# get the value, and scale to the size of the hist image
val = cv.cvRound(
cv.cvGetReal1D(hist.bins, i) * histimg.height / 255)
# compute the color
color = hsv2rgb(i * 180. / hdims)
# draw the rectangle in the wanted color
cv.cvRectangle(histimg, cv.cvPoint(i * bin_w, histimg.height),
cv.cvPoint((i + 1) * bin_w, histimg.height - val),
color, -1, 8, 0)
# Make the sweet negative selection box
if mouse_select_object and mouse_selection.width > 0 and mouse_selection.height > 0:
a = cv.cvGetSubRect(frame, mouse_selection)
cv.cvXorS(a, cv.cvScalarAll(255),
a) # Take the negative of the image..
del a
# Carry out the histogram tracking...
if track_object != 0:
cv.cvInRangeS(hsv, cv.cvScalar(0, smin, min(vmin, vmax), 0),
cv.cvScalar(180, 256, max(vmin, vmax), 0), mask)
cv.cvSplit(hsv, hue, None, None, None)
if track_object < 0:
# Calculate the histogram for the mouse_selection box
hue_roi_rect = cv.cvGetSubRect(hue, mouse_selection)
mask_roi_rect = cv.cvGetSubRect(mask, mouse_selection)
cv.cvCalcHist(hue_roi_rect, obj_hist, 0, mask_roi_rect)
min_val, max_val, min_idx, max_idx = cv.cvGetMinMaxHistValue(
obj_hist)
# get the value, and scale to the size of the hist image
val = cv.cvRound (cv.cvGetReal1D (hist.bins, i)
* histimg.height / 255)
# compute the color
color = hsv2rgb (i * 180. / hdims)
# draw the rectangle in the wanted color
cv.cvRectangle (histimg,
cv.cvPoint (i * bin_w, histimg.height),
cv.cvPoint ((i + 1) * bin_w, histimg.height - val),
color, -1, 8, 0)
# Make the sweet negative selection box
if mouse_select_object and mouse_selection.width > 0 and mouse_selection.height > 0:
a = cv.cvGetSubRect(frame,mouse_selection)
cv.cvXorS(a,cv.cvScalarAll(255), a) # Take the negative of the image..
del a
# Carry out the histogram tracking...
if track_object != 0:
cv.cvInRangeS( hsv, cv.cvScalar(0,smin ,min(vmin, vmax), 0), cv.cvScalar(180, 256, max(vmin,vmax), 0), mask )
cv.cvSplit(hsv, hue, None, None, None)
if track_object < 0:
# Calculate the histogram for the mouse_selection box
hue_roi_rect = cv.cvGetSubRect( hue, mouse_selection )
mask_roi_rect = cv.cvGetSubRect( mask, mouse_selection )
cv.cvCalcHist (hue_roi_rect, obj_hist, 0, mask_roi_rect)
min_val, max_val, min_idx, max_idx = cv.cvGetMinMaxHistValue (obj_hist)
track_window = mouse_selection
cv.cvEllipseBox(image, track_box, cv.CV_RGB(255,0,0), 3, cv.CV_AA, 0)
if (track_box.size.width > 10 or track_box.size.height > 10):
rotate = ( (image.width/2.0) - track_box.center.x) / (image.width/2.0)
translate = ((image.height/2.0) - track_box.center.y) / (image.height/2.0)
#print "rotate =", rotate, "translate =", translate
if go:
move(translate, rotate)
if select_object and selection.width > 0 and selection.height > 0:
subimg = cv.cvGetSubRect(image, selection)
cv.cvXorS( subimage, cv.cvScalarAll(255), subimage, 0 )
highgui.cvShowImage( "VisualJoystick", image )
c = highgui.cvWaitKey(10)
if c == '\x1b':
break
elif c == 'b':
backproject_mode ^= 1
elif c == 'c':
track_object = 0
cv.cvZero( histimg )
if go:
stop()
if go:
if (track_box.size.width > 10 or track_box.size.height > 10):
rotate = ((image.width / 2.0) -
track_box.center.x) / (image.width / 2.0)
translate = ((image.height / 2.0) -
track_box.center.y) / (image.height / 2.0)
#print "rotate =", rotate, "translate =", translate
if go:
move(translate, rotate)
if select_object and selection.width > 0 and selection.height > 0:
subimg = cv.cvGetSubRect(image, selection)
cv.cvXorS(subimage, cv.cvScalarAll(255), subimage, 0)
highgui.cvShowImage("VisualJoystick", image)
c = highgui.cvWaitKey(10)
if c == '\x1b':
break
elif c == 'b':
backproject_mode ^= 1
elif c == 'c':
track_object = 0
cv.cvZero(histimg)
if go:
stop()
if go:
