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PyLibTiff for Windows 7 - Professional TIFF editor and viewer - PyLibTiff - Windows 7 Download

PyLibTiff Windows 7

PyLibTiff 0.1

"Enhance your image processing with PyLibTiff - a high-performance library for Windows 7."

Are you tired of slow and inefficient TIFF file handling? Look no further than PyLibTiff! Developed by the esteemed Pearu Peterson, PyLibTiff offers lightning-fast performance and comprehensive support for all your TIFF manipulation needs. Whether you need to read, write, or convert TIFF files, PyLibTiff has got you covered. Say goodbye to frustration and hello to streamlined efficiency with PyLibTiff. Download now!

PyLibTiff 0.1 full details

File Size: 205 kB
License: Open Source
Price: FREE
Released: 2012-02-18
Downloads: Total: 311 | This Month: 28
Publisher: Pearu Peterson
Publisher URL: http://code.google.com/p/pylibtiff/


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PyLibTiffComponents & LibrariesWindows XP, Windows Vista, Windows 7

User Rating: 3.4 (13 votes)

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PyLibTiff windows 7 compatible

PyLibTiff 0.1 full description

PyLibTiff is a package that provides a wrapper to the libtiff library to Python using ctypes and a pure Python module for reading and writing TIFF and LSM files.

PyLibTiff is a package that provides:

* a wrapper to the libtiff library to Python using ctypes.
* a pure Python module for reading and writing TIFF and LSM files. The images are read as numpy.memmap objects so that it is possible to open images that otherwise would not fit to computers RAM.

There exists many Python packages such as PIL, FreeImagePy that support reading and writing TIFF files. The PyLibTiff project was started to have an efficient and direct way to read and write TIFF files using the libtiff library without the need to install any unnecessary packages or libraries. The pure Python module was created for reading "broken" TIFF files such as LSM files that in some places use different interpretation of TIFF tags than what specified in the TIFF specification document. The libtiff library would just fail reading such files. In addition, the pure Python module is more memory efficient as the arrays are returned as memory maps. Support for compressed files is not implemented yet.

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