","wb") as f1, open("test.jpg") as f2: f1.write(img2pdf.convert(f2)) # using in-memory image data with open("name.pdf","wb") as f: f.write(img2pdf.convert("\x89PNG...") # multiple inputs (variant 1) with open("name.pdf","wb") as f: f.write(img2pdf.convert("test1.jpg", "test2.png")) # multiple inputs (variant 2) with open("name.pdf","wb") as f: f.write(img2pdf.convert(["test1.jpg", "test2.png"])) # writing to file descriptor with open("name.pdf","wb") as f1, open("test.jpg") as f2: img2pdf.convert(f2, outputstream=f1) # specify paper size (A4) a4inpt = (img2pdf.mm_to_pt(210),img2pdf.mm_to_pt(297)) layout_fun = img2pdf.get_layout_fun(a4inpt) with open("name.pdf","wb") as f: f.write(img2pdf.convert('test.jpg', layout_fun=layout_fun)) Comparison to ImageMagick ------------------------- Create a large test image: $ convert logo: -resize 8000x original.jpg Convert it into PDF using ImageMagick and img2pdf: $ time img2pdf original.jpg -o img2pdf.pdf $ time convert original.jpg imagemagick.pdf Notice how ImageMagick took an order of magnitude longer to do the conversion than img2pdf. It also used twice the memory. Now extract the image data from both PDF documents and compare it to the original: $ pdfimages -all img2pdf.pdf tmp $ compare -metric AE original.jpg tmp-000.jpg null: 0 $ pdfimages -all imagemagick.pdf tmp $ compare -metric AE original.jpg tmp-000.jpg null: 118716 To get lossless output with ImageMagick we can use Zip compression but that unnecessarily increases the size of the output: $ convert original.jpg -compress Zip imagemagick.pdf $ pdfimages -all imagemagick.pdf tmp $ compare -metric AE original.jpg tmp-000.png null: 0 $ stat --format="%s %n" original.jpg img2pdf.pdf imagemagick.pdf 1535837 original.jpg 1536683 img2pdf.pdf 9397809 imagemagick.pdf Comparison to pdfLaTeX ---------------------- pdfLaTeX performs a lossless conversion from included images to PDF by default. If the input is a JPEG, then it simply embeds the JPEG into the PDF in the same way as img2pdf does it. But for other image formats it uses flate compression of the plain pixel data and thus needlessly increases the output file size: $ convert logo: -resize 8000x original.png $ cat << END > pdflatex.tex \documentclass{article} \usepackage{graphicx} \begin{document} \includegraphics{original.png} \end{document} END $ pdflatex pdflatex.tex $ stat --format="%s %n" original.png pdflatex.pdf 4500182 original.png 9318120 pdflatex.pdf Comparison to Tesseract OCR --------------------------- Tesseract OCR comes closest to the functionality img2pdf provides. It is able to convert JPEG and PNG input to PDF without needlessly increasing the filesize and is at the same time lossless. So if your input is JPEG and PNG images, then you should safely be able to use Tesseract instead of img2pdf. For other input, Tesseract might not do a lossless conversion. For example it converts CMYK input to RGB and removes the alpha channel from images with transparency. For multipage TIFF or animated GIF, it will only convert the first frame. Keywords: jpeg pdf converter Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Other Audience Classifier: Environment :: Console Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: Implementation :: CPython Classifier: Programming Language :: Python :: Implementation :: PyPy Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3) Classifier: Natural Language :: English Classifier: Operating System :: OS Independent Provides-Extra: test