def recognize_shape(self):
for k in self.templates:
for p in k[0]:
self.cloud.append(Point(p[0], p[1], p[2]))
#print(points)
self.temp.append(Template(k[1], self.cloud))
#print(temp)
for k in self.listFigurePoints:
self.drawnFigure.append(Point(k[0], k[1], k[2]))
recognizer = Recognizer(self.temp)
self.recognitionResult = recognizer.recognize(self.drawnFigure,
n=self.sampleNumber)
def read(eventstream):
# Train the recognizer on the list of template files,
# then execute the recognizer on the eventstream file.
# -------------------------------------------------------------------------
tf = open("templates.dat", 'r')
templates = []
for raw_lines in tf:
line = raw_lines.strip()
touch_num = 0
gf = open(line, 'r')
gname = gf.readline().strip()
gpoints = []
for lines in gf:
gfline = lines.strip()
if gfline == "BEGIN":
touch_num += 1
elif gfline == "END":
continue
else:
x, y = int(gfline.split(',')[0]), int(gfline.split(',')[1])
gpoints.append(Point(x, y, touch_num))
t = Template(gname, gpoints)
templates.append(t)
gname = ""
gpoints = []
recog = Recognizer(templates)
# -------------------------------------------------------------------------
# Extract the necessary points from the event stream.
gestures = [] # list of lists of points
gesture = [] # list of points
touch_num = 0
es = open(eventstream, 'r')
for raw_line in es:
line = raw_line.strip()
if line == "MOUSEDOWN":
touch_num += 1
elif line == "MOUSEUP":
continue
elif line == "RECOGNIZE":
# It's assumed recognize clears after recognition.
gestures.append(gesture)
gesture = []
touch_num = 0
else:
x, y = int(line.split(',')[0]), int(line.split(',')[1])
gesture.append(Point(x, y, touch_num))
es.close()
for gesture in gestures:
gname, accuracy = recog.recognize(gesture)
print(gname)
def read_event_points(event_file):
event_points = []
stroke_count = 0
# event_file = "D:/College/Semester 8/Natural User Interaction/Assignment1_$P/A1_TestingFiles/eventfiles/arrowhead_eventfile.txt"
EventObject = open(event_file, "r")
for line in EventObject:
line = line.strip()
if (line == 'MOUSEDOWN'):
stroke_count = stroke_count + 1
elif (line == 'MOUSEUP'):
continue
elif (line == 'RECOGNIZE'):
result = read_template_points(event_points)
# print result
event_points = []
stroke_count = 0
else:
row = line.split(',')
x = int(row[0])
y = int(row[1])
event_points.append(Point(x, y, stroke_count))
def test_recognition_successful():
tmpl = Template('X', [
Point(0, 0, 1),
Point(1, 1, 1),
Point(0, 1, 2),
Point(1, 0, 2)
])
recognizer = Recognizer([tmpl])
result = recognizer.recognize([
Point(30, 146, 1),
Point(106, 222, 1),
Point(30, 225, 2),
Point(106, 146, 2)
])
assert result[0] == 'X'
def test_recognition_failed():
tmpl = Template('X', [
Point(0, 0, 1),
Point(1, 1, 1),
Point(0, 1, 2),
Point(1, 0, 2)
])
recognizer = Recognizer([tmpl])
result = recognizer.recognize([
Point(30, 146, 1),
Point(306, 222, 1),
])
assert result[0] is None
def read_template_points(event_points):
all_templates = []
path = os.path.join('Templates')
if (os.listdir(path) == []):
print "No Templates."
else:
for filename in os.listdir(path):
new_path = path + "/" + filename
TemplateObject = open(new_path, "r")
line = TemplateObject.readline()
filename = line.strip()
stroke_count = 0
template_points = []
for line in TemplateObject:
line = line.strip()
row = line.split(',')
if (line == 'BEGIN'):
stroke_count = stroke_count + 1
elif (line == 'END'):
continue
else:
row = line.split(',')
x = int(row[0])
y = int(row[1])
template_points.append(Point(x, y, stroke_count))
new_template = Template(filename, template_points)
all_templates.append(new_template)
recognizer = Recognizer(all_templates)
result = recognizer.recognize(event_points)
print(result) # Output: ('X', 0.733770116545184)
from dollarpy import Recognizer, Template, Point
# Define 'Template' gestures, each consisting of a name and a list of 'Point' elements.
# These 'Point' elements have 'x' and 'y' coordinates and optionally the stroke index a point belongs to.
tmpl_1 = Template('X', [Point(0, 0), Point(1, 1), Point(0, 1), Point(1, 0)])
tmpl_2 = Template('line', [Point(0, 0), Point(1, 0)])
tmpl_3 = Template('line', [Point(0, 0), Point(1, 1)])
tmpl_4 = Template('line', [Point(0, 0), Point(0, 1)])
tmpl_5 = Template(
'square', [Point(0, 0), Point(0, 1),
Point(1, 1), Point(1, 0)])
# Create a 'Recognizer' object and pass the created 'Template' objects as a list.
recognizer = Recognizer([tmpl_1, tmpl_2])
# Call 'recognize(...)' to match a list of 'Point' elements to the previously defined templates.
result = recognizer.recognize([
Point(31, 141, 1),
Point(109, 222, 1),
Point(22, 219, 2),
Point(113, 146, 2)
])
print(result) # Output: ('X', 0.733770116545184)
def createArray(magnitude, z):
tempArray = []
# print(len(magnitude))
for i in range(len(magnitude)):
tempArray.append(Point(magnitude[i], z[i], 1))
return tempArray
import cv2
import time
from dollarpy import Recognizer, Template, Point
tmpl_1 = Template('X', [
Point(0, 0, 1),
Point(1, 1, 1),
Point(0, 1, 2),
Point(1, 0, 2)])
tmpl_2 = Template('line', [
Point(0, 0),
Point(1, 0)])
recognizer = Recognizer([tmpl_1, tmpl_2])
cap = cv2.VideoCapture(0)####### 0 indicates primary camera as for me i use my secondary
circle=True
prevx=0
prevy=0
framect=0
result=list()
laserpoints=list()
while(True):
ret, frame = cap.read()
blur = cv2.GaussianBlur(frame,(5,5),0)
height, width, channels = frame.shape
gray = cv2.cvtColor(blur, cv2.COLOR_BGR2GRAY)##############han3ml Gray Scaling n3rf aktar no2ta bright we deh hatob2a red dot######
(minVal, maxVal, minLoc, maxLoc) = cv2.minMaxLoc(gray)
x , y = maxLoc
intensity= gray[y,x]
if intensity<254:
circle=False
for i in range(-1,1):
for k in range(-1,1):
def test_point_repr():
point = Point(1, 2, 3)
assert str(point) == '(1, 2), stroke 3'
def get_points_from_class(template_points):
a = []
for i in range(len(template_points)):
a.append(
Point(int(template_points[i][0]), int(template_points[i][1]), 1))
return a