3j SSKrS\RS\RS\R4SjrS\RS\RS\RS\R4S jrg) NsourcetemplatereturncURnUR5nUR5n[R"USSS9up4n[R"USS9upg[R"USUR S9nXS- n[R"USUR S9n XS- n [ XU5n XRU5$)aAdjust the pixel values of an image to match its histogram towards a target image. `Histogram matching `_ is the transformation of an image so that its histogram matches a specified histogram. In this implementation, the histogram is computed over the flattened image array. Code referred to `here `_. Args: source: Image to transform. template: Template image. It can have different dimensions to source. Returns: The transformed output image as the same shape as the source image. Note: This function does not matches histograms element-wisely if input a batched tensor. T)return_inverse return_counts)rr)dimdtype)shaperaveltorchuniquecumsumr interpreshape) rroldshape_bin_idxs_countst_valuest_counts s_quantiles t_quantilesinterp_t_valuess [/home/wildlama/miniconda3/lib/python3.13/site-packages/kornia/contrib/histogram_matching.pyhistogram_matchingrs&||H \\^F~~H!<<tSWXAhdCH ,,xQfllCKB/K,,xQfllCKB/K[x@O  # + +H 55xxpfpc[R"[R"XSS9S[U5S- 5nX#S- XU- -X#XUS- - --XXS- - - $)aOne-dimensional linear interpolation for monotonically increasing sample points. Returns the one-dimensional piecewise linear interpolant to a function with given discrete data points :math:`(xp, fp)`, evaluated at :math:`x`. This is confirmed to be a correct implementation. See https://github.com/pytorch/pytorch/issues/1552#issuecomment-979998307 Args: x: the :math:`x`-coordinates at which to evaluate the interpolated values. xp: the :math:`x`-coordinates of the data points, must be increasing. fp: the :math:`y`-coordinates of the data points, same length as `xp`. Returns: the interpolated values, same size as `x`. T)right)rclip searchsortedlen)rr r!is rrr@sk&  5%%b48!SWq[IA 1uI #beqa!e9}&= ="%"QRU)BS TTr)rTensorrrrrr+sg$ (6u||(6u||(6 (6VUellU U%,,U5<<Ur