o :ήc@s$ddlZddZddZddZdS)NcCs8d|kr |ksJJ||kr|S||kr|S|S)aClip coordinate between low and high values. This method was created so that `hessian_det_appx` does not have to make a Python call. Parameters ---------- x : int Coordinate to be clipped. low : int The lower bound. high : int The higher bound. Returns ------- x : int `x` clipped between `high` and `low`. r)xlowhighrrP/tmp/pip-target-vg8gfxp4/lib/python/skimage/feature/_hessian_det_appx_pythran.py_clips rcCst|d|jdd}t|d|jdd}t||d|jdd}t||d|jdd}|||f|||f|||f|||f}td|S)aSIntegrate over the 2D integral image in the given window. This method was created so that `hessian_det_appx` does not have to make a Python call. Parameters ---------- img : array The integral image over which to integrate. r : int The row number of the top left corner. c : int The column number of the top left corner. rl : int The number of rows over which to integrate. cl : int The number of columns over which to integrate. Returns ------- ans : int The integral over the given window. rg)rshapemax)imgrcrlclr2c2ansrrr_integ"s 0 rc Cstd|}|j\}}|dd}|d}|d}|}|dd} tj|tjd} d||} |ddkr9|d7}t|D]} t|D]} t|| || |||}t|| d| d||}t|| || d||}t|| d| |||}||||}| | }t|| |d| |d|d|}t|| |d| |dd|d|}|d|}| | }t|| || |d|d|d}t|| |d| |d|d|d}|d|}| | }||d||| | | f<qCq=| S)a.Compute the approximate Hessian Determinant over a 2D image. This method uses box filters over integral images to compute the approximate Hessian Determinant as described in [1]_. Parameters ---------- img : array The integral image over which to compute Hessian Determinant. sigma : float Standard deviation used for the Gaussian kernel, used for the Hessian matrix Returns ------- out : array The array of the Determinant of Hessians. References ---------- .. [1] Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool, "SURF: Speeded Up Robust Features" ftp://ftp.vision.ee.ethz.ch/publications/articles/eth_biwi_00517.pdf Notes ----- The running time of this method only depends on size of the image. It is independent of `sigma` as one would expect. The downside is that the result for `sigma` less than `3` is not accurate, i.e., not similar to the result obtained if someone computed the Hessian and took its determinant. r)dtypeg?rgQ?)intr np empty_likedoubleranger)r sigmasizeheightwidths2s3lwboutw_ir r tlbrbltrdxymidsidedxxdyyrrr_hessian_matrix_detFs< "        $(  $(  r0)numpyrrrr0rrrrs $