Generated by Cython 3.0.10
Yellow lines hint at Python interaction.
Click on a line that starts with a "+" to see the C code that Cython generated for it.
Raw output: denoise_cython.c
001:
002:
+003: import numpy as np
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004: cimport numpy as np
005: cimport cython
006:
007: from libc.math cimport sqrt, abs
008:
+009: from PIL import Image
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010:
+011: from pathlib import Path
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012:
+013: DTYPE = np.float64
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014:
+015: @cython.boundscheck(False)
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016: def denoise_chambolle(
017: str image_path,
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021: ):
022: """Image denoising algorithm following Chambolle's method
023: proposed in [1]_.
024:
025: Note that the scikit-image library also has a reference implementation
026: of the same algorithm.
027:
028: References
029: ----------
030: .. [1] Antonin Chambolle, An algorithm for total variation minimization
031: and applications, Journal of Mathematical Imaging and Vision,
032: Springer, 2004, 20, 89 -- 97.
033: """
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035:
036:
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040: )
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__pyx_v_tau = 0.25;
043:
044: # image_shape = tuple(image_data.shape)[:2]
+045: cdef Py_ssize_t M = image_data.shape[0]
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+046: cdef Py_ssize_t N = image_data.shape[1]
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047:
048: # num_channels = image_data.shape[2]
+049: cdef Py_ssize_t num_channels = image_data.shape[2]
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050:
+051: result_image = np.zeros_like(image_data, dtype=DTYPE)
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053: cdef double [:, :, :] p_view, result_gradient_view
054: cdef double [:, :] result_channel_view
055:
+056: cdef int num_iter = 0
__pyx_v_num_iter = 0;
057: cdef double p_div_ij, scale, p_tmp, max_var, tmp_var
058:
059: cdef Py_ssize_t i, j, channel, ax
060:
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__pyx_t_9 = __pyx_v_num_channels;
__pyx_t_10 = __pyx_t_9;
for (__pyx_t_11 = 0; __pyx_t_11 < __pyx_t_10; __pyx_t_11+=1) {
__pyx_v_channel = __pyx_t_11;
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063: # p_div = np.zeros((M, N), dtype=DTYPE)
+064: result_gradient_view = result_gradient = np.zeros_like(p, dtype=DTYPE)
__Pyx_GetModuleGlobalName(__pyx_t_7, __pyx_n_s_np); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_t_1 = __Pyx_PyObject_GetAttrStr(__pyx_t_7, __pyx_n_s_zeros_like); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __pyx_t_7 = PyTuple_New(1); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __Pyx_INCREF(__pyx_v_p); __Pyx_GIVEREF(__pyx_v_p); if (__Pyx_PyTuple_SET_ITEM(__pyx_t_7, 0, __pyx_v_p)) __PYX_ERR(0, 64, __pyx_L1_error); __pyx_t_2 = __Pyx_PyDict_NewPresized(1); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_GetModuleGlobalName(__pyx_t_6, __pyx_n_s_DTYPE); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); if (PyDict_SetItem(__pyx_t_2, __pyx_n_s_dtype, __pyx_t_6) < 0) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __pyx_t_6 = __Pyx_PyObject_Call(__pyx_t_1, __pyx_t_7, __pyx_t_2); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 64, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __pyx_t_8 = __Pyx_PyObject_to_MemoryviewSlice_dsdsds_double(__pyx_t_6, PyBUF_WRITABLE); if (unlikely(!__pyx_t_8.memview)) __PYX_ERR(0, 64, __pyx_L1_error) __PYX_XCLEAR_MEMVIEW(&__pyx_v_result_gradient_view, 1); __PYX_INC_MEMVIEW(&__pyx_t_8, 1); __pyx_v_result_gradient_view = __pyx_t_8; __Pyx_INCREF(__pyx_t_6); __Pyx_XDECREF_SET(__pyx_v_result_gradient, __pyx_t_6); __PYX_XCLEAR_MEMVIEW(&__pyx_t_8, 1); __pyx_t_8.memview = NULL; __pyx_t_8.data = NULL; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+065: result_channel_view = result_channel = image_data[:, :, channel].copy()
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066:
+067: num_iter = 0
__pyx_v_num_iter = 0;
+068: while num_iter < max_num_iter:
while (1) {
__pyx_t_13 = (__pyx_v_num_iter < __pyx_v_max_num_iter);
if (!__pyx_t_13) break;
+069: if num_iter > 0:
__pyx_t_13 = (__pyx_v_num_iter > 0);
if (__pyx_t_13) {
/* … */
}
070: # p_div = p.sum(axis=0)
071: # p_div[1:, :] -= p[0, 0:-1, :]
072: # p_div[:, 1:] -= p[1, :, 0:-1]
+073: for i in range(M):
__pyx_t_14 = __pyx_v_M;
__pyx_t_15 = __pyx_t_14;
for (__pyx_t_16 = 0; __pyx_t_16 < __pyx_t_15; __pyx_t_16+=1) {
__pyx_v_i = __pyx_t_16;
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__pyx_t_17 = __pyx_v_N;
__pyx_t_18 = __pyx_t_17;
for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {
__pyx_v_j = __pyx_t_19;
+075: p_div_ij = 0
__pyx_v_p_div_ij = 0.0;
+076: if i < M - 1:
__pyx_t_13 = (__pyx_v_i < (__pyx_v_M - 1));
if (__pyx_t_13) {
/* … */
}
+077: p_div_ij += p_view[0, i, j]
__pyx_t_20 = 0;
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[2];
__pyx_v_p_div_ij = (__pyx_v_p_div_ij + (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_20 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_22 * __pyx_v_p_view.strides[2]) ))));
+078: if i > 0:
__pyx_t_13 = (__pyx_v_i > 0);
if (__pyx_t_13) {
/* … */
}
+079: p_div_ij -= p_view[0, i-1, j]
__pyx_t_22 = 0;
__pyx_t_21 = (__pyx_v_i - 1);
__pyx_t_20 = __pyx_v_j;
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[2];
__pyx_v_p_div_ij = (__pyx_v_p_div_ij - (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_22 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_20 * __pyx_v_p_view.strides[2]) ))));
+080: if j < N - 1:
__pyx_t_13 = (__pyx_v_j < (__pyx_v_N - 1));
if (__pyx_t_13) {
/* … */
}
+081: p_div_ij += p_view[1, i, j]
__pyx_t_20 = 1;
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[2];
__pyx_v_p_div_ij = (__pyx_v_p_div_ij + (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_20 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_22 * __pyx_v_p_view.strides[2]) ))));
+082: if j > 0:
__pyx_t_13 = (__pyx_v_j > 0);
if (__pyx_t_13) {
/* … */
}
+083: p_div_ij -= p_view[1, i, j-1]
__pyx_t_22 = 1;
__pyx_t_21 = __pyx_v_i;
__pyx_t_20 = (__pyx_v_j - 1);
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[2];
__pyx_v_p_div_ij = (__pyx_v_p_div_ij - (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_22 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_20 * __pyx_v_p_view.strides[2]) ))));
084:
+085: result_channel_view[i, j] = image_data_view[i, j, channel] - p_div_ij
__pyx_t_20 = __pyx_v_i;
__pyx_t_21 = __pyx_v_j;
__pyx_t_22 = __pyx_v_channel;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_image_data_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_image_data_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_image_data_view.shape[2];
__pyx_t_23 = __pyx_v_i;
__pyx_t_24 = __pyx_v_j;
if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_result_channel_view.shape[0];
if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_result_channel_view.shape[1];
*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_channel_view.data + __pyx_t_23 * __pyx_v_result_channel_view.strides[0]) ) + __pyx_t_24 * __pyx_v_result_channel_view.strides[1]) )) = ((*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_image_data_view.data + __pyx_t_20 * __pyx_v_image_data_view.strides[0]) ) + __pyx_t_21 * __pyx_v_image_data_view.strides[1]) ) + __pyx_t_22 * __pyx_v_image_data_view.strides[2]) ))) - __pyx_v_p_div_ij);
}
}
086:
087: # result_channel = image_data[:, :, channel] - p_div
088:
089: # result_gradient[0, 0:-1, :] = np.diff(result_channel, axis=0)
090: # result_gradient[1, :, 0:-1] = np.diff(result_channel, axis=1)
+091: for i in range(M):
__pyx_t_14 = __pyx_v_M;
__pyx_t_15 = __pyx_t_14;
for (__pyx_t_16 = 0; __pyx_t_16 < __pyx_t_15; __pyx_t_16+=1) {
__pyx_v_i = __pyx_t_16;
+092: for j in range(N):
__pyx_t_17 = __pyx_v_N;
__pyx_t_18 = __pyx_t_17;
for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {
__pyx_v_j = __pyx_t_19;
+093: if i < M - 1:
__pyx_t_13 = (__pyx_v_i < (__pyx_v_M - 1));
if (__pyx_t_13) {
/* … */
}
+094: result_gradient_view[0, i, j] = result_channel_view[i + 1, j] - result_channel_view[i, j]
__pyx_t_22 = (__pyx_v_i + 1);
__pyx_t_21 = __pyx_v_j;
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_result_channel_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_result_channel_view.shape[1];
__pyx_t_20 = __pyx_v_i;
__pyx_t_24 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_result_channel_view.shape[0];
if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_result_channel_view.shape[1];
__pyx_t_23 = 0;
__pyx_t_25 = __pyx_v_i;
__pyx_t_26 = __pyx_v_j;
if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_result_gradient_view.shape[0];
if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_result_gradient_view.shape[1];
if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_result_gradient_view.shape[2];
*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_gradient_view.data + __pyx_t_23 * __pyx_v_result_gradient_view.strides[0]) ) + __pyx_t_25 * __pyx_v_result_gradient_view.strides[1]) ) + __pyx_t_26 * __pyx_v_result_gradient_view.strides[2]) )) = ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_channel_view.data + __pyx_t_22 * __pyx_v_result_channel_view.strides[0]) ) + __pyx_t_21 * __pyx_v_result_channel_view.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_channel_view.data + __pyx_t_20 * __pyx_v_result_channel_view.strides[0]) ) + __pyx_t_24 * __pyx_v_result_channel_view.strides[1]) ))));
+095: if j < N - 1:
__pyx_t_13 = (__pyx_v_j < (__pyx_v_N - 1));
if (__pyx_t_13) {
/* … */
}
}
}
+096: result_gradient_view[1, i, j] = result_channel_view[i, j + 1] - result_channel_view[i, j]
__pyx_t_24 = __pyx_v_i;
__pyx_t_20 = (__pyx_v_j + 1);
if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_result_channel_view.shape[0];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_result_channel_view.shape[1];
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_result_channel_view.shape[0];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_result_channel_view.shape[1];
__pyx_t_26 = 1;
__pyx_t_25 = __pyx_v_i;
__pyx_t_23 = __pyx_v_j;
if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_result_gradient_view.shape[0];
if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_result_gradient_view.shape[1];
if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_result_gradient_view.shape[2];
*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_gradient_view.data + __pyx_t_26 * __pyx_v_result_gradient_view.strides[0]) ) + __pyx_t_25 * __pyx_v_result_gradient_view.strides[1]) ) + __pyx_t_23 * __pyx_v_result_gradient_view.strides[2]) )) = ((*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_channel_view.data + __pyx_t_24 * __pyx_v_result_channel_view.strides[0]) ) + __pyx_t_20 * __pyx_v_result_channel_view.strides[1]) ))) - (*((double *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_channel_view.data + __pyx_t_21 * __pyx_v_result_channel_view.strides[0]) ) + __pyx_t_22 * __pyx_v_result_channel_view.strides[1]) ))));
097:
098:
+099: max_var = 0
__pyx_v_max_var = 0.0;
+100: for i in range(M):
__pyx_t_14 = __pyx_v_M;
__pyx_t_15 = __pyx_t_14;
for (__pyx_t_16 = 0; __pyx_t_16 < __pyx_t_15; __pyx_t_16+=1) {
__pyx_v_i = __pyx_t_16;
+101: for j in range(N):
__pyx_t_17 = __pyx_v_N;
__pyx_t_18 = __pyx_t_17;
for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {
__pyx_v_j = __pyx_t_19;
+102: for ax in range(2):
for (__pyx_t_27 = 0; __pyx_t_27 < 2; __pyx_t_27+=1) {
__pyx_v_ax = __pyx_t_27;
+103: tmp = p_view[ax, i, j]
__pyx_t_22 = __pyx_v_ax;
__pyx_t_21 = __pyx_v_i;
__pyx_t_20 = __pyx_v_j;
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[2];
__pyx_v_tmp = (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_22 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_20 * __pyx_v_p_view.strides[2]) )));
104: scale = (
+105: 1.0 + tau / weight * sqrt(
if (unlikely(__pyx_v_weight == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(0, 105, __pyx_L1_error)
}
/* … */
__pyx_v_scale = (1.0 + ((((double)__pyx_v_tau) / __pyx_v_weight) * sqrt((pow((*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_gradient_view.data + __pyx_t_20 * __pyx_v_result_gradient_view.strides[0]) ) + __pyx_t_21 * __pyx_v_result_gradient_view.strides[1]) ) + __pyx_t_22 * __pyx_v_result_gradient_view.strides[2]) ))), 2.0) + pow((*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_gradient_view.data + __pyx_t_24 * __pyx_v_result_gradient_view.strides[0]) ) + __pyx_t_23 * __pyx_v_result_gradient_view.strides[1]) ) + __pyx_t_25 * __pyx_v_result_gradient_view.strides[2]) ))), 2.0)))));
+106: result_gradient_view[0, i, j]**2 + result_gradient_view[1, i, j]**2
__pyx_t_20 = 0;
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_result_gradient_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_result_gradient_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_result_gradient_view.shape[2];
__pyx_t_24 = 1;
__pyx_t_23 = __pyx_v_i;
__pyx_t_25 = __pyx_v_j;
if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_result_gradient_view.shape[0];
if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_result_gradient_view.shape[1];
if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_result_gradient_view.shape[2];
107: )
108: )
+109: p_view[ax, i, j] = p_view[ax, i, j] - tau * result_gradient_view[ax, i, j]
__pyx_t_25 = __pyx_v_ax;
__pyx_t_23 = __pyx_v_i;
__pyx_t_24 = __pyx_v_j;
if (__pyx_t_25 < 0) __pyx_t_25 += __pyx_v_p_view.shape[0];
if (__pyx_t_23 < 0) __pyx_t_23 += __pyx_v_p_view.shape[1];
if (__pyx_t_24 < 0) __pyx_t_24 += __pyx_v_p_view.shape[2];
__pyx_t_22 = __pyx_v_ax;
__pyx_t_21 = __pyx_v_i;
__pyx_t_20 = __pyx_v_j;
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_result_gradient_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_result_gradient_view.shape[1];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_result_gradient_view.shape[2];
__pyx_t_26 = __pyx_v_ax;
__pyx_t_28 = __pyx_v_i;
__pyx_t_29 = __pyx_v_j;
if (__pyx_t_26 < 0) __pyx_t_26 += __pyx_v_p_view.shape[0];
if (__pyx_t_28 < 0) __pyx_t_28 += __pyx_v_p_view.shape[1];
if (__pyx_t_29 < 0) __pyx_t_29 += __pyx_v_p_view.shape[2];
*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_26 * __pyx_v_p_view.strides[0]) ) + __pyx_t_28 * __pyx_v_p_view.strides[1]) ) + __pyx_t_29 * __pyx_v_p_view.strides[2]) )) = ((*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_25 * __pyx_v_p_view.strides[0]) ) + __pyx_t_23 * __pyx_v_p_view.strides[1]) ) + __pyx_t_24 * __pyx_v_p_view.strides[2]) ))) - (__pyx_v_tau * (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_result_gradient_view.data + __pyx_t_22 * __pyx_v_result_gradient_view.strides[0]) ) + __pyx_t_21 * __pyx_v_result_gradient_view.strides[1]) ) + __pyx_t_20 * __pyx_v_result_gradient_view.strides[2]) )))));
+110: p_view[ax, i, j] = p_view[ax, i, j] / scale
__pyx_t_20 = __pyx_v_ax;
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[2];
__pyx_t_30 = (*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_20 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_22 * __pyx_v_p_view.strides[2]) )));
if (unlikely(__pyx_v_scale == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "float division");
__PYX_ERR(0, 110, __pyx_L1_error)
}
__pyx_t_22 = __pyx_v_ax;
__pyx_t_21 = __pyx_v_i;
__pyx_t_20 = __pyx_v_j;
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[2];
*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_22 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_20 * __pyx_v_p_view.strides[2]) )) = (__pyx_t_30 / __pyx_v_scale);
+111: tmp_var = abs(p_view[ax, i, j] - tmp)
__pyx_t_20 = __pyx_v_ax;
__pyx_t_21 = __pyx_v_i;
__pyx_t_22 = __pyx_v_j;
if (__pyx_t_20 < 0) __pyx_t_20 += __pyx_v_p_view.shape[0];
if (__pyx_t_21 < 0) __pyx_t_21 += __pyx_v_p_view.shape[1];
if (__pyx_t_22 < 0) __pyx_t_22 += __pyx_v_p_view.shape[2];
__pyx_v_tmp_var = fabs(((*((double *) ( /* dim=2 */ (( /* dim=1 */ (( /* dim=0 */ (__pyx_v_p_view.data + __pyx_t_20 * __pyx_v_p_view.strides[0]) ) + __pyx_t_21 * __pyx_v_p_view.strides[1]) ) + __pyx_t_22 * __pyx_v_p_view.strides[2]) ))) - __pyx_v_tmp));
+112: if tmp_var > max_var:
__pyx_t_13 = (__pyx_v_tmp_var > __pyx_v_max_var);
if (__pyx_t_13) {
/* … */
}
}
}
}
+113: max_var = tmp_var
__pyx_v_max_var = __pyx_v_tmp_var;
114:
115: #factors = 1.0 + tau / weight * np.sqrt(
116: # np.power(result_gradient, 2).sum(axis=0)
117: #)
118: #factors = factors[np.newaxis, ...]
119: #p_new = p - tau * result_gradient
120: #p_new /= factors
121:
122: # max_var = np.max(np.abs(p_new - p))
123: # if num_iter % 20 == 0:
124: # print(f"Maximal variation: {max_var}")
125:
+126: if max_var < epsilon:
__pyx_t_13 = (__pyx_v_max_var < __pyx_v_epsilon);
if (__pyx_t_13) {
/* … */
}
+127: print(f"Converged after {num_iter} iterations.")
__pyx_t_6 = PyTuple_New(3); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 127, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); __pyx_t_14 = 0; __pyx_t_31 = 127; __Pyx_INCREF(__pyx_kp_u_Converged_after); __pyx_t_14 += 16; __Pyx_GIVEREF(__pyx_kp_u_Converged_after); PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_kp_u_Converged_after); __pyx_t_7 = __Pyx_PyUnicode_From_int(__pyx_v_num_iter, 0, ' ', 'd'); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 127, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __pyx_t_14 += __Pyx_PyUnicode_GET_LENGTH(__pyx_t_7); __Pyx_GIVEREF(__pyx_t_7); PyTuple_SET_ITEM(__pyx_t_6, 1, __pyx_t_7); __pyx_t_7 = 0; __Pyx_INCREF(__pyx_kp_u_iterations); __pyx_t_14 += 12; __Pyx_GIVEREF(__pyx_kp_u_iterations); PyTuple_SET_ITEM(__pyx_t_6, 2, __pyx_kp_u_iterations); __pyx_t_7 = __Pyx_PyUnicode_Join(__pyx_t_6, 3, __pyx_t_14, __pyx_t_31); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 127, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; __pyx_t_6 = __Pyx_PyObject_CallOneArg(__pyx_builtin_print, __pyx_t_7); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 127, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_6); __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0; __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+128: break
goto __pyx_L6_break;
129:
+130: num_iter += 1
__pyx_v_num_iter = (__pyx_v_num_iter + 1);
}
__pyx_L6_break:;
131:
+132: result_image_view[:, :, channel] = result_channel_view
__pyx_t_12.data = __pyx_v_result_image_view.data;
__pyx_t_12.memview = __pyx_v_result_image_view.memview;
__PYX_INC_MEMVIEW(&__pyx_t_12, 1);
__pyx_t_12.shape[0] = __pyx_v_result_image_view.shape[0];
__pyx_t_12.strides[0] = __pyx_v_result_image_view.strides[0];
__pyx_t_12.suboffsets[0] = -1;
__pyx_t_12.shape[1] = __pyx_v_result_image_view.shape[1];
__pyx_t_12.strides[1] = __pyx_v_result_image_view.strides[1];
__pyx_t_12.suboffsets[1] = -1;
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Py_ssize_t __pyx_tmp_shape = __pyx_v_result_image_view.shape[2];
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if (__pyx_tmp_idx < 0)
__pyx_tmp_idx += __pyx_tmp_shape;
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if (unlikely((__pyx_memoryview_copy_contents(__pyx_v_result_channel_view, __pyx_t_12, 2, 2, 0) < 0))) __PYX_ERR(0, 132, __pyx_L1_error)
__PYX_XCLEAR_MEMVIEW(&__pyx_t_12, 1);
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133:
134:
+135: return Image.fromarray(
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136: # (result_image * 255).astype(np.uint8)
+137: np.multiply(result_image, 255).astype(np.uint8)
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138: )
139: