def test_scheduling_limits(self):
global best_score
from kivy.clock import Clock
gdb = Recognizer(db=[self.Ninvar])
tpls = len(self.Ninvar.templates)
best_score = 0
gdb.db.append(self.Ninvar)
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
self.assertEqual(r.progress, 0)
Clock.tick()
self.assertEqual(r.progress, 0.5)
self.assertEqual(best_score, 0)
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
best_score = 0
gdb.db.append(self.Ninvar)
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
self.assertEqual(r.progress, 0)
Clock.tick()
self.assertEqual(r.progress, 1 / 3.)
Clock.tick()
self.assertEqual(r.progress, 2 / 3.)
self.assertEqual(best_score, 0)
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
def test_scheduling_limits(self):
global best_score
from kivy.clock import Clock
gdb = Recognizer(db=[self.Ninvar])
tpls = len(self.Ninvar.templates)
best_score = 0
gdb.db.append(self.Ninvar)
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
self.assertEqual(r.progress, 0)
Clock.tick()
self.assertEqual(r.progress, 0.5)
self.assertEqual(best_score, 0)
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
best_score = 0
gdb.db.append(self.Ninvar)
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
self.assertEqual(r.progress, 0)
Clock.tick()
self.assertEqual(r.progress, 1 / 3.)
Clock.tick()
self.assertEqual(r.progress, 2 / 3.)
self.assertEqual(best_score, 0)
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
def test_protractor_bound(self):
gdb = Recognizer(db=[self.Tbound, self.Nbound])
r = gdb.recognize([NGesture], orientation_sensitive=True, max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] >= 0.99)
r = gdb.recognize([NGesture], orientation_sensitive=False, max_gpf=0)
self.assertEqual(r.best['name'], None)
self.assertEqual(r.best['score'], 0)
r = gdb.recognize([Ncandidate], orientation_sensitive=True, max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_immediate(self):
gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r._match_ops, 4)
self.assertEqual(r._completed, 2)
self.assertEqual(r.progress, 1)
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_protractor_bound(self):
gdb = Recognizer(db=[self.Tbound, self.Nbound])
r = gdb.recognize([NGesture], orientation_sensitive=True,
max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] >= 0.99)
r = gdb.recognize([NGesture], orientation_sensitive=False,
max_gpf=0)
self.assertEqual(r.best['name'], None)
self.assertEqual(r.best['score'], 0)
r = gdb.recognize([Ncandidate], orientation_sensitive=True,
max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_immediate(self):
gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r._match_ops, 4)
self.assertEqual(r._completed, 2)
self.assertEqual(r.progress, 1)
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_transfer(self):
gdb1 = Recognizer(db=[self.Ninvar])
gdb2 = Recognizer()
gdb1.transfer_gesture(gdb2, name='N')
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_transfer(self):
gdb1 = Recognizer(db=[self.Ninvar])
gdb2 = Recognizer()
gdb1.transfer_gesture(gdb2, name='N')
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_export_import_case_1(self):
gdb1 = Recognizer(db=[self.Ninvar])
gdb2 = Recognizer()
g = gdb1.export_gesture(name='N')
gdb2.import_gesture(g)
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_export_import_case_1(self):
gdb1 = Recognizer(db=[self.Ninvar])
gdb2 = Recognizer()
g = gdb1.export_gesture(name='N')
gdb2.import_gesture(g)
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_priority_sorting(self):
gdb = Recognizer()
gdb.add_gesture('N', [NGesture], priority=10)
gdb.add_gesture('T', [TGesture], priority=5)
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
force_priority_sort=True)
self.assertEqual(r.best['name'], 'T')
r = gdb.recognize([Ncandidate], goodscore=0.01,
force_priority_sort=False, max_gpf=0)
self.assertEqual(r.best['name'], 'N')
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
priority=10)
self.assertEqual(r.best['name'], 'T')
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
priority=4)
self.assertEqual(r.best['name'], None)
def test_priority_sorting(self):
gdb = Recognizer()
gdb.add_gesture('N', [NGesture], priority=10)
gdb.add_gesture('T', [TGesture], priority=5)
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
force_priority_sort=True)
self.assertEqual(r.best['name'], 'T')
r = gdb.recognize([Ncandidate], goodscore=0.01,
force_priority_sort=False, max_gpf=0)
self.assertEqual(r.best['name'], 'N')
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
priority=10)
self.assertEqual(r.best['name'], 'T')
r = gdb.recognize([Ncandidate], goodscore=0.01, max_gpf=0,
priority=4)
self.assertEqual(r.best['name'], None)
def test_parallel_recognize(self):
global counter
from kivy.clock import Clock
counter = 0
gdb = Recognizer()
for i in range(9):
gdb.add_gesture('T', [TGesture], priority=50)
gdb.add_gesture('N', [NGesture])
r1 = gdb.recognize([Ncandidate], max_gpf=1)
r1.bind(on_complete=counter_cb)
Clock.tick() # first run scheduled here; 9 left
r2 = gdb.recognize([Ncandidate], max_gpf=1)
r2.bind(on_complete=counter_cb)
Clock.tick() # 8 left
r3 = gdb.recognize([Ncandidate], max_gpf=1)
r3.bind(on_complete=counter_cb)
Clock.tick() # 7 left
# run some immediate searches, should not interfere.
for i in range(5):
n = gdb.recognize([TGesture], max_gpf=0)
self.assertEqual(n.best['name'], 'T')
self.assertTrue(round(n.best['score'], 1) == 1.0)
for i in range(6):
Clock.tick()
self.assertEqual(counter, 0)
Clock.tick()
self.assertEqual(counter, 1)
Clock.tick()
self.assertEqual(counter, 2)
Clock.tick()
self.assertEqual(counter, 3)
def test_parallel_recognize(self):
global counter
from kivy.clock import Clock
counter = 0
gdb = Recognizer()
for i in range(9):
gdb.add_gesture('T', [TGesture], priority=50)
gdb.add_gesture('N', [NGesture])
r1 = gdb.recognize([Ncandidate], max_gpf=1)
r1.bind(on_complete=counter_cb)
Clock.tick() # first run scheduled here; 9 left
r2 = gdb.recognize([Ncandidate], max_gpf=1)
r2.bind(on_complete=counter_cb)
Clock.tick() # 8 left
r3 = gdb.recognize([Ncandidate], max_gpf=1)
r3.bind(on_complete=counter_cb)
Clock.tick() # 7 left
# run some immediate searches, should not interfere.
for i in range(5):
n = gdb.recognize([TGesture], max_gpf=0)
self.assertEqual(n.best['name'], 'T')
self.assertTrue(round(n.best['score'], 1) == 1.0)
for i in range(6):
Clock.tick()
self.assertEqual(counter, 0)
Clock.tick()
self.assertEqual(counter, 1)
Clock.tick()
self.assertEqual(counter, 2)
Clock.tick()
self.assertEqual(counter, 3)
def test_timeout_case_1(self):
global best_score
from kivy.clock import Clock
from time import sleep
best_score = 0
gdb = Recognizer(db=[self.Tbound, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.4)
Clock.tick() # matches Tbound in this tick
self.assertEqual(best_score, 0)
sleep(0.4)
Clock.tick() # should match Ninv, but times out (got T)
self.assertEqual(r.status, 'timeout')
self.assertEqual(r.progress, .5)
self.assertTrue(r.best['name'] == 'T')
self.assertTrue(r.best['score'] < 0.5)
def test_timeout_case_1(self):
global best_score
from kivy.clock import Clock
from time import sleep
best_score = 0
gdb = Recognizer(db=[self.Tbound, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.4)
Clock.tick() # matches Tbound in this tick
self.assertEqual(best_score, 0)
sleep(0.4)
Clock.tick() # should match Ninv, but times out (got T)
self.assertEqual(r.status, 'timeout')
self.assertEqual(r.progress, .5)
self.assertTrue(r.best['name'] == 'T')
self.assertTrue(r.best['score'] < 0.5)
def test_scheduling(self):
global best_score
from kivy.clock import Clock
gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
# _recognize_tick is scheduled here; compares to Tinvar
Clock.tick()
self.assertEqual(r.progress, .5)
self.assertEqual(best_score, .0)
# Now complete the search operation
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
def test_scheduling(self):
global best_score
from kivy.clock import Clock
gdb = Recognizer(db=[self.Tinvar, self.Ninvar])
r = gdb.recognize([Ncandidate], max_gpf=1)
r.bind(on_complete=best_score_cb)
# _recognize_tick is scheduled here; compares to Tinvar
Clock.tick()
self.assertEqual(r.progress, .5)
self.assertEqual(best_score, .0)
# Now complete the search operation
Clock.tick()
self.assertEqual(r.progress, 1)
self.assertTrue(best_score > 0.94 and best_score < 0.95)
def test_export_import_case_2(self):
from tempfile import mkstemp
import os
gdb1 = Recognizer(db=[self.Ninvar, self.Tinvar])
gdb2 = Recognizer()
fh, fn = mkstemp()
os.close(fh)
g = gdb1.export_gesture(name='N', filename=fn)
gdb2.import_gesture(filename=fn)
os.unlink(fn)
self.assertEqual(len(gdb1.db), 2)
self.assertEqual(len(gdb2.db), 1)
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_export_import_case_2(self):
from tempfile import mkstemp
import os
gdb1 = Recognizer(db=[self.Ninvar, self.Tinvar])
gdb2 = Recognizer()
fh, fn = mkstemp()
os.close(fh)
g = gdb1.export_gesture(name='N', filename=fn)
gdb2.import_gesture(filename=fn)
os.unlink(fn)
self.assertEqual(len(gdb1.db), 2)
self.assertEqual(len(gdb2.db), 1)
r = gdb2.recognize([Ncandidate], max_gpf=0)
self.assertEqual(r.best['name'], 'N')
self.assertTrue(r.best['score'] > 0.94 and r.best['score'] < 0.95)
def test_timeout_case_2(self):
global best_score
from kivy.clock import Clock
from time import sleep
best_score = 0
gdb = Recognizer(db=[self.Tbound, self.Ninvar, self.Tinvar])
r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.8)
Clock.tick() # matches Tbound in this tick
self.assertEqual(best_score, 0)
sleep(0.4)
Clock.tick() # matches Ninvar in this tick
sleep(0.4)
Clock.tick() # should match Tinvar, but times out
self.assertEqual(r.status, 'timeout')
self.assertEqual(r.progress, 2 / 3.)
self.assertTrue(r.best['score'] >= .94 and r.best['score'] <= .95)
def test_timeout_case_2(self):
global best_score
from kivy.clock import Clock
from time import sleep
best_score = 0
gdb = Recognizer(db=[self.Tbound, self.Ninvar, self.Tinvar])
r = gdb.recognize([Ncandidate], max_gpf=1, timeout=0.8)
Clock.tick() # matches Tbound in this tick
self.assertEqual(best_score, 0)
sleep(0.4)
Clock.tick() # matches Ninvar in this tick
sleep(0.4)
Clock.tick() # should match Tinvar, but times out
self.assertEqual(r.status, 'timeout')
self.assertEqual(r.progress, 2 / 3.)
self.assertTrue(r.best['score'] >= .94 and r.best['score'] <= .95)
class StrokeRecognition(object):
def __init__(self, parent, data, loglevel):
self.strokes = [[]]
self.time = time.time()
self.gdb = Recognizer()
self.logger = logging.getLogger('StrokeRecognition')
self.logger.setLevel(loglevel)
self.logger.addHandler(CH)
self.logger.info('Creating Gestures Templates..')
circle = [[Vector(int(10+10*cos(t)),
int(10+10*sin(t)))
for t in np.linspace(0,2*pi,8)]]
self.gdb.add_gesture('Circle',circle, strokes_sensitive=True)
#Horizontal or vertical lines give error
self.gdb.add_gesture('Line', [[Vector(10,60),Vector(40,50)]],
strokes_sensitive=True, priority=50)
self.gdb.add_gesture('Triangle', [[Vector(10,10),
Vector(15,15),
Vector(20,20),
Vector(20,20),
Vector(25,15),
Vector(30,10),
Vector(30,10),
Vector(20,10),
Vector(10,10)]],
strokes_sensitive=False,
orientation_sensitive=False,
permute=False)
self.gdb.add_gesture('Rectangle', [[Vector(10,10),
Vector(10,15),
Vector(10,20),
Vector(10,20),
Vector(15,20),
Vector(20,20),
Vector(20,20),
Vector(20,15),
Vector(20,10),
Vector(20,10),
Vector(15,10),
Vector(10,10)]],
strokes_sensitive=False,
orientation_sensitive=False,
permute=False)
self.logger.info('Templates created')
self.found_gesture = False
self.gesture = None
self._data = data
self._parent = parent
self.ran = False
self.gdb.bind(on_search_complete=self.search_stop)
self.dist_thres = 0
self.time_thres = 2
self.skel_sub = mfilters.Subscriber(
"skeleton", Image)
self.clas_sub = mfilters.Subscriber(
"class", TimeReference)
self.image_ts = mfilters.TimeSynchronizer(
[self.skel_sub, self.clas_sub], 30)
self.image_ts.registerCallback(
self.callback)
self.bridge = CvBridge()
def callback(self, skel, class_name):
if self._parent.initialized and not self._parent.write_mode:
try:
skel = self.bridge.imgmsg_to_cv2(skel,
desired_encoding=
'passthrough')
action = class_name.source
if action == 'Index':
self.ran = False
self.add_stroke_vector(skel[-1, -1, 1],
skel[-1, -1, 0])
self.time = time.time()
elif action == 'Palm':
self.add_stroke()
if not self.ran and time.time() - self.time > self.time_thres:
self.ran = True
if len(self.strokes[0])>0:
self.progress = self.gdb.recognize(self.strokes[:-1])
#removing last empty sublist ^
clock.tick()
self._data.add(gesture=self.gesture,
found_gesture=self.found_gesture,
strokes=self.strokes)
self.strokes = [[]]
evt = CreateEvent(EVT_STRK_TYPE, -1)
wx.PostEvent(self._parent, evt)
except Exception as e:
exc_type, exc_value, exc_traceback = sys.exc_info()
traceback.print_exception(exc_type,
exc_value,
exc_traceback, limit=2, file=sys.stdout)
print e
else:
self.strokes = [[]]
def search_stop(self, gdb, pt):
best = pt.best
dist = best['dist']
self.gesture = best['name']
if dist > self.dist_thres and self.gesture is not None:
self.found_gesture = True
self.logger.debug('Gesture found as ' + str(self.gesture) +
' having cos distance ' + str(dist))
else:
self.found_gesture = False
self.logger.debug('Gesture not found. \n\tBest candidate was '+
str(self.gesture) +' with cos distance:' + str(dist))
self.logger.debug('\tThe number of strokes was ' +
str(len(self.strokes)-1))
self.logger.debug('\tStrokes:')
for stroke in self.strokes[:-1]:
self.logger.debug('\t\t'+str(stroke))
def add_stroke(self):
if len(self.strokes[-1])>0: #add stroke only if last stroke is not empty
self.strokes.append([])
def add_stroke_vector(self, xpoint, ypoint):
if len(self.strokes[-1])>0:
dist_check = norm(np.diff([np.array(self.strokes[-1][-1]),
np.array([xpoint,ypoint])],axis=0))<10
else:
dist_check = True
if dist_check:
self.strokes[-1].append(Vector(xpoint,ypoint))
