def test_npz_2d(self):
ftmp = NamedTemporaryFile(suffix='.npz', delete=False)
try:
ftmp.close()
h = Histogram(3, [0, 3], 4, [0, 4])
h.data[:] = [[-3, 0, 5, 3], [-2, 0, 4, 2], [-1, 0, 3, 1024]]
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.axes[0].label = 'x (cm)'
h.axes[1].label = 'y (cm)'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.label = 'counts'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.title = 'title'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
finally:
os.remove(ftmp.name)
def test_root_2d(self):
ftmp = NamedTemporaryFile(suffix='.root', delete=False)
try:
ftmp.close()
h = Histogram(3, [0, 3], 4, [0, 4])
h.data[:] = [[-3, 0, 5, 3], [-2, 0, 4, 2], [-1, 0, 3, 1024]]
h.uncert = np.sqrt(np.abs(
h.data)) # ROOT will always return uncert
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.axes[0].label = 'x (cm)'
h.axes[1].label = 'y (cm)'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.label = 'counts'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.title = 'title'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
finally:
os.remove(ftmp.name)
def test_hist_1d(self):
ftmp = NamedTemporaryFile(suffix='.h5', delete=False)
try:
ftmp.close()
h = Histogram(3, [0, 3])
h.data[:] = [-3, 0, 5]
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.axes[0].label = 'x (cm)'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
#print(type(h.axes[0].label), h.axes[0].label)
#print(type(htmp.axes[0].label), htmp.axes[0].label)
self.assertTrue(h.isidentical(htmp))
h.label = 'counts'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.title = 'title'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
h.uncert = [2, 3, 4]
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
finally:
os.remove(ftmp.name)
def load_hue_histograms(self):
for h in self.known_histograms.keys():
hist = Histogram()
hist.load(self.known_histograms[h][0])
self.known_histograms[h][1] = hist
for h in self.known_histograms:
print h
print self.known_histograms[h][1]
def test_hdf5(self):
try:
import h5py
h = self.h.clone()
filename = 'h.hdf5'
h.save(filename)
hh = Histogram.load(filename)
assert h.isidentical(hh)
except ImportError:
pass
class SkinDetector:
def __init__(self, topic=DEF_TOPIC_NAME, hist_file=DEF_HISTOGRAM_FILE):
rospy.init_node("skin_detection", anonymous=True)
rospy.Subscriber(topic, Image, self.rgb_cb)
cv2.namedWindow("wnd_orig")
cv2.namedWindow("wnd_prob")
cv2.namedWindow("wnd_skin")
self.skin_threshold = 127
cv2.createTrackbar("track_skin", "wnd_skin", self.skin_threshold, 255, self.on_skin_track)
rospy.on_shutdown(self.on_shutdown)
self.hist = Histogram()
self.hist.load(hist_file)
def on_skin_track(self, pos, *argv):
self.skin_threshold = pos
def find_skin(self, img):
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
mask = hsv_filter_mask(img_hsv)
back_proj = calc_back_proj(img_hsv, self.hist.hist, hsv=True)
back_proj &= mask
skin_bin = cv2.threshold(back_proj, self.skin_threshold, 255, cv2.THRESH_BINARY)
return (back_proj, skin_bin[1])
def rgb_cb(self, msg):
try:
img = bridge.imgmsg_to_cv(msg, "bgr8")
img = np.asarray(img)
except CvBridgeError, e:
print >> stderr, "Cannot convert from ROS msg to CV image:", e
(img_prob, img_skin) = self.find_skin(img)
cv2.imshow("wnd_orig", img)
cv2.imshow("wnd_prob", img_prob)
cv2.imshow("wnd_skin", img_skin)
ch = cv2.waitKey(3)
if ch == 27:
rospy.signal_shutdown("Quit")
elif ch == ord(" "):
cv2.imwrite("img_prob.png", img_prob)
def test_unicode(self):
ftmp = NamedTemporaryFile(suffix='.npz', delete=False)
try:
h = Histogram(3, [0, 3])
h.data[:] = [-3, 0, 5]
h.title = 'χ-squared'
h.label = 'αβγ'
h.axes[0].label = 'θ'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
finally:
os.remove(ftmp.name)
def test_unicode(self):
ftmp = NamedTemporaryFile(suffix='.root', delete=False)
try:
ftmp.close()
h = Histogram(3, [0, 3])
h.data[:] = [-3, 0, 5]
h.uncert = np.sqrt(np.abs(
h.data)) # ROOT will always return uncert
h.title = 'χ-squared'
h.label = 'αβγ'
h.axes[0].label = 'θ'
h.save(ftmp.name)
htmp = Histogram.load(ftmp.name)
self.assertTrue(h.isidentical(htmp))
finally:
os.remove(ftmp.name)
def test_root(self):
# For CERN/ROOT, we resorted to converting everything
# into float64's so histograms are not typically
# "identical" but they should be "close"
try:
import ROOT
h = self.h.clone()
filename = 'h.root'
self.h.save(filename)
hh = Histogram.load(filename)
assert np.allclose(h.data,hh.data)
assert np.allclose(h.uncert,hh.uncert)
assert h.label == hh.label
assert h.title == hh.title
for a,aa in zip(h.axes,hh.axes):
assert np.allclose(a.edges,aa.edges)
assert a.label == aa.label
except ImportError:
pass
def _to_unicode(s):
if not isinstance(s,unicode):
return unicode(s,'utf-8')
else:
return s
h.title = _to_unicode(h.title)
h.label = _to_unicode(h.label)
for ax in h.axes:
ax.label = _to_unicode(ax.label)
infiles = ['h2','h3','h2.hdf5','h3.hdf5']
for infile in infiles:
print(infile)
hh = Histogram.load(infile)
assert h.isidentical(hh)
# For CERN/ROOT, we resorted to converting everything
# into float64's so histograms are not typically
# "identical" but they should be "close"
infiles = ['h2.root','h3.root']
for infile in infiles:
print(infile)
hh = Histogram.load(infile)
assert np.allclose(h.data,hh.data)
assert np.allclose(h.uncert,hh.uncert)
assert h.label == hh.label
assert h.title == hh.title
def test_npz(self):
h = self.h.clone()
filename = 'h'
h.save(filename)
hh = Histogram.load(filename)
assert h.isidentical(hh)
