From c332fd53637fbfb198c9c3e161a258c4e46aca9d Mon Sep 17 00:00:00 2001 From: Vighnesh Birodkar Date: Sat, 6 Jun 2015 21:46:50 +0530 Subject: [PATCH] docstring change --- skimage/transform/_seam_carving.pyx | 36 ++++++++++++++--------------- 1 file changed, 18 insertions(+), 18 deletions(-) diff --git a/skimage/transform/_seam_carving.pyx b/skimage/transform/_seam_carving.pyx index 86f3634a..b91887a5 100644 --- a/skimage/transform/_seam_carving.pyx +++ b/skimage/transform/_seam_carving.pyx @@ -13,7 +13,7 @@ cdef find_seam_v(cnp.double_t[:, ::1] energy_img, cnp.int8_t[:, ::1] track_img, cnp.double_t[::1] current_cost, cnp.double_t[::1] prev_cost, Py_ssize_t cols): """Find a single vertical seam in an image that will be removed. - + Parameters ---------- energy_img : (M, N) ndarray @@ -32,19 +32,19 @@ cdef find_seam_v(cnp.double_t[:, ::1] energy_img, cnp.int8_t[:, ::1] track_img, The number of cols to process for seam carving. Columns with indices more than `cols` are ignored. - + Returns ------- seam : (M, ) ndarray An array containing the index of the row of the pixel to be removed for each column in the image. - + Notes ----- `track_img`, `current_cost` and `prev_cost` are passed as arguments to avoid memory allocation at each iteration of `_seam_carve_v`. """ - + cdef Py_ssize_t rows, row, col rows = energy_img.shape[0] cdef cnp.double_t tmp, min_cost @@ -57,14 +57,14 @@ cdef find_seam_v(cnp.double_t[:, ::1] energy_img, cnp.int8_t[:, ::1] track_img, for row in range(1, rows): for col in range(0, cols): - + min_cost = ABSOLUTE_MAX for offset in range(-1, 2): idx = col + offset - + if idx > cols - 1 or idx < 0: continue - + if prev_cost[idx] < min_cost: min_cost = prev_cost[idx] track_img[row, col] = offset @@ -85,27 +85,27 @@ cdef find_seam_v(cnp.double_t[:, ::1] energy_img, cnp.int8_t[:, ::1] track_img, cdef remove_seam_v_2d(cnp.double_t[:, ::1] img, Py_ssize_t[::1] seam, Py_ssize_t cols): - cdef Py_ssize_t rows, row, col, idx - rows = img.shape[0] - """ Removes one horizontal seam from the image. + """ Removes one vertical seam from the image. The method modifies `img` so that all pixels to the right of the vertical seam are pushed one place left. image : (M, N) ndarray - Input image whose vertical seam is to be removed. + Input image whose vertical seam is to be removed. seam : (M, ) ndarray - An array use to store the index of the column in the seam for each row. + An array use to store the index of the column in the seam for each row. cols : int - Number of columns in the input image to process. Column indices more - than `cols` are ingored. + Number of columns in the input image to process. Column indices more + than `cols` are ingored. Notes ----- `seam` is passed as an argument so that we don't have to reallocate it for each iteration in `_seam_carve_v`. """ - + cdef Py_ssize_t rows, row, col, idx + rows = img.shape[0] + for row in range(rows): for idx in range(seam[row], cols - 1): img[row, idx] = img[row, idx + 1] @@ -171,7 +171,7 @@ def _seam_carve_v(img, iters, energy_func, extra_args , extra_kwargs, border): ------- image : (M, N - iters) or (M, N - iters, 3) ndarray The cropped image with the vertical seams removed. - + References ---------- .. [1] Shai Avidan and Ariel Shamir @@ -191,11 +191,11 @@ def _seam_carve_v(img, iters, energy_func, extra_args , extra_kwargs, border): sliced_img = img[:, 0:cols] energy_img = energy_func(sliced_img, *extra_args, **extra_kwargs) - + # So that borders are ignored. energy_img[:, 0:border] = ABSOLUTE_MAX energy_img[:, cols-border:cols] = ABSOLUTE_MAX - + seam = find_seam_v(energy_img, track_img, current_cost, prev_cost, cols)