def test_smooth_list_4(self):
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
readDetection_2.set_window(3)
print '------------'
for i in range(0, 5):
print i
print '------------'
input_list = [
353, 327.0, 301, 323.0, 345.0, 367, 376, 375, 365, 365, 366, 366,
369, 370.125, 371.25, 372.375, 373.5, 374.625, 375.75, 376.875,
378, 377, 373, 376, 373, 369.0, 365, 362.0, 359, 356, 363.0, 370.0,
377, 374, 372, 367.0, 362, 362, 357, 353, 352, 358.6666666666667,
365.33333333333337, 372, 368, 364, 359, 356, 354, 352, 346, 351.5,
357.0, 362.5, 368, 359, 355, 348, 348, 348, 377, 373, 367.0, 361,
358, 354, 349, 354.0, 359.0, 364, 361, 358, 351, 349, 347, 358.0,
369, 365, 360, 363, 368, 361, 360, 357, 361, 363, 361.0, 359, 355,
358, 365, 362.0, 359, 358, 355, 356.75, 358.5, 360.25, 362, 358,
355, 366, 366, 368, 363, 358, 356, 368, 371, 366, 358, 358, 363.0,
368, 364, 356, 355, 361.0, 367, 363.0, 359, 357, 362, 362
]
filtered_list = self.readDetection.filter_list(input_list)
smoothed_list = self.readDetection.smooth_list(filtered_list)
input_list_dates = []
for i in range(0, len(smoothed_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list[0:len(smoothed_list)]),
len(smoothed_list))
self.readDetection.show_plot(input_list_dates,
input_list[0:len(smoothed_list)],
smoothed_list, "test_smooth_list_4")
def test_reading_6(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 6
treshold_from_neg_to_pos = 2
treshold_window_selection = 12
treshold_second_derivative = 2.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286
]
input_list_dates = []
for i in range(0, 300):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_6")
print 'dataset 6'
print dataset
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[22])
self.assertEqual(dataset[0][1], input_list_dates[299])
def test_notify(self):
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
input_list = [
-1, 377, -1, 365, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-1, -1, -1, 397, 405, 405, 399, 395, 391, 389, -1, 377, 375, 370,
371, -1, 388, 385, 382, 380, 379, 380, 387, 388, 386, 386, 384,
383, 382, 380, 377, 378, 375, 368, 370, 384, 387, 385, 384, 382,
-1, 379, 377, 377, 371, 371, 373, 383, 388, 385, 382, 381, 379,
377, 376, 376, -1, 370, 372, 384, 387, 384, 380, 373, 372, 373,
371, 369, 369, 383, 382, 383, 385, 383, 378, 377, 374, 370, 367,
366, 383, 383, -1, 371, 374, 372, 372, 366, 370, 377, 383, 381,
379, 379, 377, 375, 373, 370, 366, 367, 365, 385, 383, 381, 379,
374, 374, 370, 367, 362, 363, -1, -1, 381, 379, 376, 375, 371, 369,
366, 367, 367, 367, 371, 376, 382, 386, 389, 385, 385, 384, 381,
380, 377, 376, 373, 370, 369, 369, 377, 382, 383, 383, 379, 376,
375, 373, 370, 368, 369, 370, 383, 385, 383, 378, 377, 374, 370,
368, 358, 364, 371, 384, 382, 379, 376, 372, 373, 370, 368, 366,
363, 359, 365, 376, 381, 381, 381, 377, 375, 374, 371, 371, 369,
368, 360, 365, 369, 382, 386, 382, 378, 378, 376, 374, -1, -1, 370,
371, 369, 368, 368, 363, 364, 364, 376, 381, 378, 379, 377, 376,
374, 373, 369, 370, 369, 368, 368, 365, 364, -1, 363, 372, 383,
381, 378, 376, 372, 373, 371, 371, 369, 365, 367, 363, 365, 366,
379, 378, 378, 375, 375, 372, 372, 371, 367, 364, 366, 366, 357,
375, 380, 378, 378, 375, 376, 374, 371, 369, 370, 372, 380, 384,
383, 379, 377, 378, 377, 374, 372, 371, 369, 368, 366, 364, 372,
381, 380, 377, 376, 374, 371, 369, 369, 367, 362, 368, 377, 378,
377, 376, 373, 371, 369, 369, 365, 366, 355, 368, 381, 381, 379,
377, 376, -1, 373, 371, 370, 365, 367, 374, 381, 378, -1, 373, 372,
370, 369, 367, 366, 361, 364, 371, 381, 381, 378, 377, 375, -1,
372, 370, 367, 365, 363, 364, 369, 381, 381, 379, 375, 373, 371,
370, 369, 367, 365, 363, -1, 379, 381, 378, 376, 374, 373, 371,
371, 369, 368, 367, 365, 363, 365, 377, 383, 383, 383, 380, 378,
375, 376, 375, 372, 371, 371, 368, 366, 360, 366, 380, 385, 383,
382, 379, 377, 376, 373, 371, 369, 369, 367, 364, 373, 383, 381,
377, 377, 375, 374, 373, 372, 369, 371, 370, 368, 367, 368, 360,
364, 376, 382, 380, 377, 374, 373, 370, 370, 370, 371, 369, 362,
364, 362, 358, 360, 374, 383, 380, 377, 374, 372, 369, 366, 368,
366, 359, -1, 363, 366, 374, 383, 378, 378, 376, 375, 373, 369,
367, -1, 367, 374, 383, 385, 382, 379, 375, 373, 372, 373, 370,
368, 366, 364, 361, -1, 383, 382, 381, 379, 377, 378, 373, 371,
370, 371, 368, 367, 366, 362, 357, 361, 364, 378, 383, 380, 378,
377, 376, 372, 370, 369, 368, 363, 365, 364, 370, 382, 382, 380,
-1, 376, 373, 370, 368, 366, 360, 361, 368, 374, 381, 381, 377,
374, 371, 370, 368, 366, 363, 368, 370, 371, 369, 370, 373, 372
]
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(str((i)))
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading notify")
print 'dataset notify'
print dataset
for i in range(0, len(input_list)):
eye = [input_list[i], 0]
readDetection_2.notify(eye, input_list_dates[i])
readDetection_2.notify_stopping_application()
def test_reading_8_reading_stop_reading(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = -1
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
427, 423, -1, -1, 430, 429, 430, -1, -1, -1, -1, -1, -1, -1, 421,
413, 416, 418, 414, 412, 409, 408, 405, 400, 395, -1, 412, 414,
412, 409, 405, 404, 403, 396, 397, 395, 390, 386, 398, 412, 413,
408, 408, 406, 403, 403, -1, -1, 392, 389, 386, 404, 407, 407, 405,
402, 401, 398, 388, 394, 395, 392, 392, -1, 409, 414, 413, 409,
407, 402, 400, 398, 395, 394, 392, -1, 410, 411, 408, 405, 405,
401, 399, 397, 394, 391, 394, 400, 401, 401, 401, 401, 400, -1, -1,
398, 400, 400, 399, 399, 399, 399, 397, 398, 398, 400, 398, 398,
401, -1, 399, 400, 397, 399, 402, 405, 411, 409, 405, 402, 401,
398, 394, 393, 391, 394, 402, 411, 408, 407, 400, 401, 398, 396,
392, 391, -1, 409, 410, 411, 409, 408, 407, 405, 397, 397, 388,
394, 401, 410, 410, 407, 400, 400, 396, 398, 396, 396, 396, 397,
397
]
#filtered_list = self.readDetection.filter_list(input_list)
#smoothed_list = self.readDetection.smooth_list(filtered_list)
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
#self.assertEqual(len(input_list[0:len(smoothed_list)]),len(smoothed_list))
#self.readDetection.show_plot(input_list_dates,filtered_list[0:len(smoothed_list)],smoothed_list,"reading_10")
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_8_reading_stop_reading")
print '---------------'
print 'dataset 8'
print dataset
print '---------------'
self.assertEqual(dataset[0][0], 8)
self.assertEqual(dataset[0][1], 98)
self.assertEqual(dataset[1][0], 118)
self.assertEqual(dataset[1][1], 160)
def test_reading_4(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 4
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = 3
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 1.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.1
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
readDetection_2.set_tresholds(
treshold_from_neg_to_pos, treshold_length_array_x_coordinates_iris,
treshold_ratio_pos_neg_read_samples, treshold_readLines_negative,
treshold_readLines_positive, treshold_read_samples_line,
treshold_second_derivative, treshold_window_selection,
treshold_window_selection_relative_marge_difference_amount_pos,
treshold_window_selection_total_pos)
input_list = [
5, 8, 1, 3, 9, 5, 6, 4, 2, 8, 2, 4, 8, 7, 6, 5, 4, 3, 4, 7, 8, 7,
6, 5, 4, 3, 7, 8, 7, 6, 5, 4, 3, 6, 5, 8, 9, 78, 5, 5, 4, 5, 8, 8,
9, 6, 5, 86, 5, 4, 5, 2, 65, 89, 7, 5, 5, 8, 45, 69, 8, 4, 5, 52,
5, 4, 5, 6, 8, 5, 8, 5, 8, 5, 6, 2, 5, 6, 8, 9, 8, 5, 4, 5, 8, 2,
7, 8, 7, 6, 5, 4, 3, 5, 7, 6, 5, 4, 3, 6, 8, 7, 6, 5, 4, 7, 8, 7,
6, 5, 4, 3, 5, 7, 9, 8, 7, 6, 5, 4
]
input_list_dates = self.generate_datetime_array_35_entries(59, 1)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = readDetection_2.analyse_list_for_reading_patterns_smooth_list(
input_list, input_list_dates)
print 'dataset 4'
print dataset
self.assertEqual(len(dataset), 2)
self.assertEqual(dataset[0][0], input_list_dates[14])
# In dit geval klopt het dat deze niet slaagt omdat er een hele reeks 5,4,5,4,5,4 voor de eigenlijke "leesdata" komt, maar int echt komt dit zelden voor
# Heeft met de second derivative te maken
#self.assertEqual(dataset[0][1],input_list_dates[34])
self.assertEqual(dataset[1][0], input_list_dates[89])
self.assertEqual(dataset[1][1], input_list_dates[119])
class TestStatistics(unittest.TestCase):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 4
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = 3
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 1.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.1
readDetection = Read_detection_tracking.ReadDetection('../../')
#readDetection = Read_detection_tracking.ReadDetection('')
readDetection.set_tresholds(
treshold_from_neg_to_pos, treshold_length_array_x_coordinates_iris,
treshold_ratio_pos_neg_read_samples, treshold_readLines_negative,
treshold_readLines_positive, treshold_read_samples_line,
treshold_second_derivative, treshold_window_selection,
treshold_window_selection_relative_marge_difference_amount_pos,
treshold_window_selection_total_pos)
def test_statistics(self):
input_list = [1, 3, 3, 4, 5, 7, 9, 10, 11, 15, 16]
window_size = 4
output_list = List_operations.movingaverage(input_list, window_size)
print output_list
def test_filter_list(self):
input_list = [1, 2, 3, 4, -1, -1, -1, 8, 9]
result = self.readDetection.filter_list(input_list)
self.assertEqual(result[0], 1)
self.assertEqual(result[1], 2)
self.assertEqual(result[2], 3)
self.assertEqual(result[3], 4)
self.assertEqual(result[4], 5)
self.assertEqual(result[5], 6)
self.assertEqual(result[6], 7)
self.assertEqual(result[7], 8)
self.assertEqual(result[8], 9)
def test_filter_list_2(self):
input_list = [-1, 2, 3, 4, -1, -1, -1, 8, 9]
result = self.readDetection.filter_list(input_list)
self.assertEqual(result[0], -1)
self.assertEqual(result[1], 2)
self.assertEqual(result[2], 3)
self.assertEqual(result[3], 4)
self.assertEqual(result[4], 5)
self.assertEqual(result[5], 6)
self.assertEqual(result[6], 7)
self.assertEqual(result[7], 8)
self.assertEqual(result[8], 9)
def test_filter_list_3(self):
input_list = [1, -1, 3, 4, -1, -1, 7, -1]
result = self.readDetection.filter_list(input_list)
self.assertEqual(result[0], 1)
self.assertEqual(result[1], 2)
self.assertEqual(result[2], 3)
self.assertEqual(result[3], 4)
self.assertEqual(result[4], 5)
self.assertEqual(result[5], 6)
self.assertEqual(result[6], 7)
self.assertEqual(result[7], -1)
def test_derivative(self):
input_list = [1, 2, 5, 4, 7, 2]
result = self.readDetection.calculate_derivative(input_list)
self.assertEqual(result[0], 0)
self.assertEqual(result[1], 1)
self.assertEqual(result[2], 3)
self.assertEqual(result[3], -1)
self.assertEqual(result[4], 3)
self.assertEqual(result[5], -5)
def generate_datetime_array_35_entries(self, seconds, minutes):
index_minutes = 0
input_list_dates = []
while index_minutes <= minutes:
index_seconds = 0
while index_seconds <= seconds:
if index_seconds < 10:
input_list_dates.append(
datetime.datetime.strptime(
"1989-12-12 08:0" + str(index_minutes) + ":0" +
str(index_seconds), "%Y-%m-%d %H:%M:%S"))
else:
input_list_dates.append(
datetime.datetime.strptime(
"1989-12-12 08:" + str(index_minutes) + ":" +
str(index_seconds), "%Y-%m-%d %H:%M:%S"))
index_seconds += 1
index_minutes += 1
return input_list_dates
def test_reading_1(self):
input_list = [
8, 7, 6, 5, 4, 3, 2, 5, 7, 8, 7, 6, 5, 4, 3, 2, 5, 7, 8, 7, 6, 5,
4, 3, 2, 5, 7, 8, 7, 6, 5, 4, 3, 2, 1
]
input_list_dates = self.generate_datetime_array_35_entries(34, 0)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_smooth_list(
input_list, input_list_dates)
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[0])
self.assertEqual(dataset[0][1], input_list_dates[34])
def test_reading_2(self):
input_list = [
2, 1, 2, 3, 7, 1, 5, 4, 3, 5, 7, 6, 5, 4, 3, 2, 5, 7, 8, 7, 6, 5,
4, 3, 2, 5, 7, 8, 7, 6, 5, 4, 3, 2, 1
]
input_list_dates = self.generate_datetime_array_35_entries(34, 0)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_smooth_list(
input_list, input_list_dates)
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[12])
self.assertEqual(dataset[0][1], input_list_dates[34])
def test_reading_3(self):
input_list = [
8, 7, 6, 5, 4, 3, 2, 5, 7, 8, 7, 6, 5, 4, 3, 2, 5, 5, 3, 2, 3, 5,
4, 5, 4, 5, 4, 5, 4, 5, 7, 8, 7, 6, 5, 4, 3, 2, 5, 7, 8, 7, 6, 5,
4, 3, 2, 1, 3, 7, 8, 7, 6, 5, 4, 7, 8, 7, 6, 5
]
input_list_dates = self.generate_datetime_array_35_entries(59, 0)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_smooth_list(
input_list, input_list_dates)
print 'dataset 3'
print dataset
self.assertEqual(len(dataset), 2)
self.assertEqual(dataset[0][0], input_list_dates[0])
#self.assertEqual(dataset[0][1],input_list_dates[20])
self.assertEqual(dataset[0][1], input_list_dates[22])
self.assertEqual(dataset[1][0], input_list_dates[33])
self.assertEqual(dataset[1][1], input_list_dates[59])
def test_reading_4(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 4
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = 3
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 1.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.1
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
readDetection_2.set_tresholds(
treshold_from_neg_to_pos, treshold_length_array_x_coordinates_iris,
treshold_ratio_pos_neg_read_samples, treshold_readLines_negative,
treshold_readLines_positive, treshold_read_samples_line,
treshold_second_derivative, treshold_window_selection,
treshold_window_selection_relative_marge_difference_amount_pos,
treshold_window_selection_total_pos)
input_list = [
5, 8, 1, 3, 9, 5, 6, 4, 2, 8, 2, 4, 8, 7, 6, 5, 4, 3, 4, 7, 8, 7,
6, 5, 4, 3, 7, 8, 7, 6, 5, 4, 3, 6, 5, 8, 9, 78, 5, 5, 4, 5, 8, 8,
9, 6, 5, 86, 5, 4, 5, 2, 65, 89, 7, 5, 5, 8, 45, 69, 8, 4, 5, 52,
5, 4, 5, 6, 8, 5, 8, 5, 8, 5, 6, 2, 5, 6, 8, 9, 8, 5, 4, 5, 8, 2,
7, 8, 7, 6, 5, 4, 3, 5, 7, 6, 5, 4, 3, 6, 8, 7, 6, 5, 4, 7, 8, 7,
6, 5, 4, 3, 5, 7, 9, 8, 7, 6, 5, 4
]
input_list_dates = self.generate_datetime_array_35_entries(59, 1)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = readDetection_2.analyse_list_for_reading_patterns_smooth_list(
input_list, input_list_dates)
print 'dataset 4'
print dataset
self.assertEqual(len(dataset), 2)
self.assertEqual(dataset[0][0], input_list_dates[14])
# In dit geval klopt het dat deze niet slaagt omdat er een hele reeks 5,4,5,4,5,4 voor de eigenlijke "leesdata" komt, maar int echt komt dit zelden voor
# Heeft met de second derivative te maken
#self.assertEqual(dataset[0][1],input_list_dates[34])
self.assertEqual(dataset[1][0], input_list_dates[89])
self.assertEqual(dataset[1][1], input_list_dates[119])
def test_reading_5(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 5
treshold_from_neg_to_pos = 2
treshold_window_selection = 6
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
readDetection_2.set_tresholds(
treshold_from_neg_to_pos, treshold_length_array_x_coordinates_iris,
treshold_ratio_pos_neg_read_samples, treshold_readLines_negative,
treshold_readLines_positive, treshold_read_samples_line,
treshold_second_derivative, treshold_window_selection,
treshold_window_selection_relative_marge_difference_amount_pos,
treshold_window_selection_total_pos)
input_list_temp = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286
]
input_list = []
for i in range(0, 300):
if i % 2 == 0:
input_list.append(input_list_temp[i])
input_list_dates = []
for i in range(0, 150):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_5")
print 'dataset 5'
print dataset
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[13])
self.assertEqual(dataset[0][1], input_list_dates[149])
def test_reading_6(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 6
treshold_from_neg_to_pos = 2
treshold_window_selection = 12
treshold_second_derivative = 2.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286
]
input_list_dates = []
for i in range(0, 300):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_6")
print 'dataset 6'
print dataset
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[22])
self.assertEqual(dataset[0][1], input_list_dates[299])
def test_reading_7(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 6
treshold_from_neg_to_pos = 2
treshold_window_selection = 12
treshold_second_derivative = 10.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286, 50, 80, 60, 50, 30, 80, 70, 50, 60, 90, 50, 200, 80, 690, 40,
60, 850, 60, 520, 60, 850, 60, 90, 80, 960, 90, 80, 90, 80, 90, 50,
80, 90, 560, 80, 690, 850
]
input_list_dates = []
for i in range(0, 337):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_7")
print 'dataset 7'
print dataset
self.assertEqual(len(dataset), 1)
self.assertEqual(dataset[0][0], input_list_dates[22])
self.assertEqual(dataset[0][1], input_list_dates[273])
# Dit is normaal juist, maar het is begrijpbaar dat het algoritme vroeger "stop reading" detecteerd door noise in de data
#self.assertEqual(dataset[0][1],input_list_dates[312])
def test_reading_8_reading_stop_reading(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = -1
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
427, 423, -1, -1, 430, 429, 430, -1, -1, -1, -1, -1, -1, -1, 421,
413, 416, 418, 414, 412, 409, 408, 405, 400, 395, -1, 412, 414,
412, 409, 405, 404, 403, 396, 397, 395, 390, 386, 398, 412, 413,
408, 408, 406, 403, 403, -1, -1, 392, 389, 386, 404, 407, 407, 405,
402, 401, 398, 388, 394, 395, 392, 392, -1, 409, 414, 413, 409,
407, 402, 400, 398, 395, 394, 392, -1, 410, 411, 408, 405, 405,
401, 399, 397, 394, 391, 394, 400, 401, 401, 401, 401, 400, -1, -1,
398, 400, 400, 399, 399, 399, 399, 397, 398, 398, 400, 398, 398,
401, -1, 399, 400, 397, 399, 402, 405, 411, 409, 405, 402, 401,
398, 394, 393, 391, 394, 402, 411, 408, 407, 400, 401, 398, 396,
392, 391, -1, 409, 410, 411, 409, 408, 407, 405, 397, 397, 388,
394, 401, 410, 410, 407, 400, 400, 396, 398, 396, 396, 396, 397,
397
]
#filtered_list = self.readDetection.filter_list(input_list)
#smoothed_list = self.readDetection.smooth_list(filtered_list)
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
#self.assertEqual(len(input_list[0:len(smoothed_list)]),len(smoothed_list))
#self.readDetection.show_plot(input_list_dates,filtered_list[0:len(smoothed_list)],smoothed_list,"reading_10")
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_8_reading_stop_reading")
print '---------------'
print 'dataset 8'
print dataset
print '---------------'
self.assertEqual(dataset[0][0], 8)
self.assertEqual(dataset[0][1], 98)
self.assertEqual(dataset[1][0], 118)
self.assertEqual(dataset[1][1], 160)
def test_reading_9_reading_wide_small(self):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 3
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = -1
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 2.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.5
input_list = [
-1, 405, -1, -1, -1, -1, 413, 413, -1, 409, 418, 415, 413, 414, -1,
416, 418, 418, 416, 417, 421, 427, 426, 426, 425, 423, 423, 420,
419, 413, -1, 406, -1, 401, 400, -1, 426, 430, 429, 427, 423, 422,
420, -1, 417, 413, 412, 410, 407, 398, -1, 400, -1, 419, 420, 419,
418, 416, 414, 411, 409, 407, 404, 402, -1, 400, 393, 394, -1, 414,
421, 420, 417, 417, 414, 413, 410, 408, -1, -1, 399, 398, 397, 393,
-1, 420, 424, 424, 419, 410, 414, 410, 408, 407, 406, 402, 400, -1,
400, 414, 422, 424, 423, 421, 419, 417, 413, 418, 424, 425, -1,
422, 419, 416, 413, 422, 424, 419, 418, -1, 421, 424, 422, 417,
414, -1, 415, 424, 421, 421, 418, 413, 413, 413, 422, 424, 421,
418, 414, 409, 410, 409, 406, 406, 405
]
#filtered_list = self.readDetection.filter_list(input_list)
#smoothed_list = self.readDetection.smooth_list(filtered_list)
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
#self.assertEqual(len(input_list[0:len(smoothed_list)]),len(smoothed_list))
#self.readDetection.show_plot(input_list_dates,filtered_list[0:len(smoothed_list)],smoothed_list,"reading_10")
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading_9_reading_wide_small")
print '---------------'
print 'dataset 9'
print dataset
print '---------------'
self.assertEqual(dataset[0][0], 26)
self.assertEqual(dataset[0][1], 111)
def test_smooth_list(self):
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286
]
input_list_dates = []
smoothed_list = self.readDetection.smooth_list(input_list)
for i in range(0, len(smoothed_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list[0:len(smoothed_list)]),
len(smoothed_list))
#self.readDetection.show_plot(input_list_dates,input_list[0:len(smoothed_list)],smoothed_list)
def test_smooth_list_2(self):
input_list = [
9, 8, 7, 6, 5, 4, 6, 8, 7, 6, 5, 4, 6, 8, 7, 6, 5, 4, 6, 8, 7, 6,
5, 4
]
result = self.readDetection.smooth_list(input_list)
def test_smooth_list_3(self):
input_list = [
-1, 58.833333333333336, 118.66666666666667, 178.5,
238.33333333333334, 298.1666666666667, 358, 357.0, 356, 355, 354,
356, 356, 356.0, 356, 354, 352, 352, 349, 355, 355, 355, 354.5,
354, 354, 353, 353, 353, 353, 353, 354, 353, 351, 345, 352, 351.0,
350.0, 349, 352, 352, 356, 353, 351, 351, 350, 352, 352, 350, 351,
352, 350, 351, 349, 352, 351, 349, 349.5, 350, 350, 349, 344, 348,
348, 351, 349, 350, 346, 348, 347.6666666666667,
347.33333333333337, 347, 348, 350, 348, 348, 347.6666666666667,
347.33333333333337, 347, 349, 348, 347.0, 346, 347, 347, 347,
348.0, 349, 349, 351, 350.5, 350, 349, 348, 348.5, 349, 350, 350,
350, 348.5, 347, 338.0, 329.0, 320, 492, 482.5, 473, 476, 475.0,
474.0, 473, 482, 474, 478, 475, 472, 474, 468, 475.0, 482, 466,
467, 478, 468, 467, 466, 463, 466, 470, 470, 459, 455.0, 451, 453,
468, 467, 470, 469, 476, 459, 475, 462, 461, 456, 466, 466, 464,
466, 463, 474, 456, 458, 464, 461, 463, 459, 458, 467, 452, 451,
451, 453, 447, 443, 451, 446, 444, 458, 459, 476.3333333333333,
493.66666666666663, 511, 502.6666666666667, 494.33333333333337,
486, 488, 489, 489, 488, 482, 479.5, 477, 481, 90, 481, 484, 484,
492, 484, 483, 484, 481, 484, 486, 480, 488, 489, 485, 488, 486.0,
484, 483.5, 483, 484.0, 485, 485, 486.5, 488, 483, 483, 492, 480,
484, 473.0, 462, 489, 478, 484, 478.6666666666667,
473.33333333333337, 468, 468, 468, 462, 457.5, 453, 374, 373.5,
373, 373.5, 374, 373.5, 373, 378.5, 384, 377, 354, 374, 378.5, 383,
378.5, 374, 383, 380.0, 377, 375, 371, 373.5, 376, 375, 374, 379,
377.5, 376, 370, 377, 374, 374, 375.0, 376, 376, 373, 370, 374,
367, 372, 372.5, 373.0, 373.5, 374, 376, 383, 391, 364, 365,
370.75, 376.5, 382.25, 388, 372, 369, 364, 368, 373, 373, 374, 370,
362, 362, 360, 366, 380, 381, 378, 376, 374, 375, 372, 372, 369,
363, 367, 366, 374.5, 383, 380, 377, 376, 374, 372, 370, 368, 362,
366, 376, 377, 375, 372, 371, 362, 364, 362, 361, 381, 294, 293,
298.5, 304.0, 309.5, 315.0, 320.5, 326, 321, 320.0, 319, 317.5,
316, 316.0, 316.0, 316.0, 316.0, 316.0, 316, 315.6666666666667,
315.33333333333337, 315.00000000000006, 314.66666666666674,
314.3333333333334, 314, 312, 324, 323.3333333333333,
322.66666666666663, 322, 321, 315.3333333333333,
309.66666666666663, 304, 304, 309.6, 315.20000000000005,
320.80000000000007, 326.4000000000001, 332, 324.5, 317, 332, 315,
315, 312, 310.0, 308, 306, 305.0, 304, 304.5, 305, 302, 303, 302.0,
301, 306.3333333333333, 311.66666666666663, 317, 317.0, 317, 315,
314, 310.0, 306, 307.5, 309, 303.6666666666667, 298.33333333333337,
293, 302, 308, 313, 311.5, 310.0, 308.5, 307.0, 305.5, 304, 301.8,
299.6, 297.40000000000003, 295.20000000000005, 293, 296.0, 299,
300, 306, 307, 307, 309, 301, 301, 319, 315, 313.3333333333333,
311.66666666666663, 310, 313.5, 317, 314.75, 312.5, 310.25, 308,
306.5, 305, 304, 302, 302, 301, 299, 300.0, 301, 297.75, 294.5,
291.25, 288, 291.0, 294.0, 297.0, 300, 299.3333333333333,
298.66666666666663, 298, 300, 300, 299, 299, 299, 298, 298.6,
299.20000000000005, 299.80000000000007, 300.4000000000001, 301,
283, 243, 236, 243, 244.5, 246, 250, 262.4, 274.79999999999995,
287.19999999999993, 299.5999999999999, 311.9999999999999,
324.39999999999986, 336.79999999999984, 349.1999999999998,
361.5999999999998, 374, 373.84615384615387, 373.69230769230774,
373.5384615384616, 373.3846153846155, 373.23076923076934,
373.0769230769232, 372.9230769230771, 372.76923076923094,
372.6153846153848, 372.4615384615387, 372.30769230769255,
372.1538461538464, 372, 366.8, 361.6, 356.40000000000003,
351.20000000000005, 346, 356.0, 366, 358.0, 350, 358.0, 366, 372,
367, 369.3333333333333, 371.66666666666663, 374, 362.0, 350,
354.75, 359.5, 364.25, 369, 368.75, 368.5, 368.25, 368.0, 367.75,
367.5, 367.25, 367.0, 366.75, 366.5, 366.25, 366, 365.375, 364.75,
364.125, 363.5, 362.875, 362.25, 361.625, 361, 362.0, 363,
361.9166666666667, 360.83333333333337, 359.75000000000006,
358.66666666666674, 357.5833333333334, 356.5000000000001,
355.4166666666668, 354.3333333333335, 353.25000000000017,
352.16666666666686, 351.08333333333354, 350, 354.4,
358.79999999999995, 363.19999999999993, 367.5999999999999, 372,
374.0, 376, 371.75, 367.5, 363.25, 359, 383, 361,
369.3333333333333, 377.66666666666663, 386, 378.0, 370,
369.1818181818182, 368.3636363636364, 367.54545454545456,
366.72727272727275, 365.90909090909093, 365.0909090909091,
364.2727272727273, 363.4545454545455, 362.6363636363637,
361.81818181818187, 361, 345.6666666666667, 330.33333333333337,
315, 312, 316, 311, 311, 312, 310, 313, 309, 310, 313, 311, 311,
312, 297, 282, 291, 285.0, 279.0, 273, 264, 257, 264, 323, 318,
318, 323, 324, 323, 325, 321, 319.6666666666667,
318.33333333333337, 317, 310.5, 304, 315, 310, 313, 311, 307.0,
303, 305, 311, 311, 313, 316, 317, 318, 316, 316, 315, 315, 314,
313, 312, 312, 311, 312, 311.0, 310.0, 309, 315, 314, 314, 313,
313.0, 313, 312, 311, 311, 311, 310, 311, 310, 309, 309, 314, 314,
312.0, 310, 315, 313, 314, 314, 313, 311.0, 309, 309, 310, 308,
308, 306, 306.0, 306, 311, 311, 288, 309, 309.5, 310, 309, 315.75,
322.5, 329.25, 336, 311, 308, 306.5, 305, 304, 310, 310, 310, 309,
307, 306, 304, 287, 280, 260.0, 240, 238, 223, 222, 228, 240, 283,
309.0, 335, 326, 317, 313, 310, 308, 306.75, 305.5, 304.25, 303,
311, 312, 310, 303, 305, 300, 295, 292.5, 290, 293, 300.0, 307,
304, 305, 305, 301.0, 297, 296, 298, 303, 309, 304, 306, 303.5,
301, 299, 295, 293, 295, 306, 302.3333333333333,
298.66666666666663, 295, 291, 296, 286, 298, 302, 300, 297.0, 294,
292, 292, 290.0, 288, 297, 296, 298, 302, 282.0, 262.0, 242, 239.0,
236.0, 233.0, 230, 228, 226.0, 224, 211.5, 199, 190.0, 181, 180.0,
179.0, 178, 176, 201.33333333333334, 226.66666666666669,
252.00000000000003, 277.33333333333337, 302.6666666666667, 328,
338, 335.6666666666667, 333.33333333333337, 331, 322.0, 313, 306,
303, 305, 303, 309, 309, 317, 316.0, 315, 313, 308, 305.5, 303,
299, 298, 299, 299, 304, 310, 312, 310, 311, 307.5, 304, 302,
299.5, 297, 298, 301.0, 304.0, 307, 308, 307, 305.6666666666667,
304.33333333333337, 303, 298, 294, 294, 308, 307, 305, 302, 300.0,
298.0, 296, 295.5, 295, 297.6666666666667, 300.33333333333337, 303,
302, 296.25, 290.5, 284.75, 279, 279.5, 280, 296, 293, 290, 284.0,
278, 293.85714285714283, 309.71428571428567, 325.5714285714285,
341.42857142857133, 357.28571428571416, 373.142857142857, 389, 380,
378.6666666666667, 377.33333333333337, 376, 376, 378, 379, 381,
378, 380, 384, 381, 382, 380, 380, 382, 385, 380, 367, 375.0,
383.0, 391, 385, 386, 379, 378, 379.0, 380, 387, 388, 381, 384,
385.0, 386, 385, 380, 379, 375, 375.3333333333333,
375.66666666666663, 376, 378, 382, 377, 377.5, 378, 377, 377, 374,
371, 377, 367, 378, 371.0, 364.0, 357, 375, 380, 376, 368, 382,
372.5, 363, 369.5, 376, 383.5, 391, 395, 396, 397, 396, 386.0, 376,
374, 410, 406, 400, 404, 404, 409.5, 415, 417, 414, 412, 410, 408,
401, 405, 404, 400, 399, 397, 394, 394, 391, 389, 387, 392, 397,
397, 398, 395.0, 392, 393, 391, 392, 392, 391, 391, 390, 389, 388,
387, 386, 386, 383, 387, 391, 398, 396, 395.0, 394, 393, 391, 392,
392, 391, 390, 384, 388, 388, 389, 387, 386, 386, 387, 386, 385,
385, 384, 384, 388, 390, 390, 388, 387.5, 387, 387, 386, 385, 385,
385, 385, 384, 383, 383, 383, 382, 382, 387, 386, 387, 388, 388.0,
388, 386, 385, 385, 383, 383, 380, 381, 383, 381, 379, 379, 377,
381, 389, 388, 388, 385, 385, 391, 391, 387, 385, 385, 384, 383,
381, 379, 378, 376, 374, 377, 382, 386, 385, 383, 381, 381, 383,
381, 379, 377, 376, 373, 372, 378.5, 385, 384.0, 383, 382, 380,
379, 378, 378, 376, 375, 373, 373, 377, 381, 381, 380.5, 380, 380,
380, 378, 379, 379, 379, 378, 378, 378, 375.0, 372
]
input_list_dates = []
smoothed_list = self.readDetection.smooth_list(input_list)
for i in range(0, len(smoothed_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list[0:len(smoothed_list)]),
len(smoothed_list))
#self.readDetection.show_plot(input_list_dates,input_list[0:len(smoothed_list)],smoothed_list)
def test_smooth_list_4(self):
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
readDetection_2.set_window(3)
print '------------'
for i in range(0, 5):
print i
print '------------'
input_list = [
353, 327.0, 301, 323.0, 345.0, 367, 376, 375, 365, 365, 366, 366,
369, 370.125, 371.25, 372.375, 373.5, 374.625, 375.75, 376.875,
378, 377, 373, 376, 373, 369.0, 365, 362.0, 359, 356, 363.0, 370.0,
377, 374, 372, 367.0, 362, 362, 357, 353, 352, 358.6666666666667,
365.33333333333337, 372, 368, 364, 359, 356, 354, 352, 346, 351.5,
357.0, 362.5, 368, 359, 355, 348, 348, 348, 377, 373, 367.0, 361,
358, 354, 349, 354.0, 359.0, 364, 361, 358, 351, 349, 347, 358.0,
369, 365, 360, 363, 368, 361, 360, 357, 361, 363, 361.0, 359, 355,
358, 365, 362.0, 359, 358, 355, 356.75, 358.5, 360.25, 362, 358,
355, 366, 366, 368, 363, 358, 356, 368, 371, 366, 358, 358, 363.0,
368, 364, 356, 355, 361.0, 367, 363.0, 359, 357, 362, 362
]
filtered_list = self.readDetection.filter_list(input_list)
smoothed_list = self.readDetection.smooth_list(filtered_list)
input_list_dates = []
for i in range(0, len(smoothed_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list[0:len(smoothed_list)]),
len(smoothed_list))
self.readDetection.show_plot(input_list_dates,
input_list[0:len(smoothed_list)],
smoothed_list, "test_smooth_list_4")
def test_notify(self):
readDetection_2 = Read_detection_tracking.ReadDetection('../../')
input_list = [
-1, 377, -1, 365, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-1, -1, -1, 397, 405, 405, 399, 395, 391, 389, -1, 377, 375, 370,
371, -1, 388, 385, 382, 380, 379, 380, 387, 388, 386, 386, 384,
383, 382, 380, 377, 378, 375, 368, 370, 384, 387, 385, 384, 382,
-1, 379, 377, 377, 371, 371, 373, 383, 388, 385, 382, 381, 379,
377, 376, 376, -1, 370, 372, 384, 387, 384, 380, 373, 372, 373,
371, 369, 369, 383, 382, 383, 385, 383, 378, 377, 374, 370, 367,
366, 383, 383, -1, 371, 374, 372, 372, 366, 370, 377, 383, 381,
379, 379, 377, 375, 373, 370, 366, 367, 365, 385, 383, 381, 379,
374, 374, 370, 367, 362, 363, -1, -1, 381, 379, 376, 375, 371, 369,
366, 367, 367, 367, 371, 376, 382, 386, 389, 385, 385, 384, 381,
380, 377, 376, 373, 370, 369, 369, 377, 382, 383, 383, 379, 376,
375, 373, 370, 368, 369, 370, 383, 385, 383, 378, 377, 374, 370,
368, 358, 364, 371, 384, 382, 379, 376, 372, 373, 370, 368, 366,
363, 359, 365, 376, 381, 381, 381, 377, 375, 374, 371, 371, 369,
368, 360, 365, 369, 382, 386, 382, 378, 378, 376, 374, -1, -1, 370,
371, 369, 368, 368, 363, 364, 364, 376, 381, 378, 379, 377, 376,
374, 373, 369, 370, 369, 368, 368, 365, 364, -1, 363, 372, 383,
381, 378, 376, 372, 373, 371, 371, 369, 365, 367, 363, 365, 366,
379, 378, 378, 375, 375, 372, 372, 371, 367, 364, 366, 366, 357,
375, 380, 378, 378, 375, 376, 374, 371, 369, 370, 372, 380, 384,
383, 379, 377, 378, 377, 374, 372, 371, 369, 368, 366, 364, 372,
381, 380, 377, 376, 374, 371, 369, 369, 367, 362, 368, 377, 378,
377, 376, 373, 371, 369, 369, 365, 366, 355, 368, 381, 381, 379,
377, 376, -1, 373, 371, 370, 365, 367, 374, 381, 378, -1, 373, 372,
370, 369, 367, 366, 361, 364, 371, 381, 381, 378, 377, 375, -1,
372, 370, 367, 365, 363, 364, 369, 381, 381, 379, 375, 373, 371,
370, 369, 367, 365, 363, -1, 379, 381, 378, 376, 374, 373, 371,
371, 369, 368, 367, 365, 363, 365, 377, 383, 383, 383, 380, 378,
375, 376, 375, 372, 371, 371, 368, 366, 360, 366, 380, 385, 383,
382, 379, 377, 376, 373, 371, 369, 369, 367, 364, 373, 383, 381,
377, 377, 375, 374, 373, 372, 369, 371, 370, 368, 367, 368, 360,
364, 376, 382, 380, 377, 374, 373, 370, 370, 370, 371, 369, 362,
364, 362, 358, 360, 374, 383, 380, 377, 374, 372, 369, 366, 368,
366, 359, -1, 363, 366, 374, 383, 378, 378, 376, 375, 373, 369,
367, -1, 367, 374, 383, 385, 382, 379, 375, 373, 372, 373, 370,
368, 366, 364, 361, -1, 383, 382, 381, 379, 377, 378, 373, 371,
370, 371, 368, 367, 366, 362, 357, 361, 364, 378, 383, 380, 378,
377, 376, 372, 370, 369, 368, 363, 365, 364, 370, 382, 382, 380,
-1, 376, 373, 370, 368, 366, 360, 361, 368, 374, 381, 381, 377,
374, 371, 370, 368, 366, 363, 368, 370, 371, 369, 370, 373, 372
]
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(str((i)))
dataset = readDetection_2.analyse_list_for_reading_patterns(
input_list, input_list_dates, "reading notify")
print 'dataset notify'
print dataset
for i in range(0, len(input_list)):
eye = [input_list[i], 0]
readDetection_2.notify(eye, input_list_dates[i])
readDetection_2.notify_stopping_application()
class TestStatistics(unittest.TestCase):
treshold_length_array_x_coordinates_iris = 20
treshold_read_samples_line = 4
treshold_ratio_pos_neg_read_samples = 1.2
treshold_readLines_positive = 2
treshold_readLines_negative = 2
treshold_from_neg_to_pos = 2
treshold_window_selection = 3
treshold_second_derivative = 1.0
# tresholds for window selection
treshold_window_selection_total_pos = 1.0
treshold_window_selection_relative_marge_difference_amount_pos = 0.1
readDetection = Read_detection_tracking.ReadDetection('../../')
readDetection.set_tresholds(
treshold_from_neg_to_pos, treshold_length_array_x_coordinates_iris,
treshold_ratio_pos_neg_read_samples, treshold_readLines_negative,
treshold_readLines_positive, treshold_read_samples_line,
treshold_second_derivative, treshold_window_selection,
treshold_window_selection_relative_marge_difference_amount_pos,
treshold_window_selection_total_pos)
def test_read_detection(self):
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286
]
input_list = input_list + input_list[3:(
len(input_list) - 1)] + input_list[3:(
len(input_list) - 1)] + input_list[3:(len(input_list) - 1)]
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_2(
input_list, input_list_dates, "reading_1")
#self.assertEqual(dataset[0][0],60)
#self.assertEqual(dataset[0][1],299)
print 'dataset 1'
print dataset
def test_read_detection_2(self):
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286, 50, 80, 60, 50, 30, 80, 70, 50, 60, 90, 50, 200, 80, 690, 40,
60, 850, 60, 520, 60, 850, 60, 90, 80, 960, 90, 80, 90, 80, 90, 50,
80, 90, 560, 80, 690, 850
]
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_2(
input_list, input_list_dates, "reading_2")
#self.assertEqual(dataset[0][0],60)
#self.assertEqual(dataset[0][1],241)
print 'dataset 2'
print dataset
def test_read_detection_3(self):
input_list = [
-1, 102.0, 205.0, 308, 306, 305, 310, 310, 309, 309, 308, 309, 311,
312.0, 313, 313, 313, 314, 314, 314, 314, 313, 313, 312, 312, 311,
312, 311, 311, 310, 310, 311, 310, 308, 309, 306, 307, 305, 303.0,
301, 302, 301.5, 301, 297, 298, 300, 299, 296, 298, 296, 295, 294,
297, 303, 307, 311, 311, 312.0, 313, 313, 312, 312, 312, 311, 311,
309, 309.0, 309, 309, 309, 309, 308, 304.5, 301, 305,
304.6666666666667, 304.33333333333337, 304, 304, 304, 302, 302,
298, 301, 298, 299, 296, 300, 299, 298, 297, 296, 296, 295, 292,
294, 292, 291, 302, 307, 313, 315, 317, 314, 315, 313, 306, 307,
309, 309, 307, 310, 307.5, 305, 302, 289, 306, 306, 305, 304, 304,
302, 302, 301, 300, 302, 299, 298, 298, 296, 298, 295, 295, 292,
291, 292, 289, 289, 289.0, 289, 305, 313, 315, 315, 315, 314,
312.5, 311, 311, 310, 310, 309, 309, 309, 308, 308, 306, 305, 303,
303, 302, 301, 300, 299.0, 298, 301, 300, 299, 297.5, 296, 295,
292, 290, 290, 290.0, 290, 288, 288, 288, 287, 293, 298, 306,
312.0, 318, 315.0, 312, 312, 311, 311, 309, 308, 309, 307.5, 306,
309, 307, 305, 307, 306, 305, 305, 306, 305, 304, 304, 303.0, 302,
301, 300, 301, 300, 299, 296, 294, 294, 293.0, 292, 292, 291, 289,
289, 292, 293, 302, 317, 314.5, 312.0, 309.5, 307, 309, 302,
303.6666666666667, 305.33333333333337, 307, 296, 294.6666666666667,
293.33333333333337, 292, 304, 306, 306, 302, 303, 302, 302, 301,
301, 301, 299, 298, 295, 294, 295, 293, 293, 292, 293, 291, 292,
291, 288, 287, 288, 287, 294, 293, 303, 309, 314, 317, 298, 316,
315, 312, 312, 310, 309, 308.0, 307, 305, 305, 304, 302, 302, 302,
299, 300, 299, 298, 298.0, 298, 296, 294, 294, 293, 293, 289, 289,
286, 50, 80, 60, 50, 30, 80, 70, 50, 60, 90, 50, 200, 80, 690, 40,
60, 850, 60, 520, 60, 850, 60, 90, 80, 960, 90, 80, 90, 80, 90, 50,
80, 90, 560, 80, 690, 850
]
input_list_dates = []
for i in range(0, len(input_list)):
input_list_dates.append(i)
self.assertEqual(len(input_list), len(input_list_dates))
dataset = self.readDetection.analyse_list_for_reading_patterns_2(
input_list, input_list_dates, "reading_2")
#self.assertEqual(dataset[0][0],60)
#self.assertEqual(dataset[0][1],241)
print 'dataset 2'
print dataset
def generate_datetime_array_35_entries(self, seconds, minutes):
index_minutes = 0
input_list_dates = []
while index_minutes <= minutes:
index_seconds = 0
while index_seconds <= seconds:
if index_seconds < 10:
input_list_dates.append(
datetime.datetime.strptime(
"1989-12-12 08:0" + str(index_minutes) + ":0" +
str(index_seconds), "%Y-%m-%d %H:%M:%S"))
else:
input_list_dates.append(
datetime.datetime.strptime(
"1989-12-12 08:" + str(index_minutes) + ":" +
str(index_seconds), "%Y-%m-%d %H:%M:%S"))
index_seconds += 1
index_minutes += 1
return input_list_dates
class UserGoneTracker():
time_last_notified = time.clock()
logging_seconds = 0.0
amount_of_webcam_images = 0
# Moet groter zijn dan amount_of_webcam_images / logging_seconds
interval_unable_to_detect_eyes = 0
teller_eyesdetected = 0
teller_eyesdetect_check = 0
teller_unable_to_detect_eyes = 0
teller_duration_iterations_sec = 0
form_user_feedback_process_shown = False
start_date_time = datetime.datetime.today()
eyes_gone = False
start_eyes_gone = datetime.datetime.today()
datetime_last_eyes_detected = datetime.datetime.now()
outputSTR_iris_coordinates = "iris coordinates: "
irisDetection = Iris_detection.IrisDetection()
radioListReden = None
#parameters for switch eye
which_eye = Iris_detection.IrisDetection.RIGHT_EYE
threshold_min_eyes_detected_relative = 0.8
eyes_detected_acc = 0.0
total_eyes_detected = 0.0
threshold_samples_for_check_switch_eye = 600
#read detection
readDetection = Read_detection_tracking.ReadDetection('')
"""
# plot
fig_right_eye = plt.figure("right eye")
fig_left_eye = plt.figure("left eye")
subplot = 111
right_eye_x = []
left_eye_x = []
right_eye_y = []
left_eye_y = []
"""
image_operations = Image_operations.ImageOperations('')
def __init__(self, logging_seconds, amount_of_webcam_images,
interval_unable_to_detect_eyes, radioListReden):
self.logging_seconds = logging_seconds
self.amount_of_webcam_images = amount_of_webcam_images
self.interval_unable_to_detect_eyes = interval_unable_to_detect_eyes / amount_of_webcam_images / logging_seconds
self.radioListReden = radioListReden
"""
@param eye
@effect After every 'amount_of_webcam_images' iteration a row is added to the data_tier indicating whether the user was detected or not and eyes_detected_acc is set to 0.
@effect During each iteration, if one of the eyes is detected, the 'eyes_detected_acc' is incremented.
@effect if after amount_of_webcam_images iterations the eyes_detected_acc is larger than 0, the system will interpret this as 'eye detected'
"""
def detect_user_gone(self, eye):
if (eye is not None):
eyes_detected = True
self.eyes_detected_acc += 1
else:
eyes_detected = False
self.total_eyes_detected += 1
if (self.teller_eyesdetect_check == self.amount_of_webcam_images):
self.teller_eyesdetect_check = 0
currentDateTime = datetime.datetime.today()
# time in seconds
datetime_difference = currentDateTime - self.datetime_last_eyes_detected
self.datetime_last_eyes_detected = currentDateTime
if (self.teller_eyesdetected > 0):
self.teller_eyesdetected = 0
DAEyesDetected_SQLite.insert_row_action(
currentDateTime, 1, datetime_difference.seconds)
self.teller_unable_to_detect_eyes = 0
if self.eyes_gone is True:
user_gone_period = currentDateTime - self.start_eyes_gone
Form_user_gone.call_form(self.radioListReden,
user_gone_period.seconds,
self.start_eyes_gone,
datetime.datetime.today())
self.eyes_gone = False
else:
DAEyesDetected_SQLite.insert_row_action(
currentDateTime, 0, datetime_difference.seconds)
self.teller_unable_to_detect_eyes += 1
if self.eyes_gone is False:
if self.teller_unable_to_detect_eyes >= self.interval_unable_to_detect_eyes:
self.start_eyes_gone = currentDateTime
self.eyes_gone = True
else:
self.teller_eyesdetect_check += 1
self.teller_eyesdetected += eyes_detected
"""
@param frame | current frame from webcam
@param duration_iteration_sec | Amount of time between this and the last function call.
@effect data will be written to the data_tier. When after 'amount_of_webcam_images' iterations, the eyes are detected at least once, the system will detect this as 'eyes detected'
"""
def notify(self, frame):
time_now = time.clock()
duration_iteration_sec = time_now - self.time_last_notified
self.time_last_notified = time.clock()
self.teller_duration_iterations_sec += duration_iteration_sec
face, face_coordinates = self.image_operations.get_face(frame)
eye = None
if face is not None:
# If the face is detected, but hardly the current eye, it could be due to bad lightning. The solution is to try to detect the other eye
if self.total_eyes_detected >= self.threshold_samples_for_check_switch_eye:
eyes_detected_percentage = self.eyes_detected_acc / self.total_eyes_detected
if eyes_detected_percentage < self.threshold_min_eyes_detected_relative:
self.switch_eye()
self.total_eyes_detected = 0.0
self.eyes_detected_acc = 0.0
eye = self.irisDetection.detect_eyes(face, frame, face_coordinates,
self.which_eye)
self.readDetection.notify(eye, datetime.datetime.today())
if self.teller_duration_iterations_sec >= self.logging_seconds:
self.teller_duration_iterations_sec = 0
self.detect_user_gone(eye)
def switch_eye(self):
if self.which_eye == Iris_detection.IrisDetection.RIGHT_EYE:
self.which_eye = Iris_detection.IrisDetection.LEFT_EYE
else:
self.which_eye = Iris_detection.IrisDetection.RIGHT_EYE
self.readDetection.eye_switched()
def notify_stopping_application(self):
self.readDetection.notify_stopping_application()