ó P'—^c@sśddlmZddlmZddlmZmZmZmZde fd„ƒYZ e j d„Z d„Z d e fd „ƒYZd e fd „ƒYZd e fd„ƒYZdS(i(tAnchor(thistogram_entropyi(tImaget ImageChopst ImageDrawt ImageStattSidecBs2eZdZdZdZdZeeeefZRS(tttrtbtl(t__name__t __module__tTOPtRIGHTtBOTTOMtLEFTtALL(((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyRs cCs‘tj|kr|dndtj|kr5|dndtj|krQ|dn |jdtj|krt|dn |jdf}|j|ƒS(Niiii(RRR RtsizeRtcrop(timgtbboxtsides((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyt_crops #)cCsŁtjd|jdƒ}|jdd|jdd}}|dkr|dkrtj|ƒ}|jdd||gdƒntj|jdƒj |ƒƒj S(Nt1iiitRGBA( RtnewRRtDrawt rectangleRtStattconvertt histogramtmedian(Rtmasktwthtdraw((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pytdetect_border_colors #tTrimBorderColorcBs,eZdZddejd„Zd„ZRS(s/Trims a color from the sides of an image. g333333Ó?cCs||_||_||_dS(s :param color: The color to trim from the image, in a 4-tuple RGBA value, where each component is an integer between 0 and 255, inclusive. If no color is provided, the processor will attempt to detect the border color automatically. :param tolerance: A number between 0 and 1 where 0. Zero is the least tolerant and one is the most. :param sides: A list of sides that should be trimmed. Possible values are provided by the :class:`Side` enum class. N(tcolorRt tolerance(tselfR'R(R((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyt__init__%s  cCs|jdƒ}|jp'tt|ƒƒ}tjd|j|ƒ}tj||ƒ}|j dkrŐd|j ko}dkns˜t d|j ƒ‚ntj |t |j dƒƒjdƒ}tj ||ƒ}n|jƒ}|r˙t|||jƒ}n|S(NRiisN%s is an invalid tolerance. Acceptable values are between 0 and 1 (inclusive).i˙(ii(RR'ttupleR%RRRRt differenceR(t ValueErrortconstanttinttsubtracttgetbboxRR(R)Rtsourcet border_colortbgtdiffttmpR((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pytprocess5s  N(R R t__doc__tNoneRRR*R7(((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR&!stCropcBs/eZdZdddddd„Zd„ZRS(s Crops an image, cropping it to the specified width and height. You may optionally provide either an anchor or x and y coordinates. This processor functions exactly the same as ``ResizeCanvas`` except that it will never enlarge the image. cCs1||_||_||_||_||_dS(N(twidththeighttanchortxty(R)R;R<R=R>R?((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR*Ts     c Csuddlm}|j\}}t||jƒt||jƒ}}|||d|jd|jd|jƒj |ƒS(Ni(t ResizeCanvasR=R>R?( tresizeR@RtminR;R<R=R>R?R7(R)RR@toriginal_widthtoriginal_heightt new_widtht new_height((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR7[s N(R R R8R9R*R7(((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR:Kst SmartCropcBs/eZdZddd„Zd„Zd„ZRS(s Crop an image to the specified dimensions, whittling away the parts of the image with the least entropy. Based on smart crop implementation from easy-thumbnails: https://github.com/SmileyChris/easy-thumbnails/blob/master/easy_thumbnails/processors.py#L193 cCs||_||_dS(sr :param width: The target width, in pixels. :param height: The target height, in pixels. N(R;R<(R)R;R<((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR*ps cCsŽt|ƒ}t|ƒ}|rjt||dƒdkrj||dkrR||fS|d}|||fS||kr€d|fS|dfSdS(sŰ Calculate the entropy of two slices (from the start and end of an axis), returning a tuple containing the amount that should be added to the start and removed from the end of the axis. ig{ŽGáz„?iiN(Rtabs(R)t start_slicet end_slicetsliceR,t start_entropyt end_entropyt half_slice((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pytcompare_entropyys       cCsŃ|j\}}t|t||jƒƒ}t|t||jƒƒ}d}}||}} x¤|rt|t|ddƒƒ} |j|d|| |fƒ} |j|| d||fƒ} |j| | | |ƒ\} }|| 7}||8}|| |}qaWx¤|rŤt|t|ddƒƒ} |jd|||| fƒ} |jd| | || fƒ} |j| | | |ƒ\} }|| 7}| |8} || |}qW|||| f}|j|ƒ}|S(Niii (RR/RBR;R<tmaxRRO(R)Rtsource_xtsource_ytdiff_xtdiff_ytleftttoptrighttbottomRKtstarttendtaddtremovetbox((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyR7s0        N(R R R8R9R*ROR7(((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyRGfs N(tbaseRtutilsRtlibRRRRtobjectRRRR%R&R:RG(((s8/tmp/pip-unpacked-wheel-gNgxnH/pilkit/processors/crop.pyts" *