Generated by Cython 3.0.11
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: processing.c
+001: # File: processing.pyx
__pyx_t_2 = __Pyx_PyDict_NewPresized(0); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_2) < 0) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
002: # cython: language_level=3, boundscheck=False, wraparound=False, nonecheck=False, cdivision=True
003:
+004: import numpy as np
__pyx_t_2 = __Pyx_ImportDottedModule(__pyx_n_s_numpy, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 4, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_2) < 0) __PYX_ERR(0, 4, __pyx_L1_error) __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
005: cimport numpy as np
+006: import pandas as pd
__pyx_t_2 = __Pyx_ImportDottedModule(__pyx_n_s_pandas, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); if (PyDict_SetItem(__pyx_d, __pyx_n_s_pd, __pyx_t_2) < 0) __PYX_ERR(0, 6, __pyx_L1_error) __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
007: cimport pandas as pd
008: from libc.math cimport isnan
009: from cpython.mem cimport PyMem_Malloc, PyMem_Free
010:
011: # Define C types for better performance
+012: ctypedef np.float32_t DTYPE_t
typedef __pyx_t_5numpy_float32_t __pyx_t_13processing_cy_DTYPE_t;
013: ctypedef np.int32_t ITYPE_t
014:
+015: def process_bbox_depth_cy(np.ndarray[DTYPE_t, ndim=2] depth_map,
/* Python wrapper */ static PyObject *__pyx_pw_13processing_cy_1process_bbox_depth_cy(PyObject *__pyx_self, #if CYTHON_METH_FASTCALL PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds #else PyObject *__pyx_args, PyObject *__pyx_kwds #endif ); /*proto*/ PyDoc_STRVAR(__pyx_doc_13processing_cy_process_bbox_depth_cy, "\n Optimized bbox depth calculations using Cython\n "); static PyMethodDef __pyx_mdef_13processing_cy_1process_bbox_depth_cy = {"process_bbox_depth_cy", (PyCFunction)(void*)(__Pyx_PyCFunction_FastCallWithKeywords)__pyx_pw_13processing_cy_1process_bbox_depth_cy, __Pyx_METH_FASTCALL|METH_KEYWORDS, __pyx_doc_13processing_cy_process_bbox_depth_cy}; static PyObject *__pyx_pw_13processing_cy_1process_bbox_depth_cy(PyObject *__pyx_self, #if CYTHON_METH_FASTCALL PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds #else PyObject *__pyx_args, PyObject *__pyx_kwds #endif ) { PyArrayObject *__pyx_v_depth_map = 0; int __pyx_v_y_min; int __pyx_v_y_max; 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if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_kwvalues, __pyx_pyargnames, 0, values + 0, kwd_pos_args, "process_bbox_depth_cy") < 0)) __PYX_ERR(0, 15, __pyx_L3_error) } } else if (unlikely(__pyx_nargs != 5)) { goto __pyx_L5_argtuple_error; } else { values[0] = __Pyx_Arg_FASTCALL(__pyx_args, 0); values[1] = __Pyx_Arg_FASTCALL(__pyx_args, 1); values[2] = __Pyx_Arg_FASTCALL(__pyx_args, 2); values[3] = __Pyx_Arg_FASTCALL(__pyx_args, 3); values[4] = __Pyx_Arg_FASTCALL(__pyx_args, 4); } __pyx_v_depth_map = ((PyArrayObject *)values[0]); __pyx_v_y_min = __Pyx_PyInt_As_int(values[1]); if (unlikely((__pyx_v_y_min == (int)-1) && PyErr_Occurred())) __PYX_ERR(0, 16, __pyx_L3_error) __pyx_v_y_max = __Pyx_PyInt_As_int(values[2]); if (unlikely((__pyx_v_y_max == (int)-1) && PyErr_Occurred())) __PYX_ERR(0, 16, __pyx_L3_error) __pyx_v_x_min = __Pyx_PyInt_As_int(values[3]); if (unlikely((__pyx_v_x_min == (int)-1) && PyErr_Occurred())) __PYX_ERR(0, 16, __pyx_L3_error) __pyx_v_x_max = __Pyx_PyInt_As_int(values[4]); 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016: int y_min, int y_max, int x_min, int x_max):
017: """
018: Optimized bbox depth calculations using Cython
019: """
020: cdef:
+021: int i, j, count = 0
__pyx_v_count = 0;
+022: double sum_val = 0.0
__pyx_v_sum_val = 0.0;
+023: double mean_val = 0.0
__pyx_v_mean_val = 0.0;
024: np.ndarray[DTYPE_t, ndim=1] flat_vals
+025: int flat_size = 0
__pyx_v_flat_size = 0;
026:
+027: for i in range(y_min, y_max):
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__pyx_t_2 = __pyx_t_1;
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__pyx_v_i = __pyx_t_3;
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/* … */
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035:
036: # Create array for trimmed mean calculation
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047:
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if (unlikely(!__pyx_tuple__6)) __PYX_ERR(0, 48, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__6); __Pyx_GIVEREF(__pyx_tuple__6); /* … */ __pyx_t_2 = __Pyx_CyFunction_New(&__pyx_mdef_13processing_cy_3handle_overlaps_cy, 0, __pyx_n_s_handle_overlaps_cy, NULL, __pyx_n_s_processing_cy, __pyx_d, ((PyObject *)__pyx_codeobj__7)); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 48, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); if (PyDict_SetItem(__pyx_d, __pyx_n_s_handle_overlaps_cy, __pyx_t_2) < 0) __PYX_ERR(0, 48, __pyx_L1_error) __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
049: np.ndarray[ITYPE_t, ndim=2] boxes):
050: """
051: Optimized overlap handling using Cython
052: """
053: cdef:
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__pyx_t_1 = __pyx_f_5numpy_7ndarray_5shape_shape(((PyArrayObject *)__pyx_v_boxes)); if (unlikely(__pyx_t_1 == ((npy_intp *)NULL) && PyErr_Occurred())) __PYX_ERR(0, 54, __pyx_L1_error) __pyx_v_n_boxes = (__pyx_t_1[0]);
055: int i, j
056: int y_min1, y_max1, x_min1, x_max1
057: int y_min2, y_max2, x_min2, x_max2
058: double area1, area2, area_intersection
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060:
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/* … */
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PyErr_NoMemory(); __PYX_ERR(0, 62, __pyx_L1_error)
063:
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/*try:*/ {
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__pyx_t_3 = __pyx_v_n_boxes;
__pyx_t_4 = __pyx_t_3;
for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
__pyx_v_i = __pyx_t_5;
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(__pyx_v_to_remove[__pyx_v_i]) = 0;
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067:
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__pyx_t_3 = __pyx_v_n_boxes;
__pyx_t_4 = __pyx_t_3;
for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
__pyx_v_i = __pyx_t_5;
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if ((__pyx_v_to_remove[__pyx_v_i])) {
/* … */
}
+070: continue
goto __pyx_L9_continue;
071:
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073:
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for (__pyx_t_14 = (__pyx_v_i + 1); __pyx_t_14 < __pyx_t_15; __pyx_t_14+=1) {
__pyx_v_j = __pyx_t_14;
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goto __pyx_L14_continue;
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__Pyx_GOTREF(__pyx_t_6);
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__Pyx_GOTREF(__pyx_t_6);
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__Pyx_GOTREF(__pyx_t_6);
__Pyx_XDECREF_SET(__pyx_v_x_min_int, __pyx_t_6);
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__Pyx_GOTREF(__pyx_t_6);
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goto __pyx_L15_break;
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}
__pyx_L4_return: {
__pyx_t_30 = __pyx_r;
__pyx_r = 0;
PyMem_Free(__pyx_v_to_remove);
__pyx_r = __pyx_t_30;
__pyx_t_30 = 0;
goto __pyx_L0;
}
}