Don't let people run with a mostly broken Pillow. "The _imaging extension was built for another version of Python.",Įlif str( v). # The _imaging C module is present, but not compiled for # Explanations for ways that we know we might have an import error
_util import DeferredError, is_pathĬategories = \n"Ĭore = DeferredError( ImportError( "The _imaging C module is not installed.")) import ImageMode, TiffTags, UnidentifiedImageError, _version_, _pluginsįrom.
# PILLOW_VERSION was removed in Pillow 9.0.0.įrom. # See the README file for information on usage and redistribution.įrom collections. # Copyright (c) 1995-2009 by Fredrik Lundh. # Copyright (c) 1997-2009 by Secret Labs AB. And the string manipulation methods discussed here are quite handy in such tasks._getattr_ Function DecompressionBombWarning Class DecompressionBombError Class isImageType Function Transpose Class Transform Class Resampling Class Dither Class Palette Class Quantize Class _conv_type_shape Function getmodebase Function getmodetype Function getmodebandnames Function getmodebands Function preinit Function init Function _getdecoder Function _getencoder Function coerce_e Function _E Class _init_ Function _neg_ Function _add_ Function _sub_ Function _rsub_ Function _mul_ Function _truediv_ Function _getscaleoffset Function Image Class _init_ Function _getattr_ Function width Function height Function size Function _new Function _enter_ Function _exit_ Function close Function _copy Function _ensure_mutable Function _dump Function _eq_ Function _repr_ Function _repr_pretty_ Function _repr_png_ Function _array_interface_ Function _getstate_ Function _setstate_ Function tobytes Function tobitmap Function frombytes Function load Function verify Function convert Function convert_transparency Function quantize Function copy Function crop Function _crop Function draft Function _expand Function filter Function getbands Function getbbox Function getcolors Function getdata Function getextrema Function _getxmp Function get_name Function get_value Function getexif Function _reload_exif Function getim Function getpalette Function apply_transparency Function getpixel Function getprojection Function histogram Function entropy Function paste Function alpha_composite Function point Function putalpha Function putdata Function putpalette Function putpixel Function remap_palette Function _get_safe_box Function resize Function reduce Function rotate Function transform Function save Function seek Function show Function split Function getchannel Function tell Function thumbnail Function round_aspect Function transform Function _transformer Function transpose Function effect_spread Function toqimage Function toqpixmap Function ImagePointHandler Class ImageTransformHandler Class _wedge Function _check_size Function new Function frombytes Function frombuffer Function fromarray Function fromqimage Function fromqpixmap Function _decompression_bomb_check Function open Function _open_core Function alpha_composite Function blend Function composite Function eval Function merge Function register_open Function register_mime Function register_save Function register_save_all Function register_extension Function register_extensions Function registered_extensions Function register_decoder Function register_encoder Function _show Function effect_mandelbrot Function effect_noise Function linear_gradient Function radial_gradient Function _apply_env_variables Function Exif Class _init_ Function _fixup Function _fixup_dict Function _get_ifd_dict Function _get_head Function load Function load_from_fp Function _get_merged_dict Function tobytes Function get_ifd Function _str_ Function _len_ Function _getitem_ Function _contains_ Function _setitem_ Function _delitem_ Function _iter_ Function In my project, a lot of information is also hidden in the image name. I usually do the below processes on image: 1. And only Python can help me with this batch processing. In my recent project, I need to process 10000+ images per day and extract the data from them. 📌 More resources are always mentioned with 💡
📌 Want to follow along? here is my Jupyter-Notebook. Additionally, here you will find a classic comparison of the speed of two image processing libraries - OpenCV and PIL This story is all about different types of image feature extraction using Python. The work of a Data Analyst is not limited to work only on readily available data, rather sometimes the data need to be mined from the images also.
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