def process(self, videofile, progress):
progress(0, _("Extracting histogram"))
video = hg.cvCreateFileCapture(str(videofile).encode(sys.getfilesystemencoding()))
if not video:
raise Exception("Could not open video file")
histo = cv.cvCreateHist([256],cv.CV_HIST_ARRAY,[[0,256]], 1)
frame = hg.cvQueryFrame(video)
frame_gray = cv.cvCreateImage(cv.cvGetSize(frame), frame.depth, 1);
hists = []
nbframes = 0
fps = hg.cvGetCaptureProperty(video, hg.CV_CAP_PROP_FPS)
while frame :
if not progress(hg.cvGetCaptureProperty(video, hg.CV_CAP_PROP_POS_AVI_RATIO)):
break
hg.cvConvertImage(frame,frame_gray)
cv.cvCalcHist(frame_gray,histo,0,None)
h = [cv.cvGetReal1D(histo.bins,i) for i in range(255) ]
h = numpy.array(h,dtype='int32')
hists.append(h)
frame = hg.cvQueryFrame(video)
nbframes += 1
hists = numpy.array(hists)
return hists.reshape(nbframes, -1), fps
scale = 0.
# scale the histograms
cv.cvConvertScale (hist.bins, hist.bins, scale, 0)
# clear the histogram image
cv.cvSetZero (histimg)
# compute the width for each bin do display
bin_w = histimg.width / hdims
for i in range (hdims):
# for all the bins
# 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)
# we can now display the images
highgui.cvShowImage ('Camera', frame)
highgui.cvShowImage ('Histogram', histimg)
# scale the histograms
cv.cvConvertScale(hist.bins, hist.bins, scale, 0)
# clear the histogram image
cv.cvSetZero(histimg)
# compute the width for each bin do display
bin_w = histimg.width / hdims
for i in range(hdims):
# for all the bins
# 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
scale = 0.
# scale the histograms
cv.cvConvertScale (hist.bins, hist.bins, scale, 0)
# clear the histogram image
cv.cvSetZero (histimg)
# compute the width for each bin do display
bin_w = histimg.width / hdims
for i in range (hdims):
# for all the bins
# 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)
# we can now display the images
highgui.cvShowImage ('Camera', frame)
highgui.cvShowImage ('Histogram', histimg)
scale = 0.0
# scale the histograms
cv.cvConvertScale(hist.bins, hist.bins, scale, 0)
# clear the histogram image
cv.cvSetZero(histimg)
# compute the width for each bin do display
bin_w = histimg.width / hdims
for i in range(hdims):
# for all the bins
# 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 * 180.0 / 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,
)
# calculate histogram
cv.cvCalcHist(img_h, h_hue, 0, thresh_mask)
cv.cvCalcHist(img_s, h_sat, 0, thresh_mask)
cv.cvCalcHist(img_v, h_val, 0, thresh_mask)
# Don't normalize, use total mask pixels to calculate relative importance
# cv.cvNormalizeHist(h_hue, 180)
# cv.cvNormalizeHist(h_sat, 255)
# cv.cvNormalizeHist(h_val, 255)
# minv,maxv,minp,maxp = cv.cvMinMaxLoc(img_h)
# print minv,maxv
cv.cvZero(hist_hue_img)
# hue_min,hue_max,min_loc,max_loc = cv.cvGetMinMaxHistValue(h_hue)
for h in xrange(h_bins):
hue = cv.cvGetReal1D(h_hue.bins, h)
color = hsv2rgb(h * h_limit / h_bins)
cv.cvRectangle(
hist_hue_img,
(h * scalewidth, 0),
((h + 1) * scalewidth, (hue / sample_pixels) * scaleheight),
color,
cv.CV_FILLED,
)
cv.cvLine(
hist_hue_img,
(0, scaleheight * hue_cutoff / sample_pixels),
(h_bins * scalewidth, scaleheight * hue_cutoff / sample_pixels),
(255, 0, 0),
1,
)