h,DSSKJr SSKrSSKrSSKJr SSKrSSKr SSK r SSK r SSK J r /SQr"SS\5r"SS \5r"S S \5r"S S \5r"SS\5r"SS\5r"SS\5r"SS\5r"SS\5rg!\a SrNf=f))divisionN)Image) functional) ComposeToTensor ToPILImage NormalizeRandomHorizontalFlipLambdaRandomResizedCrop ColorJitterRandomRotationc$\rSrSrSrSrSrSrg)rzComposes several transforms together. Args: transforms (list of ``Transform`` objects): list of transforms to compose. Example: >>> transforms.Compose([ >>> transforms.CenterCrop(10), >>> transforms.ToTensor(), >>> ]) cXlgN transforms)selfrs V/var/www/fran/franai/plugins/Silent-Face-Anti-Spoofing-master/src/data_io/transform.py__init__Compose.__init__'s$c<URH nU"U5nM U$rr)rimgts r__call__Compose.__call__*sAC&C! rrN__name__ __module__ __qualname____firstlineno____doc__rr__static_attributes__rrrrs %rrc\rSrSrSrSrSrg)r0zConvert a ``PIL Image`` or ``numpy.ndarray`` to tensor. Converts a PIL Image or numpy.ndarray (H x W x C) in the range [0, 255] to a torch.FloatTensor of shape (C x H x W) in the range [0.0, 1.0]. c.[R"U5$)zu Args: pic (PIL Image or numpy.ndarray): Image to be converted to tensor. Returns: Tensor: Converted image. )F to_tensorrpics rrToTensor.__call__8s{{3rr&Nr r!r"r#r$rr%r&rrrr0s   rrc$\rSrSrSrSrSrSrg)r CzsApply a user-defined lambda as a transform. Args: lambd (function): Lambda/function to be used for transform. cR[U[R5(deXlgr) isinstancetypes LambdaTypelambd)rr6s rrLambda.__init__Js %!1!12222 rc$URU5$rr6rrs rrLambda.__call__Nszz#rr9Nrr&rrr r Cs rr c(\rSrSrSrSSjrSrSrg)rRaConvert a tensor or an ndarray to PIL Image. Converts a torch.*Tensor of shape C x H x W or a numpy ndarray of shape H x W x C to a PIL Image while preserving the value range. Args: mode (`PIL.Image mode`_): color space and pixel depth of input data (optional). If ``mode`` is ``None`` (default) there are some assumptions made about the input data: 1. If the input has 3 channels, the ``mode`` is assumed to be ``RGB``. 2. If the input has 4 channels, the ``mode`` is assumed to be ``RGBA``. 3. If the input has 1 channel, the ``mode`` is determined by the data type (i,e, ``int``, ``float``, ``short``). .. _PIL.Image mode: http://pillow.readthedocs.io/en/3.4.x/handbook/concepts.html#modes NcXlgrmode)rr@s rrToPILImage.__init__bs rcB[R"XR5$)z Args: pic (Tensor or numpy.ndarray): Image to be converted to PIL Image. Returns: PIL Image: Image converted to PIL Image. )r* to_pil_imager@r,s rrToPILImage.__call__es~~c99--rr?rrr&rrrrRs .rrc$\rSrSrSrSrSrSrg)r qaNormalize an tensor image with mean and standard deviation. Given mean: ``(M1,...,Mn)`` and std: ``(S1,..,Sn)`` for ``n`` channels, this transform will normalize each channel of the input ``torch.*Tensor`` i.e. ``input[channel] = (input[channel] - mean[channel]) / std[channel]`` Args: mean (sequence): Sequence of means for each channel. std (sequence): Sequence of standard deviations for each channel. cXlX lgrmeanstd)rrIrJs rrNormalize.__init__|s  rcX[R"XRUR5$)z| Args: tensor (Tensor): Tensor image of size (C, H, W) to be normalized. Returns: Tensor: Normalized Tensor image. )r* normalizerIrJ)rtensors rrNormalize.__call__s{{699dhh77rrHNrr&rrr r qs8rr c\rSrSrSrSrSrg)r zIHorizontally flip the given PIL Image randomly with a probability of 0.5.cd[R"5S:a[R"U5$U$)zb Args: img (PIL Image): Image to be flipped. Returns: PIL Image: Randomly flipped image. ?)randomr*hflipr:s rrRandomHorizontalFlip.__call__s% ==?S 773<  rr&Nr/r&rrr r s S rr cR\rSrSrSrSS\R 4Sjr\S5r Sr Sr g ) r aCrop the given PIL Image to random size and aspect ratio. A crop of random size (default: of 0.08 to 1.0) of the original size and a random aspect ratio (default: of 3/4 to 4/3) of the original aspect ratio is made. This crop is finally resized to given size. This is popularly used to train the Inception networks. Args: size: expected output size of each edge scale: range of size of the origin size cropped ratio: range of aspect ratio of the origin aspect ratio cropped interpolation: Default: PIL.Image.BILINEAR )g{Gz?g?)g?gUUUUUU?cp[U[5(aXlOX4UlX@lX lX0lgr)r3tuplesize interpolationscaleratio)rr[r]r^r\s rrRandomResizedCrop.__init__s- dE " "I DI*  rc 2[S5GH4nURSURS-n[R"U6U-n[R"U6n[ [ [ R"XV-555n[ [ [ R"XV- 555n[R"5S:aXpXpRS::dMXRS::dM[R"SURSU- 5n [R"SURSU- 5n XX4s $ [URSURS5nURSU- S-n URSU- S-n XXw4$)aQGet parameters for ``crop`` for a random sized crop. Args: img (PIL Image): Image to be cropped. scale (tuple): range of size of the origin size cropped ratio (tuple): range of aspect ratio of the origin aspect ratio cropped Returns: tuple: params (i, j, h, w) to be passed to ``crop`` for a random sized crop. rrS) ranger[rTuniformintroundmathsqrtrandintmin) rr]r^attemptarea target_area aspect_ratiowhijs r get_paramsRandomResizedCrop.get_paramssGRyG88A;!,D ..%047K!>>51LE$))K$>?@AAE$))K$>?@AA}}$1HHQKA!$4NN1chhqkAo6NN1chhqkAo6Qz!!"  SXXa[ ) XXa[1_ " XXa[1_ "Qzrc URXRUR5up#pE[R"XX4XPR UR 5$)zm Args: img (PIL Image): Image to be flipped. Returns: PIL Image: Randomly cropped and resize image. )rtr]r^r* resized_cropr[r\)rrrrrsrqrps rrRandomResizedCrop.__call__s?__S**djjA a~~caAyy$:L:LMMr)r\r^r]r[N) r r!r"r#r$rBILINEARr staticmethodrtrr%r&rrr r s8 $/6HX]XfXf  D Nrr c8\rSrSrSrSSjr\S5rSrSr g) r ayRandomly change the brightness, contrast and saturation of an image. Args: brightness (float): How much to jitter brightness. brightness_factor is chosen uniformly from [max(0, 1 - brightness), 1 + brightness]. contrast (float): How much to jitter contrast. contrast_factor is chosen uniformly from [max(0, 1 - contrast), 1 + contrast]. saturation (float): How much to jitter saturation. saturation_factor is chosen uniformly from [max(0, 1 - saturation), 1 + saturation]. hue(float): How much to jitter hue. hue_factor is chosen uniformly from [-hue, hue]. Should be >=0 and <= 0.5. c4XlX lX0lX@lgr) brightnesscontrast saturationhue)rr~rrrs rrColorJitter.__init__s$ $rc^^^^ /nUS:aN[RR[SSU- 5SU-5mUR [ U4Sj55 US:aN[RR[SSU- 5SU-5mUR [ U4Sj55 US:aN[RR[SSU- 5SU-5m UR [ U 4Sj55 US:a?[RRU*U5mUR [ U4Sj55 [RR U5 [U5nU$)zGet a randomized transform to be applied on image. Arguments are same as that of __init__. Returns: Transform which randomly adjusts brightness, contrast and saturation in a random order. rrbc2>[R"UT5$r)r*adjust_brightness)rbrightness_factors r(ColorJitter.get_params..1D1DSJ[1\rc2>[R"UT5$r)r*adjust_contrast)rcontrast_factors rrrs1B1B31Xrc2>[R"UT5$r)r*adjust_saturation)rsaturation_factors rrr rrc2>[R"UT5$r)r* adjust_hue)r hue_factors rrrsc:1Nr)nprTremaxappendr shuffler) r~rrrr transformrrrrs @@@@rrtColorJitter.get_paramss! > " 1 1#aZ2H!j. Y    f%\] ^ a< ii//Aq8|0Da(lSO   f%XY Z > " 1 1#aZ2H!j. Y    f%\] ^ 7**C45J   f%NO P *%J' rcURURURURUR5nU"U5$)zX Args: img (PIL Image): Input image. Returns: PIL Image: Color jittered image. )rtr~rrr)rrrs rrColorJitter.__call__s5OODOOT]]$(OOTXX? ~r)r~rrrN)rrrr r r!r"r#r$rrzrtrr%r&rrr r s%  > rr c8\rSrSrSrSSjr\S5rSrSr g) ri"aRotate the image by angle. Args: degrees (sequence or float or int): Range of degrees to select from. If degrees is a number instead of sequence like (min, max), the range of degrees will be (-degrees, +degrees). resample ({PIL.Image.NEAREST, PIL.Image.BILINEAR, PIL.Image.BICUBIC}, optional): An optional resampling filter. See http://pillow.readthedocs.io/en/3.4.x/handbook/concepts.html#filters If omitted, or if the image has mode "1" or "P", it is set to PIL.Image.NEAREST. expand (bool, optional): Optional expansion flag. If true, expands the output to make it large enough to hold the entire rotated image. If false or omitted, make the output image the same size as the input image. Note that the expand flag assumes rotation around the center and no translation. center (2-tuple, optional): Optional center of rotation. Origin is the upper left corner. Default is the center of the image. Nc[U[R5(aUS:a [S5eU*U4UlO [ U5S:wa [S5eXlX lX0lX@lg)Nrz3If degrees is a single number, it must be positive.rcz.If degrees is a sequence, it must be of len 2.) r3numbersNumber ValueErrordegreeslenresampleexpandcenter)rrrrrs rrRandomRotation.__init__6s` gw~~ . .{ !VWW$Hg.DL7|q  !QRR"L   rcR[RRUSUS5nU$)zGet parameters for ``rotate`` for a random rotation. Returns: sequence: params to be passed to ``rotate`` for random rotation. rrb)rrTre)rangles rrtRandomRotation.get_paramsDs' !!'!*gaj9 rcURUR5n[R"XURUR UR 5$)zS img (PIL Image): Image to be rotated. Returns: PIL Image: Rotated image. )rtrr*rotaterrr)rrrs rrRandomRotation.__call__Os7 -xxDMM4;; LLr)rrrr)FFNrr&rrrr"s&&  Mrr) __future__rrhrTPILraccimage ImportErrornumpyrrr4 src.data_iorr*__all__objectrrr rr r r r rr&rrrs  ' Kf, v & V ..>884 6  DNDNN=&=@7MV7MiHsBBB