def __findedge(self, filename):
tmpimg = highgui.cvLoadImage (filename)
self.img = cv.cvCreateImage(cv.cvSize(int(tmpimg.width * self.enlarge), int(tmpimg.height * self.enlarge)), 8, 3)
cv.cvResize(tmpimg, self.img, cv.CV_INTER_LINEAR)
if (self.drawimage):
self.drawimg = cv.cvCloneImage(self.img)
else:
self.drawimg = cv.cvCreateImage(cv.cvGetSize(self.img), 8, 3)
greyimg = cv.cvCreateImage(cv.cvSize(self.img.width, self.img.height), 8,1)
cv.cvCvtColor(self.img, greyimg, cv.CV_BGR2GRAY)
self.allcurve = []
for i in range(80, 200, 20):
bimg = cv.cvCloneImage(greyimg)
cv.cvSmooth(bimg, bimg, cv.CV_MEDIAN, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BILATERAL, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BLUR, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BLUR, 9)
cv.cvThreshold(greyimg, bimg, i, 255, cv.CV_THRESH_BINARY)
self.__findcurve(bimg)
def DrawKeyPoints(self):
if (not self.drawimg):
self.drawimg = cv.cvCloneImage(self.img)
myfont = cv.cvInitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 0.5, 0.5)
ic = 0
for c in self.points:
cv.cvPutText(self.drawimg, str(ic), cv.cvPoint(int(c.x), int(c.y)), myfont, cv.cvScalar(255, 255, 0,0))
ic += 1
cv.cvDrawCircle(self.drawimg, c, 4, cv.cvScalar(255,255,0,0))
def DrawKeyPoints(self):
if (not self.drawimg):
self.drawimg = cv.cvCloneImage(self.img)
myfont = cv.cvInitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 0.5, 0.5)
ic = 0
for c in self.points:
cv.cvPutText(self.drawimg, str(ic), cv.cvPoint(int(c.x), int(c.y)),
myfont, cv.cvScalar(255, 255, 0, 0))
ic += 1
cv.cvDrawCircle(self.drawimg, c, 4, cv.cvScalar(255, 255, 0, 0))
def __findedge(self, filename):
tmpimg = highgui.cvLoadImage(filename)
self.img = cv.cvCreateImage(
cv.cvSize(int(tmpimg.width * self.enlarge),
int(tmpimg.height * self.enlarge)), 8, 3)
cv.cvResize(tmpimg, self.img, cv.CV_INTER_LINEAR)
if (self.drawimage):
self.drawimg = cv.cvCloneImage(self.img)
else:
self.drawimg = cv.cvCreateImage(cv.cvGetSize(self.img), 8, 3)
greyimg = cv.cvCreateImage(cv.cvSize(self.img.width, self.img.height),
8, 1)
cv.cvCvtColor(self.img, greyimg, cv.CV_BGR2GRAY)
self.allcurve = []
for i in range(80, 200, 20):
bimg = cv.cvCloneImage(greyimg)
cv.cvSmooth(bimg, bimg, cv.CV_MEDIAN, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BILATERAL, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BLUR, 9)
# cv.cvSmooth(bimg, bimg, cv.CV_BLUR, 9)
cv.cvThreshold(greyimg, bimg, i, 255, cv.CV_THRESH_BINARY)
self.__findcurve(bimg)
def mask_image( im, mask ): if mask.depth == 8: bim = cv.cvCreateImage( cv.cvSize(mask.width, mask.height), cv.IPL_DEPTH_32F, mask.nChannels ) cv.cvConvertScale( mask, bim, 1.0/255.0) if im.depth == 8: newim = cv.cvCreateImage( cv.cvSize(im.width, im.height), cv.IPL_DEPTH_32F, im.nChannels ) cv.cvConvertScale( im, newim, 1.0/255.0) print 'newim.depth = ',newim.depth print 'newim.nChannels = ',newim.nChannels print 'bim.depth = ',bim.depth print 'bim.nChannels = ',bim.nChannels if newim.nChannels == 3 and newim.depth == 32 and bim.nChannels == 3 and bim.depth == 32: outputIm = cv.cvCloneImage( bim ) cv.cvMul( bim, newim, outputIm, 1 ) return outputIm else: print 'oops problem with formats' return mask
def mask_image(im, mask):
if mask.depth == 8:
bim = cv.cvCreateImage(cv.cvSize(mask.width, mask.height),
cv.IPL_DEPTH_32F, mask.nChannels)
cv.cvConvertScale(mask, bim, 1.0 / 255.0)
if im.depth == 8:
newim = cv.cvCreateImage(cv.cvSize(im.width, im.height),
cv.IPL_DEPTH_32F, im.nChannels)
cv.cvConvertScale(im, newim, 1.0 / 255.0)
print 'newim.depth = ', newim.depth
print 'newim.nChannels = ', newim.nChannels
print 'bim.depth = ', bim.depth
print 'bim.nChannels = ', bim.nChannels
if newim.nChannels == 3 and newim.depth == 32 and bim.nChannels == 3 and bim.depth == 32:
outputIm = cv.cvCloneImage(bim)
cv.cvMul(bim, newim, outputIm, 1)
return outputIm
else:
print 'oops problem with formats'
return mask
# right click on a location to see HSV thresholding result, left click anywhere to return to RGB image
import sys
sys.path.append('/usr/local/lib64/python2.6/site-packages')
import stereo
from opencv import highgui,cv
if len(sys.argv) >= 2:
imgorig = highgui.cvLoadImage(sys.argv[1])
img = cv.cvCloneImage(imgorig)
cv.cvCvtColor(img,img,cv.CV_RGB2HSV)
size = cv.cvGetSize(img)
IMGW = size.width
IMGH = size.height
fromfile = True
else:
fromfile = False
IMGW = 640
IMGH = 480
cap0 = highgui.cvCreateCameraCapture(0)
highgui.cvSetCaptureProperty(cap0, highgui.CV_CAP_PROP_FRAME_WIDTH, IMGW)
highgui.cvSetCaptureProperty(cap0, highgui.CV_CAP_PROP_FRAME_HEIGHT, IMGH)
joined = cv.cvCreateImage(cv.cvSize(IMGW,IMGH), 8, 3)
highgui.cvNamedWindow("Blob")
tx = 100
ty = 100
def detect_squares(self, img):
""" Find squares within the video stream and draw them """
N = 11
thresh = 5
sz = cv.cvSize(img.width & -2, img.height & -2)
timg = cv.cvCloneImage(img)
gray = cv.cvCreateImage(sz, 8, 1)
pyr = cv.cvCreateImage(cv.cvSize(sz.width / 2, sz.height / 2), 8, 3)
# create empty sequence that will contain points -
# 4 points per square (the square's vertices)
squares = cv.cvCreateSeq(0, cv.sizeof_CvSeq, cv.sizeof_CvPoint,
self.storage)
squares = cv.CvSeq_CvPoint.cast(squares)
# select the maximum ROI in the image
# with the width and height divisible by 2
subimage = cv.cvGetSubRect(timg, cv.cvRect(0, 0, sz.width, sz.height))
# down-scale and upscale the image to filter out the noise
cv.cvPyrDown(subimage, pyr, 7)
cv.cvPyrUp(pyr, subimage, 7)
tgray = cv.cvCreateImage(sz, 8, 1)
# find squares in every color plane of the image
for c in range(3):
# extract the c-th color plane
channels = [None, None, None]
channels[c] = tgray
cv.cvSplit(subimage, channels[0], channels[1], channels[2], None)
for l in range(N):
# hack: use Canny instead of zero threshold level.
# Canny helps to catch squares with gradient shading
if (l == 0):
# apply Canny. Take the upper threshold from slider
# and set the lower to 0 (which forces edges merging)
cv.cvCanny(tgray, gray, 0, thresh, 5)
# dilate canny output to remove potential
# holes between edge segments
cv.cvDilate(gray, gray, None, 1)
else:
# apply threshold if l!=0:
# tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
cv.cvThreshold(tgray, gray, (l + 1) * 255 / N, 255,
cv.CV_THRESH_BINARY)
# find contours and store them all as a list
count, contours = cv.cvFindContours(gray, self.storage,
cv.sizeof_CvContour,
cv.CV_RETR_LIST,
cv.CV_CHAIN_APPROX_SIMPLE,
cv.cvPoint(0, 0))
if not contours:
continue
# test each contour
for contour in contours.hrange():
# approximate contour with accuracy proportional
# to the contour perimeter
result = cv.cvApproxPoly(
contour, cv.sizeof_CvContour, self.storage,
cv.CV_POLY_APPROX_DP,
cv.cvContourPerimeter(contours) * 0.02, 0)
# square contours should have 4 vertices after approximation
# relatively large area (to filter out noisy contours)
# and be convex.
# Note: absolute value of an area is used because
# area may be positive or negative - in accordance with the
# contour orientation
if (result.total == 4
and abs(cv.cvContourArea(result)) > 1000
and cv.cvCheckContourConvexity(result)):
s = 0
for i in range(5):
# find minimum angle between joint
# edges (maximum of cosine)
if (i >= 2):
t = abs(
self.squares_angle(result[i],
result[i - 2],
result[i - 1]))
if s < t:
s = t
# if cosines of all angles are small
# (all angles are ~90 degree) then write quandrange
# vertices to resultant sequence
if (s < 0.3):
for i in range(4):
squares.append(result[i])
i = 0
while i < squares.total:
pt = []
# read 4 vertices
pt.append(squares[i])
pt.append(squares[i + 1])
pt.append(squares[i + 2])
pt.append(squares[i + 3])
# draw the square as a closed polyline
cv.cvPolyLine(img, [pt], 1, cv.CV_RGB(0, 255, 0), 3, cv.CV_AA, 0)
i += 4
return img
if __name__ == '__main__':
argc = len(sys.argv)
filename = "../c/stuff.jpg"
if (argc == 2):
filename = sys.argv[1]
slider_pos = 70
# load image and force it to be grayscale
image03 = highgui.cvLoadImage(filename, 0)
if not image03:
print "Could not load image " + filename
sys.exit(-1)
# Create the destination images
image02 = cv.cvCloneImage(image03)
image04 = cv.cvCloneImage(image03)
# Create windows.
highgui.cvNamedWindow("Source", 1)
highgui.cvNamedWindow("Result", 1)
# Show the image.
highgui.cvShowImage("Source", image03)
# Create toolbars. HighGUI use.
highgui.cvCreateTrackbar("Threshold", "Result", slider_pos, 255,
process_image)
process_image(1)
random.randrange (0, 5) * 0.1,
random.randrange (0, 10),
line_type)
cv.cvPutText (image, "Testing text rendering!",
pt1, font,
random_color (random))
highgui.cvShowImage (window_name, image)
highgui.cvWaitKey (delay)
# prepare a text, and get it's properties
font = cv.cvInitFont (cv.CV_FONT_HERSHEY_COMPLEX,
3, 3, 0.0, 5, line_type)
text_size, ymin = cv.cvGetTextSize ("OpenCV forever!", font)
pt1.x = (width - text_size.width) / 2
pt1.y = (height + text_size.height) / 2
image2 = cv.cvCloneImage(image)
# now, draw some OpenCV pub ;-)
for i in range (255):
cv.cvSubS (image2, cv.cvScalarAll (i), image, None)
cv.cvPutText (image, "OpenCV forever!",
pt1, font, cv.cvScalar (255, i, i))
highgui.cvShowImage (window_name, image)
highgui.cvWaitKey (delay)
# wait some key to end
highgui.cvWaitKey (0)
def on_trackbar1(position):
global pos1
global pos2
global pos3
global pos4
global pos5
global pos6
global pos7
global img
global gray
global edges
print
print position, pos2, pos3, pos4, pos5, pos6, pos7
temp = cv.cvCloneImage(img)
gray = cv.cvCreateImage(cv.cvGetSize(temp), 8, 1)
edges = cv.cvCreateImage(cv.cvGetSize(temp), 8, 1)
dst = cv.cvCreateImage( cv.cvSize(256,256), 8, 3 )
src = cv.cvCloneImage(img)
src2 = cv.cvCreateImage( cv.cvGetSize(src), 8, 3 );
cv.cvCvtColor(img, gray, cv.CV_BGR2GRAY)
cv.cvCanny(gray, edges, position, pos2, 3)
cv.cvSmooth(edges, edges, cv.CV_GAUSSIAN, 9, 9)
storage = cv.cvCreateMat(50, 1, cv.CV_32FC3)
cv.cvSetZero(storage)
try:
circles = cv.cvHoughCircles(gray, storage, cv.CV_HOUGH_GRADIENT, 1, float(pos3), float(pos2), float(pos4), long(pos5),long(pos6) )
#print storage
for i in storage:
print "Center: ", i[0], i[1], " Radius: ", i[2]
center = cv.cvRound(i[0]), cv.cvRound(i[1])
radius = cv.cvRound(i[2])
cv.cvCircle(temp, (center), radius, cv.CV_RGB(255, 0, 0), 1, cv.CV_AA, 0 )
cv.cvCircle(edges, (center), radius, cv.CV_RGB(255, 255, 255), 1, cv.CV_AA, 0 )
if radius > 200:
print "Circle found over 200 Radius"
center_crop_topleft = (center[0]-(radius - pos7)), (center[1]-(radius - pos7))
center_crop_bottomright = (center[0]+(radius - pos7)), (center[1]+(radius - pos7))
print "crop top left: ", center_crop_topleft
print "crop bottom right: ", center_crop_bottomright
center_crop = cv.cvGetSubRect(src, (center_crop_topleft[0], center_crop_topleft[1] , (center_crop_bottomright[0] - center_crop_topleft[0]), (center_crop_bottomright[1] - center_crop_topleft[1]) ))
#center_crop = cv.cvGetSubRect(src, (50, 50, radius/2, radius/2))
cvShowImage( "center_crop", center_crop )
print "center_crop created"
#mark found circle's center with blue point and blue circle of pos 7 radius
cv.cvCircle(temp ,(center), 2, cv.CV_RGB(0, 0, 255), 3, cv.CV_AA, 0 )
cv.cvCircle(temp ,(center), (radius - pos7), cv.CV_RGB(0, 0, 255), 3, cv.CV_AA, 0 )
#cvLogPolar(src, dst, (center), 48, CV_INTER_LINEAR +CV_WARP_FILL_OUTLIERS )
#this will draw a smaller cirle outlining the center circle
#pos7 = int(pos7 /2.5)
#cv.cvCircle(dst ,(img_size.width-pos7, 0), 2, cv.CV_RGB(0, 0, 255), 3, cv.CV_AA, 0 )
#cv.cvLine(dst, (img_size.width-pos7-1, 0), (img_size.width-pos7-1, img_size.height), cv.CV_RGB(0, 0, 255),1,8,0)
#cvShowImage( "log-polar", dst )
#print radius, (radius-pos7)
#cropped = cv.cvCreateImage( (pos7, img_size.height), 8, 3)
#cropped2 = cv.cvCreateImage( (pos7, img_size.height), 8, 3)
#coin_edge_img = cv.cvGetSubRect(dst, (img_size.width-pos7, 0, pos7 ,img_size.height ))
#to create the center cropped part of coin
#img_size = cvGetSize(scr)
#cvCopy(coin_edge_img, cropped)
#cvSaveImage("temp.png", cropped)
#im = Image.open("temp.png").rotate(90)
#print "pil image size = ", im.size[0], im.size[1]
#im = im.resize((im.size[0]*2, im.size[1]*2))
#print "pil image size = ", im.size
#im.show()
#im.save("temp2.png")
cropped2 = highgui.cvLoadImage("temp2.png")
#cvShowImage( "cropped", cropped2)
except:
print "Exception:", sys.exc_info()[0]
print position, pos2, pos3, pos4, pos5, pos6, pos7
pass
highgui.cvShowImage("edges", edges)
#cvShowImage( "log-polar", dst )
cvShowImage(wname, temp)
def atualizeVar(self, frameA, frameB, frameC, capture):
frameA = cvCloneImage(frameB)
frameB = cvCloneImage(frameC)
frameC = cvQueryFrame(capture)
return frameA, frameB, frameC
if __name__ == '__main__':
argc = len(sys.argv)
filename = "../c/stuff.jpg"
if(argc == 2):
filename = sys.argv[1]
slider_pos = 70
# load image and force it to be grayscale
image03 = highgui.cvLoadImage(filename, 0)
if not image03:
print "Could not load image " + filename
sys.exit(-1)
# Create the destination images
image02 = cv.cvCloneImage( image03 );
image04 = cv.cvCloneImage( image03 );
# Create windows.
highgui.cvNamedWindow("Source", 1);
highgui.cvNamedWindow("Result", 1);
# Show the image.
highgui.cvShowImage("Source", image03);
# Create toolbars. HighGUI use.
highgui.cvCreateTrackbar( "Threshold", "Result", slider_pos, 255, process_image );
process_image( 1 );
break
################ traitement de l'image ################
cv.cvCvtColor(frame, frameGray, cv.CV_BGR2GRAY)
# niveau de gris
cv.cvSub(frameGray, frameGrayBg, framewithoutbg)
# soustraction du background
cv.cvMul(framewithoutbg, framewithoutbg, framemul, get_gain())
# amplification
cv.cvSmooth(framemul, framelisser1, cv.CV_BLUR, param_liss[0],
param2_liss[0])
# lissage
if first == 0: # "moyenne" sur deux image
cv.cvAnd(framelisser1, framelisser2, framelisser)
if first == 1:
framelisser = cv.cvCloneImage(framelisser1)
framelisser2 = cv.cvCloneImage(framelisser1)
cv.cvThreshold(framelisser, frameBin, get_seuil(), float(255),
cv.CV_THRESH_BINARY) # binaristaion de l image
################ run detection ################
zone_active = zoneActivePremier(zone_active, frameBin)
if len(zone_active) == 0:
centrePointeur = []
info_size = []
if len(zone_active) != 0:
for i in range(1, nb_div_zone[0] + 1):
zone_active = zoneActive(zone_active, frameBin, i)
pointeur = pointeurPrecision(zone_active, frameBin)
random.randrange (0, 100) * 0.05 + 0.01,
random.randrange (0, 5) * 0.1,
random.randrange (0, 10),
line_type)
cv.cvPutText (image, "Testing text rendering!",
pt1, font,
random_color (random))
highgui.cvShowImage (window_name, image)
highgui.cvWaitKey (delay)
# prepare a text, and get it's properties
font = cv.cvInitFont (cv.CV_FONT_HERSHEY_COMPLEX,
3, 3, 0.0, 5, line_type)
text_size, ymin = cv.cvGetTextSize ("OpenCV forever!", font)
pt1.x = (width - text_size.width) / 2
pt1.y = (height + text_size.height) / 2
image2 = cv.cvCloneImage(image)
# now, draw some OpenCV pub ;-)
for i in range (255):
cv.cvSubS (image2, cv.cvScalarAll (i), image, None)
cv.cvPutText (image, "OpenCV forever!",
pt1, font, cv.cvScalar (255, i, i))
highgui.cvShowImage (window_name, image)
highgui.cvWaitKey (delay)
# wait some key to end
highgui.cvWaitKey (0)
def main():
print "OpenCV version: %s (%d, %d, %d)" % (cv.CV_VERSION,
cv.CV_MAJOR_VERSION,
cv.CV_MINOR_VERSION,
cv.CV_SUBMINOR_VERSION)
# create windows
create_and_position_window('Thresholded_HSV_Image', 10, 10)
create_and_position_window('RGB_VideoFrame', 10+cam_width, 10)
create_and_position_window('Hue', 10, 10+cam_height)
create_and_position_window('Saturation', 210, 10+cam_height)
create_and_position_window('Value', 410, 10+cam_height)
create_and_position_window('LaserPointer', 0,0)
capture = setup_camera_capture()
# create images for the different channels
h_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
s_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
v_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
laser_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
cv.cvSetZero(h_img)
cv.cvSetZero(s_img)
cv.cvSetZero(v_img)
cv.cvSetZero(laser_img)
while True:
# 1. capture the current image
frame = highgui.cvQueryFrame (capture)
if frame is None:
# no image captured... end the processing
break
hsv_image = cv.cvCloneImage(frame) # temporary copy of the frame
cv.cvCvtColor(frame, hsv_image, cv.CV_BGR2HSV) # convert to HSV
# split the video frame into color channels
cv.cvSplit(hsv_image, h_img, s_img, v_img, None)
# Threshold ranges of HSV components.
cv.cvInRangeS(h_img, hmin, hmax, h_img)
cv.cvInRangeS(s_img, smin, smax, s_img)
cv.cvInRangeS(v_img, vmin, vmax, v_img)
# Perform an AND on HSV components to identify the laser!
cv.cvAnd(h_img, v_img, laser_img)
# This actually Worked OK for me without using Saturation.
#cv.cvAnd(laser_img, s_img,laser_img)
# Merge the HSV components back together.
cv.cvMerge(h_img, s_img, v_img, None, hsv_image)
#-----------------------------------------------------
# NOTE: default color space in OpenCV is BGR!!
# we can now display the images
highgui.cvShowImage ('Thresholded_HSV_Image', hsv_image)
highgui.cvShowImage ('RGB_VideoFrame', frame)
highgui.cvShowImage ('Hue', h_img)
highgui.cvShowImage ('Saturation', s_img)
highgui.cvShowImage ('Value', v_img)
highgui.cvShowImage('LaserPointer', laser_img)
# handle events
k = highgui.cvWaitKey (10)
if k == '\x1b' or k == 'q':
# user has press the ESC key, so exit
break
def detect_squares(self, img_grey, img_orig): """ Find squares within the video stream and draw them """ cv.cvClearMemStorage(self.faces_storage) N = 11 thresh = 5 sz = cv.cvSize(img_grey.width & -2, img_grey.height & -2) timg = cv.cvCloneImage(img_orig) pyr = cv.cvCreateImage(cv.cvSize(sz.width/2, sz.height/2), 8, 3) # create empty sequence that will contain points - # 4 points per square (the square's vertices) squares = cv.cvCreateSeq(0, cv.sizeof_CvSeq, cv.sizeof_CvPoint, self.squares_storage) squares = cv.CvSeq_CvPoint.cast(squares) # select the maximum ROI in the image # with the width and height divisible by 2 subimage = cv.cvGetSubRect(timg, cv.cvRect(0, 0, sz.width, sz.height)) cv.cvReleaseImage(timg) # down-scale and upscale the image to filter out the noise cv.cvPyrDown(subimage, pyr, 7) cv.cvPyrUp(pyr, subimage, 7) cv.cvReleaseImage(pyr) tgrey = cv.cvCreateImage(sz, 8, 1) # find squares in every color plane of the image for c in range(3): # extract the c-th color plane channels = [None, None, None] channels[c] = tgrey cv.cvSplit(subimage, channels[0], channels[1], channels[2], None) for l in range(N): # hack: use Canny instead of zero threshold level. # Canny helps to catch squares with gradient shading if(l == 0): # apply Canny. Take the upper threshold from slider # and set the lower to 0 (which forces edges merging) cv.cvCanny(tgrey, img_grey, 0, thresh, 5) # dilate canny output to remove potential # holes between edge segments cv.cvDilate(img_grey, img_grey, None, 1) else: # apply threshold if l!=0: # tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 cv.cvThreshold(tgrey, img_grey, (l+1)*255/N, 255, cv.CV_THRESH_BINARY) # find contours and store them all as a list count, contours = cv.cvFindContours(img_grey, self.squares_storage, cv.sizeof_CvContour, cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_SIMPLE, cv.cvPoint(0,0)) if not contours: continue # test each contour for contour in contours.hrange(): # approximate contour with accuracy proportional # to the contour perimeter result = cv.cvApproxPoly(contour, cv.sizeof_CvContour, self.squares_storage, cv.CV_POLY_APPROX_DP, cv.cvContourPerimeter(contours)*0.02, 0) # square contours should have 4 vertices after approximation # relatively large area (to filter out noisy contours) # and be convex. # Note: absolute value of an area is used because # area may be positive or negative - in accordance with the # contour orientation if(result.total == 4 and abs(cv.cvContourArea(result)) > 1000 and cv.cvCheckContourConvexity(result)): s = 0 for i in range(5): # find minimum angle between joint # edges (maximum of cosine) if(i >= 2): t = abs(self.squares_angle(result[i], result[i-2], result[i-1])) if s<t: s = t # if cosines of all angles are small # (all angles are ~90 degree) then write quandrange # vertices to resultant sequence if(s < 0.3): for i in range(4): squares.append(result[i]) cv.cvReleaseImage(tgrey) return squares
def clone_image(self,image): return cv.cvCloneImage(image)
def atualizeVar(self, frameA, frameB, frameC, capture):
frameA = cvCloneImage(frameB)
frameB = cvCloneImage(frameC)
frameC = cvQueryFrame(capture)
return frameA, frameB, frameC
highgui.cvCreateTrackbar("Canny2", wname, 175, 250, on_trackbar2)
highgui.cvCreateTrackbar("minDistance", wname, 40, 150, on_trackbar3)
highgui.cvCreateTrackbar("accumThresh", wname, 55, 100, on_trackbar4)
highgui.cvCreateTrackbar("minRadius", wname, 190, 500, on_trackbar5)
highgui.cvCreateTrackbar("maxRadius", wname, 210, 1200, on_trackbar6)
highgui.cvCreateTrackbar("SearchRadius", wname, 50, 100, on_trackbar7)
pos1 = highgui.cvGetTrackbarPos("Canny1", wname)
pos2 = highgui.cvGetTrackbarPos("Canny2", wname)
pos3 = highgui.cvGetTrackbarPos("minDistance", wname)
pos4 = highgui.cvGetTrackbarPos("accumThresh", wname)
pos5 = highgui.cvGetTrackbarPos("minRadius", wname)
pos6 = highgui.cvGetTrackbarPos("maxRadius", wname)
pos7 = highgui.cvGetTrackbarPos("SearchRadius", wname)
pos1 = int(pos2/2)
highgui.cvSetTrackbarPos("Canny1", wname, pos1)
on_trackbar1(pos1)
#highgui.cvNamedWindow( "original",1 );
#highgui.cvNamedWindow( "log-polar", 1 );
#highgui.cvNamedWindow( "inverse log-polar", 1 );
dst = cv.cvCreateImage( cv.cvSize(256,256), 8, 3 );
src = cv.cvCloneImage(img)
src2 = cv.cvCreateImage( cv.cvGetSize(src), 8, 3 );
#cvShowImage( "original", src );
highgui.cvSetMouseCallback( "original", on_mouse );
on_mouse( CV_EVENT_LBUTTONDOWN, src.width/2, src.height/2, None, None)
highgui.cvWaitKey()