def __init__(self, core_file_name):
super(Listener, self).__init__()
self.core_file_name = core_file_name
self.setup_ui()
self.setup_timers()
port = SERIAL_PORT
self.serial = serial.Serial(port, BAUDE_RATE, timeout=0)
self.incoming_data = []
self.imu = IMU(PLATFORM_SPECIFIC_QUOTIENTS['stm'])
self.stroke = Stroke()
self.selector = Selector(self.core_file_name)
self.acceleration_filter = AperiodicFilter(ACCELERATION_TIME_CONST)
self.stroke.widget = self.display
self.stroke.on_done = self.get_stroke
self.previous_time = None
self.data_buffer = ''
self.init_selector()
def compute_stroke_steps(self, s: Stroke):
if (self._is_point_within_grid(s.get_start())
and self._is_point_within_grid(s.get_end())) == False:
raise Exception(
"Stroke start or end point are out of the grid range.")
virtual_points = s.compute_parameters(self._lines, self._columns,
self._inter_dist)
self._actuator_triggers.clear()
self._compute_physical_mapping(virtual_points, s.get_intensity())
return self._actuator_triggers
def get_strokes_as_one(self):
"""
@TODO - maybe not necessary function
@TODO - this is not efficient implements
:return: all the strokes in the file, merged into one stroke, without pauses
"""
map = {
0: 'time',
1: 'x',
2: 'y',
3: 'pressure',
4: 'tiltX',
5: 'tiltY',
6: 'azimuth',
7: 'sidePressure',
8: 'rotation'
}
copy_data = copy.deepcopy(self._data)
new_stroke = []
lst = []
for j in range(len(map)):
for i in range(self.size()):
lst += list(copy_data[i].get_feature(map[j]))
lst = []
new_stroke.append(lst)
return Stroke(np.asarray(new_stroke))
def hello_world(i):
templates = get_templates
strokeNumber = i
cs = strokes[i - 1]
strk = Stroke(x=cs['x'], y=cs['y'], t=cs['t'])
clean_segment_indices, segtypes = segment_stroke(strk)
best_match = classify_stroke(strk, templates)
return best_match
def get_strokes(data):
"""
:param data: DataFrame object
:return: list of strokes that represent the data
"""
stroke_list = []
stroke = []
start_stroke_location = 0 # the location of the next stroke in data
current_time = 0.0
for i, time in enumerate(data['time']):
if time == 'Pause':
# getting threshold for the size of stroke
if i - start_stroke_location < Constants.MIN_SIZE_OF_STROKE: # MIN_SIZE_OF_STROKE = 2
start_stroke_location = i + 1
continue
# creating the data for the new stroke that will be create
for index, feature in enumerate(data):
stroke.append(
Analyzer.string2float_array(
data[feature][start_stroke_location:i]))
if index == Constants.TIME:
current_time = Analyzer.update_time(
stroke, current_time)
start_stroke_location = i + 1
stroke_list.append(Stroke(stroke))
stroke = []
if i + 2 == len(data['time']): # end of file
break
# creating the data for the new pause-stroke
pause_time = float(list(data['time'])[i + 1]) - float(
list(data['time'])[i - 1])
pause_data = Analyzer.get_pause_data(
int(pause_time / Constants.TIME_STAMP))
current_time = Analyzer.update_time(pause_data, current_time)
stroke_list.append(Stroke(pause_data, pause=True))
return stroke_list
def take_in_request():
data = request.get_json()
templates = get_templates()
print(len(data['x']))
# strks = [Stroke(x=data['x'], y=data['y'], t=data['t']) for i in range(1)]
for d in range(len(data['x'])):
print("length of data", len(data['x'][d]))
if len(data['x'][d]) < 3:
print(data['x'][d] * 2)
data['x'][d] = [data['x'][d][0], data['x'][d][0], data['x'][d][0]]
data['y'][d] = [data['y'][d][0], data['y'][d][0], data['y'][d][0]]
data['t'][d] = [
data['t'][d][0], data['t'][d][0] + 1, data['t'][d][0] + 2
]
print(len(data['t'][d]))
strks = [
Stroke(x=data['x'][i], y=data['y'][i], t=data['t'][i])
for i in range(len(data['x']))
]
print("stroke", data)
best_match = classify_stroke(strks, templates)
return {"best": best_match}
s = s.strip()
duration = 0
try:
duration = float(s)
except Exception as e:
raise Exception(
"Invalid duration was passed. A decimal value must be passed.")
return duration
if __name__ == "__main__":
print("Enter stroke start position (x,y):")
start_str = input()
start_x, start_y = get_position_from_string(start_str)
print("Enter stroke start position (x,y):")
end_str = input()
end_x, end_y = get_position_from_string(end_str)
print("Enter duration of stroke in msec:")
duration_str = input()
duration = get_duration_from_string(duration_str)
t = TactileBrush(Config.lines, Config.columns, Config.spacing)
s = Stroke(start_x, start_y, end_x, end_y, duration, 1)
motion = t.compute_stroke_steps(s)
pattern = create_pattern(motion)
print("Json Pattern:\n")
print(pattern.to_json())
8: "FIVE",
9: "THREE FEATHERS",
10: "CHEF HAT",
11: "DOME",
12: "MUSIC NOTE"
}
if len(sys.argv) != 2:
raise ValueError('Error! Give stroke number after filename in command. \n e.g. python eval_stroke.py 2')
i = int(sys.argv[1])
if i <= len(strokes) and i > 0 or i == -1:
strokeNumber = i
cs = strokes[i-1]
strk = Stroke(x=cs['x'], y=cs['y'], t=cs['t'])
clean_segment_indices, segtypes = segment_stroke(strk)
best_match = classify_stroke(strk, templates)
print(f"{bcolors.BOLD}", "STROKE NUMBER:", strokeNumber, f"{bcolors.ENDC}")
print(f"{bcolors.BOLD}", "STROKE CLASS:", stroke_names[strokeNumber], f"{bcolors.ENDC}")
if best_match == stroke_names[strokeNumber]:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.OKGREEN}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
else:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.FAIL}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
plot_segmentation(strk, clean_segment_indices, segtypes)
plt.figure(1).canvas.set_window_title('MIT 6.835: Stroke Segmentation')
plt.show()
else:
msg = 'Stroke index out of range. Give a number between 1 and ' + str(strokes.size)
import matplotlib.pyplot as plt
from stroke_segmentation import segment_stroke
from plot_segmentation import plot_segmentation
from Stroke import Stroke
from stroke_data import strokes
custom_strokes = strokes
plt.figure(1, figsize=(12, 8))
for cs in custom_strokes:
strk = Stroke(x=cs['x'], y=cs['y'], time=cs['time'])
clean_segment_indices, segtypes = segment_stroke(strk)
plot_segmentation(strk, clean_segment_indices, segtypes, all=True)
plt.figure(1).canvas.set_window_title('MIT 6.835: Stroke Segmentation')
plt.tight_layout()
plt.show()
ratio = math.hypot(c1 - e.first / self._inter_dist, l1 -
e.second / self._inter_dist) / math.hypot(
c1 - c2, l1 - l2)
phy1 = ActuatorStep(c1, l1,
math.sqrt(1 - ratio) * global_intensity,
e.get_duration(), e.timer_max_intensity)
phy2 = ActuatorStep(c2, l2,
math.sqrt(ratio) * global_intensity,
e.get_duration(), e.timer_max_intensity)
self._insert_actuator_step(e.get_start(), phy1)
self._insert_actuator_step(e.get_start(), phy2)
def _is_point_within_grid(self, point: ActuatorPoint):
if point.first < self._min_coord.first or point.first > self._max_coord.first:
return False
if point.second < self._min_coord.second or point.second > self._max_coord.second:
return False
return True
if __name__ == "__main__":
#t = TactileBrush(2, 4, 2.5)
#s = Stroke(0, 1, 3, 0, 1000, 1)
t = TactileBrush(3, 4, 1.5)
s = Stroke(0.6666, 2, 3, 0.6666, 1000.0, 1.0)
t.compute_stroke_steps(s)
t.pretty_print()
class Listener(QWidget):
def __init__(self, core_file_name):
super(Listener, self).__init__()
self.core_file_name = core_file_name
self.setup_ui()
self.setup_timers()
port = SERIAL_PORT
self.serial = serial.Serial(port, BAUDE_RATE, timeout=0)
self.incoming_data = []
self.imu = IMU(PLATFORM_SPECIFIC_QUOTIENTS['stm'])
self.stroke = Stroke()
self.selector = Selector(self.core_file_name)
self.acceleration_filter = AperiodicFilter(ACCELERATION_TIME_CONST)
self.stroke.widget = self.display
self.stroke.on_done = self.get_stroke
self.previous_time = None
self.data_buffer = ''
self.init_selector()
def setup_ui(self):
self.resize(500, 500)
self.out = QLabel(self)
self.out.setMinimumHeight(100)
font = QFont()
font.setPixelSize(80)
self.out.setFont(font)
self.grid = QGridLayout(self)
self.display = StrokeWidget()
self.letter_selector = QComboBox()
self.grid.addWidget(self.display, 0, 0, 1, 1)
self.grid.addWidget(self.letter_selector, 1, 0, 1, 1)
self.grid.addWidget(self.out, 2, 0, 1, 1)
def setup_timers(self):
self.serial_timer = QTimer()
self.serial_timer.setInterval(SERIAL_INTERVAL)
self.serial_timer.timeout.connect(self.get_data)
self.serial_timer.start()
self.process_timer = QTimer()
self.process_timer.setInterval(PROCESS_INTERVAL)
self.process_timer.timeout.connect(self.process)
self.process_timer.start()
self.display_timer = QTimer()
self.display_timer.setInterval(DISPLAY_TIMEOUT)
self.display_timer.setSingleShot(True)
self.display_timer.timeout.connect(self.set_background)
def init_selector(self):
sel_lines = self.selector.letters_dict.keys()
sel_lines.insert(0, 'new strokes')
sel_lines.insert(0, 'free run')
self.letter_selector.addItems(sel_lines)
self.letter_selector.currentIndexChanged.connect(self.set_background)
def set_background(self):
letter = str(self.letter_selector.currentText())
self.display.set_background(self.core_file_name, letter)
def store_stroke(self, key, stroke, existing=True):
file_name = '{key}{time}.txt'.format(key=key, time=int(time()))
file_path = os.path.join(LEARNED_FOLDER, file_name)
np.savetxt(file_path, stroke)
if existing:
self.display.set_background(self.core_file_name, key, color='g')
self.display_timer.start()
def get_stroke(self, data):
stroke = data['stroke']
dimention = data['dimention']
if dimention < MIN_DIMENTION:
print 'too small'
return
letter = str(self.letter_selector.currentText())
if letter == 'new strokes':
self.store_stroke('_', stroke, existing=False)
print 'recorded'
try:
letters = self.selector.check_stroke(stroke)
except: #TODO: check unify_stroke
return
if letters:
self.out.setText(self.out.text()+letters[0])
if letter == 'free run' and letters:
self.store_stroke(letters[0], stroke)
elif letter in letters:
self.store_stroke(letter, stroke)
def process(self):
local_data_storage = deepcopy(self.incoming_data)
self.incoming_data = []
for data in local_data_storage:
if self.previous_time is None:
self.previous_time = data[0]
continue
data[0], self.previous_time = data[0] - self.previous_time, data[0]
if data[0] < MAX_DATA_TIMELAPSE:
self.imu.calc(data)
gyro = np.linalg.norm(np.array([data[7:]]))
accel = self.imu.get_global_acceleration()
accel = self.acceleration_filter.set_input(accel, data[0])
accel_magnitude = np.linalg.norm(accel)
if accel_magnitude > ACCELERATION_RESET:
self.execute_spell()
Yr = self.imu.get_y_direction()
self.stroke.set_data(Yr, gyro)
self.stroke.process_size(data[0], accel)
self.setVisible(not self.imu.in_calibration)
def execute_spell(self):
self.out.setText('')
def get_data(self):
try:
self.data_buffer += self.serial.read(self.serial.inWaiting())
if self.data_buffer == '':
return
data_pieces = self.data_buffer.split(BUFFER_DELIMITER)
# Put incomplete piece back to the buffer
self.data_buffer = data_pieces.pop(-1)
# If there are no complete data pieces - return from function
if not data_pieces:
return
# Else - get the last of the pieces and discard the rest
line = data_pieces[-1]
result = [float(d) for d in line.split()]
if len(result) != 9:
raise ValueError('Nine pieces of data should be provided.')
new_line = [time()] + result
self.incoming_data.append(new_line)
except KeyboardInterrupt:
raise
except Exception as e:
# Something went wrong... nobody cares.
print e
11: "DOME",
12: "MUSIC NOTE"
}
if len(sys.argv) != 2:
raise ValueError('Error! Give stroke number after filename in command. \n e.g. python eval_stroke.py 2')
i = int(sys.argv[1])
if i <= len(strokes) and i > 0 or i == -1:
strokeNumber = i
# cs = strokes[i-1]
# cs = {'x': [[224.6171875, 223.6171875, 223.6171875, 223.6171875, 222.6171875, 220.6171875, 217.6171875, 215.6171875, 213.6171875, 210.6171875, 207.6171875, 205.6171875, 202.6171875, 201.6171875, 199.6171875, 198.6171875, 197.6171875, 196.6171875, 195.6171875, 194.6171875, 193.6171875, 193.6171875, 192.6171875, 191.6171875, 191.6171875, 190.6171875, 189.6171875, 188.6171875, 186.6171875, 185.6171875, 183.6171875, 182.6171875, 181.6171875, 181.6171875, 179.6171875, 179.6171875, 178.6171875, 177.6171875, 176.6171875, 174.6171875, 172.6171875, 170.6171875, 167.6171875, 164.6171875, 159.6171875, 157.6171875, 153.6171875, 152.6171875, 150.6171875, 150.6171875, 151.6171875, 160.6171875, 171.6171875, 186.6171875, 194.6171875, 203.6171875, 204.6171875, 203.6171875, 187.6171875, 174.6171875, 164.6171875, 158.6171875, 153.6171875, 151.6171875, 150.6171875, 149.6171875, 149.6171875, 149.6171875, 148.6171875, 148.6171875, 148.6171875, 148.6171875, 148.6171875, 151.6171875, 156.6171875, 165.6171875, 175.6171875, 186.6171875, 198.6171875, 204.6171875, 210.6171875, 215.6171875, 218.6171875, 221.6171875, 225.6171875, 230.6171875, 235.6171875, 243.6171875, 250.6171875, 258.6171875, 266.6171875, 272.6171875, 281.6171875, 286.6171875, 293.6171875, 298.6171875, 302.6171875, 306.6171875, 310.6171875, 313.6171875, 316.6171875, 319.6171875, 322.6171875, 325.6171875, 328.6171875, 332.6171875, 336.6171875, 340.6171875, 343.6171875, 345.6171875, 348.6171875, 349.6171875, 350.6171875, 351.6171875, 352.6171875, 353.6171875, 353.6171875, 354.6171875, 356.6171875, 359.6171875, 363.6171875, 366.6171875, 368.6171875, 371.6171875, 375.6171875, 376.6171875, 378.6171875, 379.6171875, 380.6171875, 380.6171875, 380.6171875, 380.6171875, 380.6171875, 380.6171875, 380.6171875, 379.6171875, 378.6171875, 377.6171875, 375.6171875, 375.6171875, 373.6171875, 372.6171875, 370.6171875, 367.6171875, 363.6171875, 356.6171875, 345.6171875, 331.6171875, 319.6171875, 311.6171875, 304.6171875, 300.6171875, 300.6171875, 300.6171875, 301.6171875, 303.6171875, 304.6171875, 304.6171875, 301.6171875, 295.6171875, 287.6171875, 277.6171875, 265.6171875, 247.6171875, 241.6171875, 226.6171875, 221.6171875, 215.6171875, 211.6171875, 208.6171875, 207.6171875, 205.6171875, 204.6171875, 202.6171875]], 'y': [[120.91015625, 120.91015625, 120.91015625, 120.91015625, 120.91015625, 122.91015625, 125.91015625, 129.91015625, 134.91015625, 139.91015625, 145.91015625, 150.91015625, 155.91015625, 159.91015625, 163.91015625, 166.91015625, 169.91015625, 174.91015625, 177.91015625, 180.91015625, 183.91015625, 185.91015625, 188.91015625, 190.91015625, 191.91015625, 194.91015625, 196.91015625, 198.91015625, 200.91015625, 203.91015625, 206.91015625, 209.91015625, 211.91015625, 213.91015625, 215.91015625, 217.91015625, 219.91015625, 222.91015625, 224.91015625, 227.91015625, 229.91015625, 231.91015625, 234.91015625, 236.91015625, 240.91015625, 243.91015625, 246.91015625, 250.91015625, 254.91015625, 257.91015625, 260.91015625, 261.91015625, 261.91015625, 259.91015625, 259.91015625, 259.91015625, 263.91015625, 277.91015625, 307.91015625, 332.91015625, 349.91015625, 359.91015625, 365.91015625, 368.91015625, 369.91015625, 370.91015625, 371.91015625, 372.91015625, 373.91015625, 374.91015625, 376.91015625, 378.91015625, 379.91015625, 379.91015625, 379.91015625, 377.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 375.91015625, 373.91015625, 372.91015625, 370.91015625, 369.91015625, 367.91015625, 366.91015625, 365.91015625, 364.91015625, 362.91015625, 361.91015625, 359.91015625, 358.91015625, 356.91015625, 354.91015625, 352.91015625, 350.91015625, 348.91015625, 345.91015625, 343.91015625, 340.91015625, 338.91015625, 335.91015625, 334.91015625, 333.91015625, 333.91015625, 332.91015625, 331.91015625, 331.91015625, 329.91015625, 328.91015625, 325.91015625, 322.91015625, 318.91015625, 315.91015625, 312.91015625, 307.91015625, 304.91015625, 301.91015625, 299.91015625, 296.91015625, 294.91015625, 291.91015625, 290.91015625, 288.91015625, 286.91015625, 284.91015625, 282.91015625, 281.91015625, 278.91015625, 276.91015625, 274.91015625, 271.91015625, 267.91015625, 263.91015625, 258.91015625, 254.91015625, 250.91015625, 249.91015625, 249.91015625, 251.91015625, 256.91015625, 259.91015625, 260.91015625, 253.91015625, 233.91015625, 215.91015625, 192.91015625, 181.91015625, 165.91015625, 159.91015625, 153.91015625, 145.91015625, 137.91015625, 130.91015625, 123.91015625, 121.91015625, 116.91015625, 114.91015625, 111.91015625, 109.91015625, 107.91015625, 107.91015625, 106.91015625, 105.91015625, 105.91015625]], 't': [[1589264172488, 1589264172489, 1589264172696, 1589264172704, 1589264172721, 1589264172737, 1589264172753, 1589264172771, 1589264172787, 1589264172804, 1589264172820, 1589264172837, 1589264172854, 1589264172871, 1589264172888, 1589264172904, 1589264172921, 1589264172937, 1589264172955, 1589264172971, 1589264172988, 1589264173005, 1589264173020, 1589264173037, 1589264173055, 1589264173071, 1589264173087, 1589264173105, 1589264173120, 1589264173137, 1589264173154, 1589264173172, 1589264173187, 1589264173205, 1589264173221, 1589264173237, 1589264173254, 1589264173271, 1589264173288, 1589264173304, 1589264173321, 1589264173338, 1589264173354, 1589264173370, 1589264173387, 1589264173404, 1589264173421, 1589264173437, 1589264173455, 1589264173471, 1589264173488, 1589264173504, 1589264173522, 1589264173538, 1589264173554, 1589264173571, 1589264173587, 1589264173604, 1589264173621, 1589264173637, 1589264173655, 1589264173670, 1589264173688, 1589264173705, 1589264173721, 1589264173737, 1589264173754, 1589264173772, 1589264173788, 1589264173804, 1589264173821, 1589264173838, 1589264173854, 1589264173871, 1589264173887, 1589264173905, 1589264173921, 1589264173938, 1589264173955, 1589264173971, 1589264173988, 1589264174005, 1589264174021, 1589264174038, 1589264174054, 1589264174071, 1589264174088, 1589264174105, 1589264174121, 1589264174139, 1589264174155, 1589264174171, 1589264174187, 1589264174203, 1589264174221, 1589264174237, 1589264174254, 1589264174271, 1589264174287, 1589264174304, 1589264174321, 1589264174338, 1589264174355, 1589264174371, 1589264174387, 1589264174407, 1589264174422, 1589264174439, 1589264174455, 1589264174471, 1589264174488, 1589264174505, 1589264174522, 1589264174539, 1589264174554, 1589264174572, 1589264174588, 1589264174604, 1589264174622, 1589264174647, 1589264174671, 1589264174688, 1589264174704, 1589264174720, 1589264174739, 1589264174755, 1589264174772, 1589264174788, 1589264174804, 1589264174822, 1589264174837, 1589264174854, 1589264174873, 1589264174889, 1589264174905, 1589264174921, 1589264174938, 1589264174955, 1589264174971, 1589264174988, 1589264175006, 1589264175022, 1589264175039, 1589264175054, 1589264175073, 1589264175088, 1589264175105, 1589264175122, 1589264175139, 1589264175155, 1589264175171, 1589264175188, 1589264175204, 1589264175221, 1589264175238, 1589264175255, 1589264175272, 1589264175289, 1589264175305, 1589264175323, 1589264175338, 1589264175355, 1589264175371, 1589264175388, 1589264175405, 1589264175421, 1589264175438, 1589264175455, 1589264175472, 1589264175496, 1589264175505, 1589264175522, 1589264175538, 1589264175554]]}
cs = {'x': [[258.6171875, 258.6171875, 257.6171875, 255.6171875, 252.6171875, 248.6171875, 244.6171875, 241.6171875, 237.6171875, 234.6171875, 230.6171875, 225.6171875, 218.6171875, 210.6171875, 203.6171875, 197.6171875, 194.6171875, 192.6171875, 191.6171875, 191.6171875, 191.6171875, 191.6171875, 193.6171875, 196.6171875, 199.6171875, 202.6171875, 205.6171875, 208.6171875, 210.6171875, 211.6171875, 211.6171875, 212.6171875, 212.6171875, 210.6171875, 206.6171875, 202.6171875, 194.6171875, 185.6171875, 176.6171875, 167.6171875, 159.6171875, 152.6171875, 147.6171875, 142.6171875, 138.6171875, 136.6171875, 134.6171875, 131.6171875, 129.6171875, 127.6171875, 126.6171875, 125.6171875, 124.6171875, 123.6171875, 123.6171875, 123.6171875, 123.6171875, 123.6171875, 125.6171875, 127.6171875, 131.6171875, 140.6171875, 149.6171875, 155.6171875, 163.6171875, 169.6171875, 174.6171875, 177.6171875, 180.6171875, 183.6171875, 186.6171875, 188.6171875, 191.6171875, 193.6171875, 197.6171875, 200.6171875, 201.6171875, 203.6171875, 205.6171875, 206.6171875, 207.6171875, 207.6171875, 207.6171875, 207.6171875, 207.6171875, 206.6171875, 203.6171875, 199.6171875, 195.6171875, 189.6171875, 184.6171875, 178.6171875, 173.6171875, 168.6171875, 161.6171875, 155.6171875, 150.6171875, 145.6171875, 141.6171875, 137.6171875, 135.6171875, 133.6171875, 131.6171875, 131.6171875, 131.6171875, 131.6171875, 131.6171875, 131.6171875, 132.6171875, 136.6171875, 142.6171875, 153.6171875, 174.6171875, 198.6171875, 223.6171875, 253.6171875, 272.6171875, 290.6171875, 305.6171875, 318.6171875, 330.6171875, 342.6171875, 352.6171875, 359.6171875, 367.6171875, 374.6171875, 380.6171875, 385.6171875, 392.6171875, 396.6171875, 400.6171875, 403.6171875, 405.6171875, 406.6171875, 406.6171875, 406.6171875, 403.6171875, 399.6171875, 394.6171875, 388.6171875, 383.6171875, 378.6171875, 371.6171875, 361.6171875, 351.6171875, 343.6171875, 335.6171875, 328.6171875, 324.6171875, 321.6171875, 321.6171875, 321.6171875, 321.6171875, 321.6171875, 322.6171875, 324.6171875, 328.6171875, 329.6171875, 331.6171875, 332.6171875, 333.6171875, 333.6171875, 333.6171875, 333.6171875, 333.6171875, 333.6171875, 332.6171875, 331.6171875, 329.6171875, 325.6171875, 320.6171875, 315.6171875, 310.6171875, 305.6171875, 301.6171875, 298.6171875, 296.6171875, 294.6171875, 293.6171875, 292.6171875, 292.6171875, 291.6171875, 291.6171875, 291.6171875, 291.6171875, 291.6171875, 292.6171875, 292.6171875, 292.6171875, 292.6171875, 292.6171875, 292.6171875, 292.6171875, 291.6171875, 290.6171875, 289.6171875, 288.6171875, 285.6171875, 283.6171875, 280.6171875, 277.6171875, 275.6171875, 272.6171875, 270.6171875, 267.6171875, 264.6171875, 262.6171875, 261.6171875, 260.6171875, 258.6171875, 258.6171875]], 'y': [[124.91015625, 124.91015625, 124.91015625, 124.91015625, 124.91015625, 124.91015625, 124.91015625, 124.91015625, 126.91015625, 131.91015625, 136.91015625, 144.91015625, 157.91015625, 170.91015625, 184.91015625, 197.91015625, 207.91015625, 213.91015625, 221.91015625, 226.91015625, 231.91015625, 233.91015625, 234.91015625, 235.91015625, 237.91015625, 239.91015625, 241.91015625, 242.91015625, 244.91015625, 245.91015625, 246.91015625, 247.91015625, 248.91015625, 249.91015625, 250.91015625, 251.91015625, 253.91015625, 256.91015625, 259.91015625, 262.91015625, 266.91015625, 268.91015625, 270.91015625, 271.91015625, 273.91015625, 274.91015625, 275.91015625, 279.91015625, 281.91015625, 283.91015625, 286.91015625, 288.91015625, 290.91015625, 292.91015625, 294.91015625, 296.91015625, 297.91015625, 297.91015625, 298.91015625, 298.91015625, 299.91015625, 300.91015625, 301.91015625, 303.91015625, 304.91015625, 305.91015625, 306.91015625, 306.91015625, 307.91015625, 307.91015625, 307.91015625, 307.91015625, 308.91015625, 309.91015625, 309.91015625, 310.91015625, 311.91015625, 312.91015625, 312.91015625, 313.91015625, 314.91015625, 314.91015625, 315.91015625, 316.91015625, 318.91015625, 319.91015625, 321.91015625, 322.91015625, 323.91015625, 325.91015625, 327.91015625, 330.91015625, 333.91015625, 336.91015625, 339.91015625, 342.91015625, 344.91015625, 346.91015625, 348.91015625, 350.91015625, 351.91015625, 352.91015625, 355.91015625, 357.91015625, 359.91015625, 360.91015625, 363.91015625, 364.91015625, 365.91015625, 366.91015625, 367.91015625, 370.91015625, 373.91015625, 375.91015625, 377.91015625, 378.91015625, 378.91015625, 378.91015625, 378.91015625, 376.91015625, 372.91015625, 369.91015625, 365.91015625, 363.91015625, 360.91015625, 357.91015625, 355.91015625, 352.91015625, 348.91015625, 345.91015625, 342.91015625, 339.91015625, 337.91015625, 334.91015625, 331.91015625, 328.91015625, 324.91015625, 320.91015625, 316.91015625, 312.91015625, 310.91015625, 308.91015625, 307.91015625, 305.91015625, 304.91015625, 303.91015625, 301.91015625, 300.91015625, 299.91015625, 299.91015625, 298.91015625, 297.91015625, 296.91015625, 295.91015625, 293.91015625, 289.91015625, 280.91015625, 275.91015625, 268.91015625, 261.91015625, 255.91015625, 251.91015625, 247.91015625, 245.91015625, 244.91015625, 242.91015625, 241.91015625, 240.91015625, 239.91015625, 236.91015625, 234.91015625, 232.91015625, 230.91015625, 229.91015625, 228.91015625, 227.91015625, 226.91015625, 225.91015625, 224.91015625, 223.91015625, 222.91015625, 220.91015625, 218.91015625, 214.91015625, 211.91015625, 208.91015625, 202.91015625, 198.91015625, 193.91015625, 187.91015625, 181.91015625, 177.91015625, 173.91015625, 170.91015625, 168.91015625, 166.91015625, 164.91015625, 162.91015625, 160.91015625, 158.91015625, 156.91015625, 155.91015625, 153.91015625, 151.91015625, 149.91015625, 147.91015625, 145.91015625, 143.91015625, 141.91015625, 139.91015625, 138.91015625]], 't': [[1589265688900, 1589265689028, 1589265689040, 1589265689058, 1589265689074, 1589265689090, 1589265689106, 1589265689123, 1589265689140, 1589265689156, 1589265689173, 1589265689190, 1589265689206, 1589265689224, 1589265689241, 1589265689257, 1589265689274, 1589265689291, 1589265689307, 1589265689323, 1589265689340, 1589265689357, 1589265689373, 1589265689390, 1589265689407, 1589265689424, 1589265689441, 1589265689458, 1589265689474, 1589265689491, 1589265689508, 1589265689525, 1589265689541, 1589265689558, 1589265689573, 1589265689590, 1589265689607, 1589265689624, 1589265689641, 1589265689657, 1589265689675, 1589265689691, 1589265689707, 1589265689724, 1589265689741, 1589265689757, 1589265689774, 1589265689791, 1589265689808, 1589265689823, 1589265689841, 1589265689857, 1589265689875, 1589265689891, 1589265689907, 1589265689925, 1589265689941, 1589265689958, 1589265689974, 1589265689991, 1589265690008, 1589265690024, 1589265690040, 1589265690058, 1589265690074, 1589265690092, 1589265690106, 1589265690123, 1589265690141, 1589265690158, 1589265690175, 1589265690191, 1589265690207, 1589265690224, 1589265690241, 1589265690258, 1589265690273, 1589265690291, 1589265690309, 1589265690325, 1589265690341, 1589265690358, 1589265690374, 1589265690391, 1589265690411, 1589265690425, 1589265690441, 1589265690457, 1589265690473, 1589265690491, 1589265690507, 1589265690524, 1589265690540, 1589265690558, 1589265690575, 1589265690591, 1589265690607, 1589265690625, 1589265690642, 1589265690658, 1589265690674, 1589265690691, 1589265690707, 1589265690724, 1589265690741, 1589265690758, 1589265690775, 1589265690791, 1589265690808, 1589265690825, 1589265690842, 1589265690859, 1589265690875, 1589265690891, 1589265690908, 1589265690925, 1589265690941, 1589265690958, 1589265690975, 1589265690992, 1589265691008, 1589265691026, 1589265691041, 1589265691058, 1589265691075, 1589265691092, 1589265691109, 1589265691124, 1589265691141, 1589265691157, 1589265691175, 1589265691191, 1589265691208, 1589265691225, 1589265691241, 1589265691257, 1589265691274, 1589265691292, 1589265691307, 1589265691325, 1589265691341, 1589265691358, 1589265691374, 1589265691392, 1589265691409, 1589265691426, 1589265691441, 1589265691459, 1589265691475, 1589265691492, 1589265691508, 1589265691526, 1589265691542, 1589265691558, 1589265691575, 1589265691591, 1589265691609, 1589265691626, 1589265691642, 1589265691659, 1589265691675, 1589265691692, 1589265691708, 1589265691725, 1589265691741, 1589265691759, 1589265691775, 1589265691792, 1589265691808, 1589265691825, 1589265691841, 1589265691858, 1589265691876, 1589265691892, 1589265691909, 1589265691925, 1589265691942, 1589265691959, 1589265691975, 1589265691992, 1589265692009, 1589265692024, 1589265692041, 1589265692058, 1589265692074, 1589265692092, 1589265692108, 1589265692125, 1589265692142, 1589265692159, 1589265692175, 1589265692192, 1589265692209, 1589265692225, 1589265692242, 1589265692258, 1589265692275, 1589265692292, 1589265692309, 1589265692326, 1589265692342, 1589265692359, 1589265692376, 1589265692392, 1589265692408, 1589265692426, 1589265692443, 1589265692459, 1589265692475, 1589265692492, 1589265692509]]}
# strk = Stroke(x=cs['x'], y=cs['y'], t=cs['t'])
strks = [Stroke(x=cs['x'][i], y=cs['y'][i], t=cs['t'][i]) for i in range(len(cs['x']))]
best_match = classify_stroke(strks, templates)
for strk in strks:
clean_segment_indices, segtypes = segment_stroke(strk)
print(f"{bcolors.BOLD}", "STROKE NUMBER:", strokeNumber, f"{bcolors.ENDC}")
print(f"{bcolors.BOLD}", "STROKE CLASS:", stroke_names[strokeNumber], f"{bcolors.ENDC}")
if best_match == stroke_names[strokeNumber]:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.OKGREEN}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
else:
print(f"{bcolors.BOLD}", "YOUR CLASSIFICATION:", f"{bcolors.FAIL}", best_match, f"{bcolors.ENDC}", f"{bcolors.ENDC}")
plot_segmentation(strk, clean_segment_indices, segtypes)
plt.figure(1).canvas.set_window_title('MIT 6.835: Stroke Segmentation')
plt.show()
else: