def __get_color_histograms(self, src, args, bin_mask=None):
"""Executes :meth:`features.color_histograms`."""
histograms = []
for colorspace, bins in vars(args).iteritems():
if colorspace.lower() == "bgr":
colorspace = ft.CS_BGR
img = src
elif colorspace.lower() == "hsv":
colorspace = ft.CS_HSV
img = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
elif colorspace.lower() == "luv":
colorspace = ft.CS_LUV
img = cv2.cvtColor(src, cv2.COLOR_BGR2LUV)
else:
raise ValueError("Unknown colorspace '%s'" % colorspace)
hists = ft.color_histograms(img, bins, bin_mask, colorspace)
# Get the color space ranges. Correct for the exclusive upper
# boundaries.
ranges = np.array(ft.CS_RANGE[colorspace]).astype(float) - [0,1]
for i, hist in enumerate(hists):
# Normalize the features if a scaler is set.
if self.scaler:
self.scaler.fit(ranges[i])
hist = self.scaler.transform( hist.astype(float) )
histograms.extend( hist.ravel() )
return histograms
def __get_color_histograms(self, src, args, bin_mask=None):
"""Executes :meth:`features.color_histograms`."""
histograms = []
for colorspace, bins in vars(args).iteritems():
if colorspace.lower() == "bgr":
colorspace = ft.CS_BGR
img = src
elif colorspace.lower() == "hsv":
colorspace = ft.CS_HSV
img = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
elif colorspace.lower() == "luv":
colorspace = ft.CS_LUV
img = cv2.cvtColor(src, cv2.COLOR_BGR2LUV)
else:
raise ValueError("Unknown colorspace '%s'" % colorspace)
hists = ft.color_histograms(img, bins, bin_mask, colorspace)
# Get the color space ranges. Correct for the exclusive upper
# boundaries.
ranges = np.array(ft.CS_RANGE[colorspace]).astype(float) - [0, 1]
for i, hist in enumerate(hists):
# Normalize the features if a scaler is set.
if self.scaler:
self.scaler.fit(ranges[i])
hist = self.scaler.transform(hist.astype(float))
histograms.extend(hist.ravel())
return histograms
def main():
print __doc__
parser = argparse.ArgumentParser(description="Get image color statistics")
parser.add_argument("image", metavar="FILE", help="Input image")
args = parser.parse_args()
img = cv2.imread(args.image)
if img == None or img.size == 0:
sys.stderr.write("Failed to read %s\n" % args.image)
return 1
sys.stderr.write("Processing %s...\n" % args.image)
# Scale the image down if its perimeter exceeds the maximum.
img = common.scale_max_perimeter(img, 1000)
cs_str = "BGR"
hists = ft.color_histograms(img)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "BGR ranges:", get_min_max(img)
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
cs_str = "HSV"
hists = ft.color_histograms(img_hsv)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "HSV ranges:", get_min_max(img_hsv)
img_luv = cv2.cvtColor(img, cv2.COLOR_BGR2LUV)
cs_str = "Luv"
hists = ft.color_histograms(img_luv)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "LUV ranges:", get_min_max(img_luv)
return 0
def main():
print __doc__
parser = argparse.ArgumentParser(description='Get image color statistics')
parser.add_argument('image', metavar='FILE', help='Input image')
args = parser.parse_args()
img = cv2.imread(args.image)
if img == None or img.size == 0:
sys.stderr.write("Failed to read %s\n" % args.image)
return 1
sys.stderr.write("Processing %s...\n" % args.image)
# Scale the image down if its perimeter exceeds the maximum.
img = common.scale_max_perimeter(img, 1000)
cs_str = "BGR"
hists = ft.color_histograms(img)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "BGR ranges:", get_min_max(img)
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
cs_str = "HSV"
hists = ft.color_histograms(img_hsv)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "HSV ranges:", get_min_max(img_hsv)
img_luv = cv2.cvtColor(img, cv2.COLOR_BGR2LUV)
cs_str = "Luv"
hists = ft.color_histograms(img_luv)
for i, hist in enumerate(hists):
print "%s: %s" % (cs_str[i], hist.astype(int).ravel())
print "LUV ranges:", get_min_max(img_luv)
return 0
def get_color_histograms(self, src, args, bin_mask=None):
histograms = []
for colorspace, bins in vars(args).iteritems():
if colorspace.lower() == "bgr":
colorspace = ft.CS_BGR
img = src
elif colorspace.lower() == "hsv":
colorspace = ft.CS_HSV
img = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
elif colorspace.lower() == "luv":
colorspace = ft.CS_LUV
img = cv2.cvtColor(src, cv2.COLOR_BGR2LUV)
else:
raise ValueError("Unknown colorspace '%s'" % colorspace)
hists = ft.color_histograms(img, bins, bin_mask, colorspace)
for hist in hists:
hist = cv2.normalize(hist, None, -1, 1, cv2.NORM_MINMAX)
histograms.extend( hist.ravel() )
return histograms
