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Merge remote-tracking branch 'refs/remotes/upstream/master'

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This commit is contained in:
Olexa Bilaniuk 2015-03-03 23:15:05 -05:00
commit 3a4d9a77b2
6 changed files with 47 additions and 36 deletions
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12
doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown
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@ -59,7 +59,7 @@ denotes they are the parameters of possible lines in the image. (Image courtesy:
![](images/houghlines2.jpg)
Hough Tranform in OpenCV
Hough Transform in OpenCV
=========================
Everything explained above is encapsulated in the OpenCV function, \*\*cv2.HoughLines()\*\*. It simply returns an array of :math:(rho,
@ -78,7 +78,8 @@ gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
lines = cv2.HoughLines(edges,1,np.pi/180,200)
for rho,theta in lines[0]:
for line in lines:
rho,theta = line[0]
a = np.cos(theta)
b = np.sin(theta)
x0 = a*rho
@ -123,10 +124,9 @@ import numpy as np
img = cv2.imread('dave.jpg')
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(gray,50,150,apertureSize = 3)
minLineLength = 100
maxLineGap = 10
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength,maxLineGap)
for x1,y1,x2,y2 in lines[0]:
lines = cv2.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)
for line in lines:
x1,y1,x2,y2 = line[0]
cv2.line(img,(x1,y1),(x2,y2),(0,255,0),2)
cv2.imwrite('houghlines5.jpg',img)

4
modules/core/src/system.cpp
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@ -327,9 +327,9 @@ struct HWFeatures
if (cpufile >= 0)
{
Elf32_auxv_t auxv;
const size_t size_auxv_t = sizeof(Elf32_auxv_t);
const size_t size_auxv_t = sizeof(auxv);
while ((size_t)read(cpufile, &auxv, sizeof(Elf32_auxv_t)) == size_auxv_t)
while ((size_t)read(cpufile, &auxv, size_auxv_t) == size_auxv_t)
{
if (auxv.a_type == AT_HWCAP)
{

3
modules/videoio/include/opencv2/videoio.hpp
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@ -136,7 +136,8 @@ enum { CAP_PROP_POS_MSEC =0,
// Currently, these are supported through the libv4l interface only.
enum { CAP_MODE_BGR = 0, // BGR24 (default)
CAP_MODE_RGB = 1, // RGB24
CAP_MODE_GRAY = 2 // Y8
CAP_MODE_GRAY = 2, // Y8
CAP_MODE_YUYV = 3 // YUYV
};

3
modules/videoio/include/opencv2/videoio/videoio_c.h
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@ -299,7 +299,8 @@ enum
{
CV_CAP_MODE_BGR = 0, // BGR24 (default)
CV_CAP_MODE_RGB = 1, // RGB24
CV_CAP_MODE_GRAY = 2 // Y8
CV_CAP_MODE_GRAY = 2, // Y8
CV_CAP_MODE_YUYV = 3 // YUYV
};
enum

27
modules/videoio/src/cap_libv4l.cpp
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@ -646,6 +646,8 @@ static inline int channels_for_mode(int mode)
switch(mode) {
case CV_CAP_MODE_GRAY:
return 1;
case CV_CAP_MODE_YUYV:
return 2;
default:
return 3;
}
@ -713,31 +715,26 @@ static int _capture_V4L2 (CvCaptureCAM_V4L *capture, char *deviceName)
/* libv4l will convert from any format to V4L2_PIX_FMT_BGR24,
V4L2_PIX_FMT_RGV24, or V4L2_PIX_FMT_YUV420 */
unsigned int requestedPixelFormat;
int width;
int height;
switch (capture->mode) {
case CV_CAP_MODE_RGB:
requestedPixelFormat = V4L2_PIX_FMT_RGB24;
width = capture->width;
height = capture->height;
break;
case CV_CAP_MODE_GRAY:
requestedPixelFormat = V4L2_PIX_FMT_YUV420;
width = capture->width;
height = capture->height;
break;
case CV_CAP_MODE_YUYV:
requestedPixelFormat = V4L2_PIX_FMT_YUYV;
break;
default:
requestedPixelFormat = V4L2_PIX_FMT_BGR24;
width = capture->width;
height = capture->height;
break;
}
CLEAR (capture->form);
capture->form.type = V4L2_BUF_TYPE_VIDEO_CAPTURE;
capture->form.fmt.pix.pixelformat = requestedPixelFormat;
capture->form.fmt.pix.field = V4L2_FIELD_ANY;
capture->form.fmt.pix.width = width;
capture->form.fmt.pix.height = height;
capture->form.fmt.pix.width = capture->width;
capture->form.fmt.pix.height = capture->height;
if (-1 == xioctl (capture->deviceHandle, VIDIOC_S_FMT, &capture->form)) {
fprintf(stderr, "VIDEOIO ERROR: libv4l unable to ioctl S_FMT\n");
@ -949,6 +946,10 @@ static int _capture_V4L (CvCaptureCAM_V4L *capture, char *deviceName)
requestedVideoPalette = VIDEO_PALETTE_YUV420;
depth = 8;
break;
case CV_CAP_MODE_YUYV:
requestedVideoPalette = VIDEO_PALETTE_YUYV;
depth = 16;
break;
default:
requestedVideoPalette = VIDEO_PALETTE_RGB24;
depth = 24;
@ -1319,6 +1320,7 @@ static IplImage* icvRetrieveFrameCAM_V4L( CvCaptureCAM_V4L* capture, int) {
switch(capture->imageProperties.palette) {
case VIDEO_PALETTE_RGB24:
case VIDEO_PALETTE_YUV420:
case VIDEO_PALETTE_YUYV:
memcpy((char *)capture->frame.imageData,
(char *)(capture->memoryMap + capture->memoryBuffer.offsets[capture->bufferIndex]),
capture->frame.imageSize);
@ -1464,6 +1466,10 @@ static int icvSetVideoSize( CvCaptureCAM_V4L* capture, int w, int h) {
cropHeight = h*8;
cropWidth = w*8;
break;
case CV_CAP_MODE_YUYV:
cropHeight = h*16;
cropWidth = w*16;
break;
default:
cropHeight = h*24;
cropWidth = w*24;
@ -1719,6 +1725,7 @@ static int icvSetPropertyCAM_V4L(CvCaptureCAM_V4L* capture, int property_id, dou
case CV_CAP_MODE_BGR:
case CV_CAP_MODE_RGB:
case CV_CAP_MODE_GRAY:
case CV_CAP_MODE_YUYV:
capture->mode = mode;
/* recreate the capture buffer for the same output resolution
but a different pixel format */

34
samples/python2/houghlines.py
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@ -18,23 +18,25 @@ src = cv2.imread(fn)
dst = cv2.Canny(src, 50, 200)
cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
# HoughLines()
# lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
# a,b,c = lines.shape
# for i in range(b):
# rho = lines[0][i][0]
# theta = lines[0][i][1]
# a = math.cos(theta)
# b = math.sin(theta)
# x0, y0 = a*rho, b*rho
# pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
# pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
# cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA)
if True: # HoughLinesP
lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 40, np.array([]), 50, 10)
a,b,c = lines.shape
for i in range(a):
cv2.line(cdst, (lines[i][0][0], lines[i][0][1]), (lines[i][0][2], lines[i][0][3]), (0, 0, 255), 3, cv2.LINE_AA)
else: # HoughLines
lines = cv2.HoughLines(dst, 1, math.pi/180.0, 50, np.array([]), 0, 0)
a,b,c = lines.shape
for i in range(a):
rho = lines[i][0][0]
theta = lines[i][0][1]
a = math.cos(theta)
b = math.sin(theta)
x0, y0 = a*rho, b*rho
pt1 = ( int(x0+1000*(-b)), int(y0+1000*(a)) )
pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA)
lines = cv2.HoughLinesP(dst, 1, math.pi/180.0, 50, np.array([]), 50, 10)
a,b,c = lines.shape
for i in range(b):
cv2.line(cdst, (lines[0][i][0], lines[0][i][1]), (lines[0][i][2], lines[0][i][3]), (0, 0, 255), 3, cv2.LINE_AA)
cv2.imshow("source", src)
cv2.imshow("detected lines", cdst)