mirror of
https://github.com/wassname/scikit-image.git
synced 2026-07-16 11:21:25 +08:00
added morphology functions and support for IplConvKernel
This commit is contained in:
sccolbert
File diff suppressed because it is too large
Load Diff
@@ -7,6 +7,7 @@ cdef extern from "Python.h":
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cdef extern from "numpy/arrayobject.h":
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object PyArray_Empty(int, np.npy_intp*, dtype, int)
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bint PyArray_ISCONTIGUOUS(np.ndarray)
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ctypedef np.uint8_t UINT8_t
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ctypedef np.int8_t INT8_t
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@@ -44,3 +45,9 @@ cdef np.npy_intp* clone_array_shape(np.ndarray arr)
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#-------------------------------------------------------------------------------
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cdef CvPoint2D32f* array_as_cvPoint2D32f_ptr(np.ndarray arr)
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cdef CvTermCriteria get_cvTermCriteria(int, double)
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cdef IplConvKernel* get_IplConvKernel_ptr_from_array(np.ndarray arr, anchor) except NULL
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cdef void free_IplConvKernel(IplConvKernel* iplkernel)
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#-------------------------------------------------------------------------------
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# Other convienences
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#-------------------------------------------------------------------------------
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@@ -4,7 +4,7 @@ cimport numpy as np
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from python cimport *
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from opencv_constants import *
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from opencv_type cimport *
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from _libimport import cxcore
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from _libimport import cv, cxcore
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# setup numpy tables for this module
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np.import_array()
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@@ -108,6 +108,7 @@ cdef CvMat* cvmat_ptr_from_iplimage(IplImage* arr):
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return mat_hdr
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cdef int validate_array(np.ndarray arr) except -1:
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assert PyArray_ISCONTIGUOUS(arr), 'Array must be contiguous'
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if arr.ndim != 2 and arr.ndim != 3:
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raise ValueError('Arrays must have either 2 or 3 dimensions')
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if arr.ndim == 3:
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@@ -187,7 +188,7 @@ cdef np.ndarray new_array_like_diff_dtype(np.ndarray arr, dtype):
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return PyArray_Empty(arr.ndim, arr.shape, dtype, 0)
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cdef np.npy_intp* clone_array_shape(np.ndarray arr):
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# make sure you call PyMem_Free after your done with the shape
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# make sure you call PyMem_Free after you're done with the shape
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cdef int ndim = arr.ndim
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cdef np.npy_intp* shape = <np.npy_intp*>PyMem_Malloc(
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ndim * sizeof(np.npy_intp))
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@@ -223,3 +224,61 @@ cdef CvTermCriteria get_cvTermCriteria(int iterations, double epsilon):
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crit.max_iter = 0
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crit.epsilon = epsilon
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return crit
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ctypedef IplConvKernel* (*cvCreateStructuringElementExPtr)(int, int, int, int,
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int, int*)
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cdef cvCreateStructuringElementExPtr c_cvCreateStructuringElementEx
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c_cvCreateStructuringElementEx = (<cvCreateStructuringElementExPtr*><size_t>
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ctypes.addressof(cv.cvCreateStructuringElementEx))[0]
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ctypedef void (*cvReleaseStructuringElementPtr)(IplConvKernel**)
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cdef cvReleaseStructuringElementPtr c_cvReleaseStructuringElement
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c_cvReleaseStructuringElement = (<cvReleaseStructuringElementPtr*><size_t>
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ctypes.addressof(cv.cvReleaseStructuringElement))[0]
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cdef IplConvKernel* get_IplConvKernel_ptr_from_array(np.ndarray arr, anchor) \
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except NULL:
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# make sure you call free_IplConvKernel you're done with the kernel
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validate_array(arr)
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assert_ndims(arr, [2])
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assert_dtype(arr, [INT32])
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cdef int rows
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cdef int cols
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cdef int anchorx
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cdef int anchory
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if anchor is not None:
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assert len(anchor) == 2, 'anchor must be (x, y) tuple'
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anchorx = <int>anchor[0]
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anchory = <int>anchor[1]
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assert (anchorx < arr.shape[1]) and (anchorx >= 0) \
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and (anchory < arr.shape[0]) and (anchory >= 0), \
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'anchor point must be inside kernel'
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else:
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anchorx = <int>(arr.shape[1] / 2.)
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anchory = <int>(arr.shape[0] / 2.)
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rows = arr.shape[0]
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cols = arr.shape[1]
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cdef int* values = <int*>arr.data
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# this function copies the data from the array into (i'm guessing)
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# aligned memory. Since this is using opencv memory management
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# the free_IplConvKernel function makes the appropriate calls to free it
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cdef IplConvKernel* iplkernel = \
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c_cvCreateStructuringElementEx(cols, rows, anchorx, anchory,
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CV_SHAPE_CUSTOM, values)
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return iplkernel
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cdef void free_IplConvKernel(IplConvKernel* iplkernel):
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c_cvReleaseStructuringElement(&iplkernel)
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#-------------------------------------------------------------------------------
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# Other convienences
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#-------------------------------------------------------------------------------
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@@ -22,6 +22,17 @@ CV_INTER_AREA = 3
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CV_WARP_FILL_OUTLIERS = 8
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CV_WARP_INVERSE_MAP = 16
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CV_SHAPE_RECT = 0
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CV_SHAPE_CROSS = 1
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CV_SHAPE_ELLIPSE = 2
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CV_SHAPE_CUSTOM = 100
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CV_MOP_OPEN = 2
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CV_MOP_CLOSE = 3
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CV_MOP_GRADIENT = 4
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CV_MOP_TOPHAT = 5
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CV_MOP_BLACKHAT = 6
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#########################
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# Calibration Constants #
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#########################
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+3282
-1212
File diff suppressed because it is too large
Load Diff
@@ -111,6 +111,28 @@ cdef cvWarpPerspectivePtr c_cvWarpPerspective
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c_cvWarpPerspective = (<cvWarpPerspectivePtr*><size_t>
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ctypes.addressof(cv.cvWarpPerspective))[0]
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# cvLogPolar
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ctypedef void (*cvLogPolarPtr)(IplImage*, IplImage*, CvPoint2D32f, double, int)
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cdef cvLogPolarPtr c_cvLogPolar
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c_cvLogPolar = (<cvLogPolarPtr*><size_t>ctypes.addressof(cv.cvLogPolar))[0]
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# cvErode
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ctypedef void (*cvErodePtr)(IplImage*, IplImage*, IplConvKernel*, int)
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cdef cvErodePtr c_cvErode
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c_cvErode = (<cvErodePtr*><size_t>ctypes.addressof(cv.cvErode))[0]
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# cvDilate
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ctypedef void (*cvDilatePtr)(IplImage*, IplImage*, IplConvKernel*, int)
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cdef cvDilatePtr c_cvDilate
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c_cvDilate = (<cvDilatePtr*><size_t>ctypes.addressof(cv.cvDilate))[0]
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# cvMorphologyEx
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ctypedef void (*cvMorphologyExPtr)(IplImage*, IplImage*, IplImage*,
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IplConvKernel*, int, int)
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cdef cvMorphologyExPtr c_cvMorphologyEx
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c_cvMorphologyEx = (<cvMorphologyExPtr*><size_t>
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ctypes.addressof(cv.cvMorphologyEx))[0]
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# cvCalibrateCamera2
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ctypedef void (*cvCalibrateCamera2Ptr)(CvMat*, CvMat*, CvMat*,
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CvSize, CvMat*, CvMat*, CvMat*, CvMat*, int)
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@@ -764,6 +786,139 @@ def cvWarpPerspective(np.ndarray src, np.ndarray warpmat,
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return out
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def cvLogPolar(np.ndarray src, center, double M,
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int flags=CV_INTER_LINEAR+CV_WARP_FILL_OUTLIERS):
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validate_array(src)
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assert len(center) == 2
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cdef np.ndarray out = new_array_like(src)
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cdef CvPoint2D32f cv_center
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cv_center.x = <float>center[0]
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cv_center.y = <float>center[1]
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cdef IplImage srcimg
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cdef IplImage outimg
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populate_iplimage(src, &srcimg)
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populate_iplimage(out, &outimg)
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c_cvLogPolar(&srcimg, &outimg, cv_center, M, flags)
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return out
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def cvErode(np.ndarray src, np.ndarray element=None, int iterations=1,
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anchor=None, in_place=False):
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validate_array(src)
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cdef np.ndarray out
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cdef IplConvKernel* iplkernel
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if element == None:
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iplkernel = NULL
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else:
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iplkernel = get_IplConvKernel_ptr_from_array(element, anchor)
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if in_place:
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out = src
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else:
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out = new_array_like(src)
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cdef IplImage srcimg
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cdef IplImage outimg
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populate_iplimage(src, &srcimg)
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populate_iplimage(out, &outimg)
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c_cvErode(&srcimg, &outimg, iplkernel, iterations)
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free_IplConvKernel(iplkernel)
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if in_place:
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return None
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else:
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return out
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def cvDilate(np.ndarray src, np.ndarray element=None, int iterations=1,
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anchor=None, in_place=False):
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validate_array(src)
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cdef np.ndarray out
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cdef IplConvKernel* iplkernel
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if element == None:
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iplkernel = NULL
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else:
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iplkernel = get_IplConvKernel_ptr_from_array(element, anchor)
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if in_place:
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out = src
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else:
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out = new_array_like(src)
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cdef IplImage srcimg
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cdef IplImage outimg
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populate_iplimage(src, &srcimg)
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populate_iplimage(out, &outimg)
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c_cvDilate(&srcimg, &outimg, iplkernel, iterations)
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free_IplConvKernel(iplkernel)
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if in_place:
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return None
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else:
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return out
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def cvMorphologyEx(np.ndarray src, np.ndarray element, int operation,
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int iterations=1, anchor=None, in_place=False):
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validate_array(src)
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cdef np.ndarray out
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cdef np.ndarray temp
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cdef IplConvKernel* iplkernel
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iplkernel = get_IplConvKernel_ptr_from_array(element, anchor)
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if in_place:
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out = src
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else:
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out = new_array_like(src)
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cdef IplImage srcimg
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cdef IplImage outimg
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cdef IplImage tempimg
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cdef IplImage* tempimgptr = &tempimg
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populate_iplimage(src, &srcimg)
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populate_iplimage(out, &outimg)
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# determine if we need the tempimg
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if operation == CV_MOP_OPEN or operation == CV_MOP_CLOSE:
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tempimgptr = NULL
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elif operation == CV_MOP_GRADIENT:
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temp = new_array_like(src)
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populate_iplimage(temp, &tempimg)
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elif operation == CV_MOP_TOPHAT or operation == CV_MOP_BLACKHAT:
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if in_place:
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temp = new_array_like(src)
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populate_iplimage(temp, &tempimg)
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else:
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tempimgptr = NULL
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else:
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raise RuntimeError('operation type not understood')
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c_cvMorphologyEx(&srcimg, &outimg, tempimgptr, iplkernel, operation,
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iterations)
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free_IplConvKernel(iplkernel)
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if in_place:
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return None
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else:
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return out
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def cvCalibrateCamera2(np.ndarray object_points, np.ndarray image_points,
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np.ndarray point_counts, image_size):
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@@ -66,4 +66,13 @@ cdef struct CvTermCriteria:
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cdef struct CvScalar:
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double val[4]
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cdef struct _IplConvKernel:
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int nCols
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int nRows
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int anchorX
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int anchorY
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int *values
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int nShiftR
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ctypedef _IplConvKernel IplConvKernel
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@@ -15,7 +15,7 @@ with warnings.catch_warnings():
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opencv_skip = dec.skipif(cv is None,
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'OpenCV libraries not found')
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class OpenCVTest:
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class OpenCVTest(object):
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lena_RGB_U8 = np.load(os.path.join(data_dir, 'lena_RGB_U8.npy'))
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lena_GRAY_U8 = np.load(os.path.join(data_dir, 'lena_GRAY_U8.npy'))
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@@ -70,7 +70,7 @@ class TestSmooth(OpenCVTest):
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cvSmooth(self.lena_GRAY_U8, None, st, 3, 0, 0, 0, False)
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class TestFindCornerSubPix:
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class TestFindCornerSubPix(object):
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@opencv_skip
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def test_cvFindCornersSubPix(self):
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img = np.array([[1, 1, 1, 0, 0, 0, 1, 1, 1],
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@@ -133,7 +133,45 @@ class TestWarpPerspective(OpenCVTest):
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cvWarpPerspective(self.lena_RGB_U8, warpmat)
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class TestFindChessboardCorners:
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class TestLogPolar(OpenCVTest):
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@opencv_skip
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def test_cvLogPolar(self):
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img = self.lena_RGB_U8
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width = img.shape[1]
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height = img.shape[0]
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x = width / 2.
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y = height / 2.
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cvLogPolar(img, (x, y), 20)
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class TestErode(OpenCVTest):
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@opencv_skip
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def test_cvErode(self):
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kern = np.array([[0, 1, 0],
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[1, 1, 1],
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[0, 1, 0]], dtype='int32')
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cvErode(self.lena_RGB_U8, kern, in_place=True)
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class TestDilate(OpenCVTest):
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@opencv_skip
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def test_cvDilate(self):
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kern = np.array([[0, 1, 0],
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[1, 1, 1],
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[0, 1, 0]], dtype='int32')
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cvDilate(self.lena_RGB_U8, kern, in_place=True)
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class TestMorphologyEx(OpenCVTest):
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@opencv_skip
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def test_cvMorphologyEx(self):
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kern = np.array([[0, 1, 0],
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[1, 1, 1],
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[0, 1, 0]], dtype='int32')
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cvMorphologyEx(self.lena_RGB_U8, kern, CV_MOP_TOPHAT, in_place=True)
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class TestFindChessboardCorners(object):
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@opencv_skip
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def test_cvFindChessboardCorners(self):
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chessboard_GRAY_U8 = np.load(os.path.join(data_dir,
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@@ -141,7 +179,7 @@ class TestFindChessboardCorners:
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pts = cvFindChessboardCorners(chessboard_GRAY_U8, (7, 7))
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class TestDrawChessboardCorners:
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class TestDrawChessboardCorners(object):
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@opencv_skip
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def test_cvDrawChessboardCorners(self):
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chessboard_GRAY_U8 = np.load(os.path.join(data_dir,
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@@ -150,9 +188,11 @@ class TestDrawChessboardCorners:
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'chessboard_RGB_U8.npy'))
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corners = cvFindChessboardCorners(chessboard_GRAY_U8, (7, 7))
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cvDrawChessboardCorners(chessboard_RGB_U8, (7, 7), corners)
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class TestCvCalibrateCamera2(object):
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def test_cvCalibrateCamear2_Identity(self):
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class TestCalibrateCamera2(object):
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@opencv_skip
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def test_cvCalibrateCamera2_Identity(self):
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ys = xs = range(4)
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image_points = np.array( [(4 * x, 4 * y) for x in xs for y in ys ],
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@@ -177,8 +217,9 @@ class TestCvCalibrateCamera2(object):
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assert_almost_equal( intrinsics[2,1], 0)
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assert_almost_equal( intrinsics[2,2], 1)
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@opencv_skip
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@dec.slow
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def test_cvCalibrateCamear2_KnownData(self):
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def test_cvCalibrateCamera2_KnownData(self):
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(object_points,points_count,image_points,intrinsics,distortions) =\
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cPickle.load(open(os.path.join(
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data_dir, "cvCalibrateCamera2TestData.pck"), "rb")
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