# compute which pixels are in the wanted range
cv.cvInRangeS (hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit (hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect (hue, selection)
mask_roi = cv.cvGetSubRect (mask, selection)
# it's time to compute the histogram
cv.cvCalcHist (hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val = cv.cvGetMinMaxHistValue (hist, None, None)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
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
# compute which pixels are in the wanted range
cv.cvInRangeS (hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit (hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect (hue, selection)
mask_roi = cv.cvGetSubRect (mask, selection)
# it's time to compute the histogram
cv.cvCalcHist (hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val, min_idx, max_idx = cv.cvGetMinMaxHistValue (hist)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
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
# compute which pixels are in the wanted range
cv.cvInRangeS(hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit(hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect(hue, selection)
mask_roi = cv.cvGetSubRect(mask, selection)
# it's time to compute the histogram
cv.cvCalcHist(hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val, min_idx, max_idx = cv.cvGetMinMaxHistValue(hist)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
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
# compute which pixels are in the wanted range
cv.cvInRangeS(hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit(hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect(hue, selection)
mask_roi = cv.cvGetSubRect(mask, selection)
# it's time to compute the histogram
cv.cvCalcHist(hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val = cv.cvGetMinMaxHistValue(hist, None, None)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
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
