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3 commits

Author SHA1 Message Date
Nickiel12
650b8af331 wait, this is testing validation info 2023-10-11 16:59:49 -07:00
Nickiel12
dff604b66f added conditional print for file processing 2023-10-10 18:14:20 -07:00
Nickiel12
ec4dec6dc9 added validation statistics 2023-10-10 18:13:49 -07:00
9 changed files with 101 additions and 4080 deletions

3
.gitignore vendored
View file

@ -8,4 +8,5 @@ training_data/training_data_*/
training_data/*.vec
training_data/backgrounds.txt
training_data/negatives
training_data/opencv
training_data/opencv
validation/cascade*

View file

@ -97,6 +97,8 @@ if args.training_data:
tmp, frm = cap.read()
height, width, channels = frm.shape
if (args.file):
print(f"Image is {height} tall and {width} wide")
frame_count = 0
start_timestamp = time.strftime("%Y%m%d-%H%M%S")
# print(f"{height*.25}, {width}")

File diff suppressed because it is too large Load diff

View file

@ -1,522 +0,0 @@
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View file

@ -1,627 +0,0 @@
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View file

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287, 1176, 187, 1641, 522
292, 1105, 179, 1666, 583
295, 1126, 176, 1619, 531
296, 1143, 158, 1610, 494
297, 1141, 152, 1607, 488
298, 1118, 172, 1603, 522
299, 1112, 162, 1611, 521
300, 1108, 174, 1593, 524
301, 1099, 158, 1596, 516
302, 1104, 159, 1600, 516
303, 1103, 164, 1586, 512
304, 1093, 153, 1595, 514
305, 1090, 151, 1605, 522
306, 1087, 164, 1605, 537
307, 1088, 174, 1590, 535
308, 1054, 145, 1590, 531
309, 1110, 154, 1590, 500
310, 1112, 151, 1590, 495
311, 1106, 154, 1593, 505
312, 1087, 160, 1602, 531
313, 1088, 159, 1591, 521
314, 1097, 165, 1577, 511
315, 1095, 159, 1582, 509
316, 1095, 159, 1582, 509
317, 1100, 157, 1580, 503
318, 1091, 162, 1588, 520
319, 1095, 158, 1588, 513
320, 1085, 163, 1588, 525
321, 1085, 158, 1593, 524
322, 1085, 161, 1593, 527
323, 1049, 150, 1593, 542
324, 1091, 157, 1580, 509
324, 928, 128, 1638, 639
325, 1078, 173, 1586, 539
326, 1070, 174, 1585, 545
327, 1034, 153, 1570, 539
328, 1006, 155, 1582, 569
329, 1091, 166, 1553, 499
330, 982, 126, 1593, 566
331, 934, 128, 1606, 611
332, 1039, 169, 1524, 519
333, 973, 144, 1555, 563
334, 1024, 175, 1511, 526
335, 1049, 166, 1511, 499
336, 1008, 166, 1515, 531
337, 1000, 171, 1508, 537
338, 1018, 155, 1507, 507
339, 978, 182, 1502, 559
340, 960, 183, 1515, 582
341, 958, 197, 1494, 583
342, 961, 187, 1485, 564
343, 965, 177, 1458, 532
344, 963, 194, 1444, 540
345, 946, 186, 1449, 548
346, 948, 190, 1437, 542
347, 932, 181, 1431, 540
348, 941, 192, 1419, 536
349, 939, 195, 1432, 550
352, 914, 188, 1413, 547
355, 912, 181, 1405, 536
378, 918, 203, 1380, 536
379, 918, 203, 1380, 536
380, 918, 203, 1380, 536
381, 916, 206, 1401, 556
382, 919, 201, 1412, 556
387, 948, 203, 1410, 536
388, 943, 203, 1405, 536
389, 945, 201, 1430, 551
390, 948, 194, 1429, 540
391, 945, 203, 1438, 558
392, 949, 196, 1467, 569
393, 949, 201, 1457, 567
394, 952, 200, 1470, 573
395, 956, 209, 1474, 582
397, 954, 206, 1486, 588
398, 958, 192, 1513, 591
399, 966, 203, 1508, 593
400, 971, 188, 1507, 574
401, 988, 193, 1520, 575
402, 942, 195, 1534, 621
404, 1020, 188, 1532, 556
405, 975, 167, 1556, 585
406, 1011, 172, 1563, 569
407, 968, 177, 1590, 624
408, 1097, 178, 1559, 511
408, 941, 169, 1607, 648
409, 1091, 194, 1553, 527
409, 945, 160, 1611, 639
410, 1083, 190, 1572, 542
411, 1102, 190, 1580, 534
412, 1034, 156, 1618, 576
413, 1043, 170, 1613, 580
414, 1065, 171, 1611, 564
415, 1122, 191, 1584, 524
416, 1112, 198, 1593, 544
427, 1094, 188, 1615, 563
428, 1108, 201, 1593, 551
430, 1092, 191, 1610, 564
431, 1092, 197, 1600, 563
432, 1087, 197, 1595, 563
433, 1102, 188, 1595, 543
436, 1103, 203, 1565, 536
437, 1089, 202, 1574, 552
438, 932, 160, 1598, 639
439, 938, 193, 1604, 672
440, 1074, 229, 1598, 606
441, 991, 215, 1613, 662
442, 923, 204, 1589, 683
443, 973, 210, 1602, 662
444, 913, 198, 1612, 701
445, 909, 194, 1619, 705
446, 958, 228, 1580, 675
447, 936, 238, 1574, 697
449, 947, 238, 1576, 690
450, 941, 227, 1585, 690
453, 926, 229, 1592, 708
454, 932, 213, 1598, 692
480, 819, 549, 1281, 882
517, 815, 324, 1308, 679
602, 386, 250, 910, 627
603, 378, 238, 910, 620
605, 371, 235, 895, 612
606, 378, 221, 902, 598
608, 382, 218, 900, 591
609, 402, 216, 895, 571
612, 395, 196, 903, 562
613, 374, 189, 914, 578
615, 378, 193, 902, 570
616, 357, 180, 917, 582
617, 379, 197, 897, 570
618, 352, 189, 911, 591
619, 352, 189, 911, 591
620, 395, 182, 903, 548
628, 766, 206, 1087, 437
629, 760, 202, 1102, 448
631, 411, 198, 904, 553
632, 760, 202, 1102, 448
632, 406, 200, 903, 558
633, 760, 202, 1102, 448
633, 395, 191, 903, 557
637, 338, 167, 964, 617
638, 359, 187, 951, 613
639, 350, 188, 949, 619
640, 344, 186, 954, 625
643, 362, 207, 917, 606
644, 766, 206, 1087, 437
644, 362, 207, 917, 606
646, 775, 214, 1096, 445
648, 767, 212, 1088, 443
649, 765, 205, 1086, 436
650, 768, 213, 1089, 444
651, 761, 196, 1082, 427
652, 763, 200, 1084, 431
653, 763, 200, 1084, 431
654, 762, 201, 1083, 432
655, 763, 200, 1084, 431
656, 764, 199, 1085, 430
657, 764, 199, 1085, 430
658, 764, 205, 1085, 436
659, 767, 202, 1088, 433
660, 767, 202, 1088, 433
661, 767, 202, 1088, 433
662, 767, 202, 1088, 433
663, 767, 202, 1088, 433
664, 766, 201, 1087, 432
665, 766, 201, 1087, 432
666, 766, 201, 1087, 432
667, 767, 202, 1088, 433
668, 767, 202, 1088, 433
669, 767, 205, 1088, 436
670, 765, 200, 1086, 431
671, 770, 212, 1091, 443
674, 775, 214, 1096, 445
675, 775, 214, 1096, 445
676, 766, 206, 1087, 437
677, 770, 206, 1091, 437
678, 766, 206, 1087, 437
679, 766, 206, 1087, 437
680, 383, 211, 915, 593
681, 344, 186, 954, 625
682, 344, 186, 954, 625
683, 444, 194, 906, 527
685, 342, 187, 934, 613
686, 375, 195, 917, 585
687, 372, 195, 916, 587
688, 334, 194, 926, 620
689, 343, 201, 920, 616
690, 355, 222, 910, 621
694, 355, 207, 910, 606
695, 355, 207, 910, 606
697, 355, 207, 910, 606
701, 752, 181, 1094, 427
701, 342, 196, 919, 611
702, 760, 196, 1097, 438
702, 333, 194, 925, 620
703, 760, 196, 1097, 438
706, 760, 202, 1102, 448
707, 355, 200, 910, 599
708, 760, 202, 1102, 448
708, 355, 200, 910, 599
709, 355, 200, 910, 599
710, 355, 200, 910, 599
718, 760, 202, 1102, 448
719, 766, 206, 1087, 437
719, 355, 200, 910, 599
720, 333, 190, 916, 609
721, 333, 190, 916, 609
722, 355, 200, 910, 599
724, 770, 199, 1091, 430
725, 770, 197, 1091, 428
726, 766, 197, 1087, 428
726, 331, 182, 960, 634
727, 773, 198, 1094, 429
728, 774, 195, 1095, 426
729, 778, 203, 1099, 434
877, 924, 240, 1386, 573
878, 935, 208, 1420, 558
879, 928, 215, 1452, 592
880, 944, 214, 1425, 560
881, 943, 206, 1440, 564
882, 944, 201, 1462, 574
883, 933, 213, 1475, 603
884, 939, 216, 1481, 606
885, 946, 222, 1482, 608
886, 944, 222, 1476, 604
887, 942, 222, 1478, 608
888, 957, 226, 1465, 592
889, 955, 222, 1479, 599
890, 944, 228, 1476, 610
891, 945, 225, 1469, 602
892, 944, 214, 1484, 602
893, 936, 212, 1478, 602
894, 936, 214, 1476, 602
895, 946, 204, 1492, 596
896, 946, 218, 1482, 604
897, 942, 214, 1478, 600
898, 938, 218, 1474, 604
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901, 946, 196, 1454, 562
902, 950, 209, 1449, 568
903, 920, 182, 1462, 572
904, 936, 206, 1444, 572
905, 952, 208, 1414, 541
907, 943, 203, 1405, 536
908, 938, 208, 1400, 541
1030, 592, 222, 1054, 555
1033, 553, 219, 1089, 605
1034, 593, 213, 1086, 568
1036, 496, 182, 1125, 634
1091, 538, 178, 1182, 641
1092, 510, 171, 1183, 655
1123, 621, 207, 1176, 606
1125, 635, 228, 1159, 605
1126, 1008, 178, 1345, 420
1166, 921, 200, 1445, 577
1168, 926, 216, 1419, 571
1176, 926, 201, 1419, 556
1295, 1010, 176, 1331, 407
1302, 575, 203, 1167, 629
1306, 576, 208, 1159, 627
1308, 561, 195, 1153, 621
1320, 594, 200, 1149, 599

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@ -0,0 +1,97 @@
import argparse
import os
def dir_path(string):
if os.path.exists(string):
return string
else:
raise NotADirectoryError(string)
def init_argparse() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(
prog="FaceDetection",
usage="%(prog)s [OPTION]",
description="Run face localization"
)
parser.add_argument(
"ground_truth", type=dir_path, help="ground truth file"
)
parser.add_argument(
"test_file", type=dir_path, help="file to compare to the ground truth"
)
parser.add_argument(
"out_file", help="the file to write the output to"
)
return parser
multiplication_factor = 0.05
def get_adjustment_amount(imgSize, x1, y1, x2, y2):
# find the difference between the left gap and the right gap, divide it by two, and multiply it by the speed scale
horizontal_adjustment = multiplication_factor * (x1 - (imgSize[0] - x2)) / 2
vertical_adjustment = multiplication_factor * (y1 - (imgSize[0] - y2)) / 2
return [horizontal_adjustment, vertical_adjustment]
parser = init_argparse()
args = parser.parse_args()
class FrameBox:
frame_number: int
top_left: tuple
bottom_right: tuple
def __init__(self, frame_number, x1, y1, x2, y2):
self.frame_number = frame_number
self.top_left = (x1, y1)
self.bottom_right = (x2, y2)
ground_truth = []
with open(args.ground_truth, 'r') as gt_file:
lines = gt_file.readlines()
for line in lines:
items = line.split(",")
ground_truth.append(FrameBox(int(items[0].strip()), int(items[1].strip()), int(items[2].strip()), int(items[3].strip()), int(items[4].strip())))
test_results = []
with open(args.test_file, 'r') as test_file:
lines = test_file.readlines()
for line in lines:
items = line.split(",")
test_results.append(FrameBox(int(items[0].strip()), int(items[1].strip()), int(items[2].strip()), int(items[3].strip()), int(items[4].strip())))
test_fb: FrameBox
gt_frame: FrameBox
last_frame_num = 0
average_sum = 0
average_count = 0
print("length of test file: " + str(len(test_results)))
for test_fb in test_results:
# make
def bring_up_gt():
if test_fb.frame_number > ground_truth[0].frame_number:
ground_truth.pop(0)
bring_up_gt()
bring_up_gt()
assert(ground_truth[0].frame_number == test_fb.frame_number)
gt_frame = ground_truth[0]
gt_adjustment = get_adjustment_amount((1920, 1000), gt_frame.top_left[0], gt_frame.top_left[1], gt_frame.bottom_right[0], gt_frame.bottom_right[1])
test_adjustment = get_adjustment_amount((1920, 1000), test_fb.top_left[0], test_fb.top_left[1], test_fb.bottom_right[0], test_fb.bottom_right[1])
if last_frame_num != test_fb.frame_number and average_count != 0:
with open(args.out_file, 'a') as out_file:
out_file.write(f"{average_sum},\n")
average_sum = 0
average_count = 0
average_count += 1
# get the average
average_sum += abs(( (gt_adjustment[0] - test_adjustment[0]) + (gt_adjustment[1] - test_adjustment[1]) ) / 2)
last_frame_num = test_fb.frame_number

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validation/final.xlsx Normal file

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@ -1,4 +1,3 @@
frame_number, top_left_x, top_left_y, bottom_right_x, bottom_right_y
0, 856, 189, 1202, 623
1, 856, 189, 1202, 623
2, 857, 189, 1203, 623