Mitosis Detection Results: A Comparative Analysis of Published Pretrained Models and Reproduce Training Approaches Using Domain Adversarial RetinaNet #5
Description
Hello, firstly, I'd like to express our gratitude for the opportunity to contribute to the advancement of mitosis detection and the associated challenges. We are currently engaged in scientific research focused on mitosis detection, and in our pursuit, we've come across the MIDOG21 and MIDOG22 datasets, which are renowned for their extensive and diverse content.
Our attention was drawn to a proposed 'baseline' methodology known as Domain Adversarial RetinaNet, which we believe holds promise for our objectives. We endeavoured to employ this methodology by utilizing both the published pretrained model and conducting our own training and inference processes. During this endeavour, we ensured consistency by employing the same MIDOG slides for training purposes.
However, upon comparing the results obtained from the pretrained model and our own trained model, we encountered discrepancies. On the left, we have the results obtained from the published pretrained model, while on the right, we present the results from our trained model. In your paper [link], a threshold of 0.64 is mentioned, which we adhered to in both cases. Additionally, we meticulously examined the docker code for inference and the implementation for patching to ensure conformity in parameters and methodology.
Despite these efforts, the observed disparities persist, prompting us to seek clarification and possibly identify areas where our approach may require refinement. We are keen to address these challenges and enhance the efficacy of mitosis detection methodology the below you can see our training process metrics and loss. We could not see any not expected situation. This model got fit.
epoch train_loss valid_loss pascal_voc_metric_by_distance_da BBloss focal_loss domain_loss total acc AP-mitotic figure time
0 0.785450 0.983057 0.346603 0.202706 0.779731 0.000620 0.736207 0.977500 0.346603 09:26
Better model found at epoch 0 with total value: 0.736207127571106.
1 0.542444 0.610519 0.690280 0.142023 0.468416 0.000080 0.457749 0.992000 0.690280 07:01
Better model found at epoch 1 with total value: 0.45774924755096436.
2 0.450877 0.469345 0.808177 0.127178 0.342132 0.000035 0.351947 0.994000 0.808177 06:05
Better model found at epoch 2 with total value: 0.35194727778434753.
3 0.331436 0.378063 0.868382 0.099184 0.278862 0.000017 0.283518 0.996000 0.868382 05:42
Better model found at epoch 3 with total value: 0.2835179567337036.
4 0.327526 0.312038 0.895164 0.081804 0.230220 0.000014 0.234004 0.994500 0.895164 05:26
Better model found at epoch 4 with total value: 0.23400427401065826.
5 0.266648 0.284434 0.899722 0.074652 0.209772 0.000010 0.213308 0.996500 0.899722 05:12
Better model found at epoch 5 with total value: 0.21330773830413818.
6 0.258341 0.299516 0.921162 0.068209 0.231297 0.000011 0.224619 0.996500 0.921162 05:06
7 0.254432 0.251472 0.906898 0.060052 0.191414 0.000005 0.188594 0.996000 0.906898 05:00
Better model found at epoch 7 with total value: 0.18859417736530304.
8 0.237483 0.261316 0.906031 0.066721 0.194590 0.000005 0.195978 0.995500 0.906031 04:58
9 0.224526 0.231317 0.916301 0.056809 0.174500 0.000008 0.173473 0.993000 0.916301 04:56
Better model found at epoch 9 with total value: 0.17347344756126404.
10 0.222153 0.237260 0.916550 0.061097 0.176161 0.000002 0.177942 0.998000 0.916550 04:56
11 0.236798 0.223430 0.937565 0.052226 0.171199 0.000005 0.167563 0.995500 0.937565 04:56
Better model found at epoch 11 with total value: 0.16756345331668854.
12 0.196236 0.230294 0.925636 0.060864 0.169403 0.000027 0.172672 0.985000 0.925636 04:54
13 0.197627 0.226272 0.937331 0.057529 0.168739 0.000004 0.169697 0.992500 0.937331 04:52
14 0.214247 0.219538 0.940474 0.056912 0.162621 0.000005 0.164645 0.994000 0.940474 04:53
Better model found at epoch 14 with total value: 0.1646449863910675.
15 0.175549 0.224067 0.952182 0.048183 0.175883 0.000001 0.168048 0.999000 0.952182 04:53
16 0.189039 0.218559 0.913038 0.052150 0.166405 0.000004 0.163912 0.994500 0.913038 04:52
Better model found at epoch 16 with total value: 0.16391249001026154.
17 0.172550 0.204367 0.937197 0.048504 0.155858 0.000005 0.153267 0.992500 0.937197 04:51
Better model found at epoch 17 with total value: 0.15326663851737976.
18 0.187031 0.214273 0.905593 0.047507 0.166760 0.000005 0.160696 0.994500 0.905593 04:52
19 0.186904 0.221622 0.948327 0.054655 0.166962 0.000005 0.166208 0.994000 0.948327 04:52
20 0.202084 0.249369 0.919916 0.050631 0.198738 0.000001 0.187025 0.998500 0.919916 04:51
21 0.156743 0.193121 0.942234 0.044848 0.148140 0.000133 0.144607 0.968500 0.942234 04:52
Better model found at epoch 21 with total value: 0.14460746943950653.
22 0.182503 0.199949 0.944177 0.050305 0.149634 0.000009 0.149946 0.992500 0.944177 04:50
23 0.180590 0.197966 0.948764 0.049220 0.148709 0.000037 0.148410 0.971500 0.948764 04:51
24 0.164153 0.169926 0.942608 0.046240 0.123659 0.000027 0.127398 0.976500 0.942608 04:53
Better model found at epoch 24 with total value: 0.12739767134189606.
25 0.193322 0.188513 0.941290 0.045644 0.142856 0.000014 0.141360 0.989500 0.941290 04:51
26 0.180413 0.197304 0.951649 0.052441 0.144830 0.000032 0.147921 0.987000 0.951649 04:50
27 0.159821 0.206688 0.940152 0.057649 0.148869 0.000170 0.154719 0.936000 0.940152 04:52
28 0.158653 0.288118 0.949677 0.054382 0.233663 0.000073 0.215960 0.969000 0.949677 04:53
29 0.156991 0.266293 0.907901 0.047837 0.218218 0.000239 0.199302 0.919000 0.907901 04:51
30 0.162830 0.195992 0.928350 0.049219 0.136453 0.010320 0.128934 0.594000 0.928350 04:51
31 0.180620 0.189446 0.945017 0.042536 0.135710 0.011201 0.122484 0.470500 0.945017 04:51
Better model found at epoch 31 with total value: 0.12248370051383972.
32 0.189680 0.204291 0.930798 0.044373 0.148940 0.010978 0.134007 0.521000 0.930798 04:51
33 0.171617 0.249374 0.915211 0.051483 0.182120 0.015771 0.159431 0.340000 0.915211 04:52
34 0.172175 0.272676 0.914635 0.055209 0.202369 0.015098 0.178085 0.379500 0.914635 04:52
35 0.197487 0.209198 0.936295 0.045366 0.148199 0.015633 0.129541 0.334500 0.936295 04:51
36 0.160086 0.207027 0.943772 0.050380 0.145067 0.011580 0.135006 0.522500 0.943772 04:52
37 0.168441 0.213366 0.932930 0.044194 0.153431 0.015741 0.132478 0.314500 0.932930 04:51
38 0.180116 0.196610 0.958032 0.043068 0.137225 0.016317 0.118902 0.298000 0.958032 04:52
Better model found at epoch 38 with total value: 0.11890240758657455.
39 0.190928 0.203397 0.942083 0.047760 0.139312 0.016325 0.123979 0.343000 0.942083 04:51
40 0.163907 0.222326 0.932640 0.044493 0.162745 0.015088 0.140340 0.311500 0.932640 04:51
41 0.163990 0.212104 0.934992 0.048361 0.147599 0.016143 0.130827 0.303500 0.934992 04:51
42 0.179682 0.220284 0.949341 0.049924 0.154292 0.016068 0.137094 0.299000 0.949341 04:52
43 0.161919 0.200178 0.947384 0.046068 0.141197 0.012914 0.127535 0.423500 0.947384 04:51
44 0.156455 0.235900 0.927150 0.047400 0.172466 0.016034 0.148866 0.340500 0.927150 04:50
45 0.154492 0.225369 0.941197 0.042586 0.166588 0.016195 0.140686 0.277000 0.941197 04:50
46 0.167239 0.217614 0.936051 0.047130 0.154223 0.016261 0.134754 0.321500 0.936051 04:50
47 0.142298 0.197371 0.943239 0.042996 0.138553 0.015822 0.120340 0.323000 0.943239 04:50
48 0.181488 0.319136 0.903015 0.055773 0.246466 0.016898 0.209781 0.306000 0.903015 04:49
49 0.183666 0.253149 0.939159 0.047853 0.191290 0.014006 0.165351 0.427000 0.939159 04:50
50 0.167431 0.261053 0.910725 0.047439 0.197972 0.015642 0.168417 0.334500 0.910725 04:46
51 0.156896 0.220033 0.936470 0.046075 0.159330 0.014628 0.139425 0.370500 0.936470 04:46
52 0.171971 0.204539 0.925098 0.041754 0.148185 0.014599 0.127856 0.432000 0.925098 04:47
53 0.161871 0.220858 0.927294 0.047065 0.158594 0.015199 0.139046 0.350500 0.927294 04:46
54 0.159982 0.208867 0.938260 0.040258 0.151700 0.016909 0.127060 0.294500 0.938260 04:47
55 0.153658 0.209263 0.943699 0.039806 0.155189 0.014268 0.131979 0.387500 0.943699 04:47
56 0.185696 0.208002 0.950126 0.041127 0.152948 0.013927 0.131630 0.439000 0.950126 04:48
57 0.144182 0.179400 0.950784 0.040102 0.123425 0.015874 0.106771 0.312000 0.950784 04:47
Better model found at epoch 57 with total value: 0.10677138715982437.
58 0.176117 0.202111 0.947194 0.047481 0.137643 0.016986 0.121858 0.334500 0.947194 04:48
59 0.144845 0.177567 0.940757 0.045533 0.116166 0.015869 0.105405 0.287500 0.940757 04:47
Better model found at epoch 59 with total value: 0.10540502518415451.
60 0.156287 0.227368 0.944799 0.038740 0.172753 0.015875 0.142744 0.374000 0.944799 04:48
61 0.160707 0.184147 0.950982 0.045141 0.123691 0.015315 0.111309 0.314000 0.950982 04:48
62 0.150024 0.200020 0.957444 0.043341 0.142159 0.014520 0.124606 0.396500 0.957444 04:47
63 0.162003 0.201243 0.946226 0.038524 0.145131 0.017587 0.120154 0.282000 0.946226 04:47
64 0.138322 0.182657 0.948850 0.040711 0.127395 0.014552 0.111528 0.417000 0.948850 04:47
65 0.144133 0.200995 0.934477 0.042571 0.143671 0.014753 0.124928 0.352500 0.934477 04:48
66 0.127142 0.190230 0.943350 0.041578 0.132417 0.016235 0.114262 0.309000 0.943350 04:47
67 0.155443 0.240632 0.937342 0.042395 0.182529 0.015707 0.152986 0.341500 0.937342 04:47
68 0.144572 0.171364 0.945882 0.039459 0.116960 0.014945 0.102369 0.352500 0.945882 04:48
Better model found at epoch 68 with total value: 0.10236901044845581.
69 0.161703 0.195337 0.940093 0.047317 0.132942 0.015078 0.120115 0.362500 0.940093 04:48
70 0.144342 0.336308 0.949807 0.040224 0.281974 0.014110 0.227539 0.370500 0.949807 04:47
71 0.144123 0.180164 0.965901 0.043903 0.121420 0.014840 0.109152 0.338500 0.965901 04:47
72 0.141794 0.208556 0.938842 0.043725 0.147690 0.017140 0.126421 0.285500 0.938842 04:57
73 0.149875 0.186927 0.958077 0.045622 0.124439 0.016865 0.110681 0.288000 0.958077 04:55
74 0.139127 0.236158 0.940866 0.045136 0.175814 0.015209 0.150503 0.379000 0.940866 04:46
75 0.121149 0.283810 0.922071 0.045367 0.222432 0.016011 0.184839 0.290000 0.922071 04:47
76 0.151578 0.210009 0.955442 0.044814 0.148047 0.017148 0.127498 0.247500 0.955442 04:47
77 0.141308 0.246644 0.941830 0.041339 0.189283 0.016022 0.156944 0.299000 0.941830 04:47
78 0.142363 1.521045 0.928240 0.059404 1.439179 0.022461 1.101476 0.334000 0.928240 04:47
79 0.133982 0.174231 0.943210 0.042523 0.117101 0.014607 0.105111 0.421500 0.943210 04:48
80 0.142308 0.211360 0.933219 0.039926 0.156366 0.015068 0.132151 0.323500 0.933219 04:47
81 0.141441 0.190722 0.947818 0.044007 0.130053 0.016661 0.113884 0.328000 0.947818 04:47
82 0.140780 0.225875 0.941220 0.042266 0.166093 0.017516 0.138752 0.295000 0.941220 04:47
83 0.160125 0.198652 0.932029 0.041318 0.141601 0.015734 0.121455 0.363500 0.932029 04:47
84 0.132766 0.185648 0.948422 0.044723 0.125424 0.015501 0.112109 0.313500 0.948422 04:46
85 0.147027 0.204072 0.934485 0.044901 0.144499 0.014672 0.127379 0.357500 0.934485 04:48
86 0.155001 0.198236 0.934426 0.042693 0.139123 0.016420 0.119941 0.310000 0.934426 04:47
87 0.129572 0.187880 0.927613 0.039618 0.132512 0.015750 0.113348 0.318000 0.927613 04:46
88 0.119754 0.219112 0.947549 0.047004 0.155832 0.016276 0.135851 0.315500 0.947549 04:47
89 0.123231 0.236715 0.938996 0.041993 0.179774 0.014947 0.151378 0.361000 0.938996 04:47
90 0.133879 0.238884 0.955843 0.040154 0.182933 0.015797 0.151518 0.296500 0.955843 04:47
91 0.150030 0.211925 0.936782 0.043796 0.152163 0.015966 0.131003 0.309500 0.936782 04:47
92 0.132356 0.188554 0.950641 0.042847 0.130123 0.015585 0.114143 0.341000 0.950641 04:48
93 0.109335 0.237328 0.950354 0.041139 0.179571 0.016618 0.148914 0.255500 0.950354 04:47
94 0.114027 0.211238 0.944948 0.043280 0.151887 0.016071 0.130305 0.293000 0.944948 04:47
95 0.140208 0.216891 0.938503 0.045852 0.153699 0.017340 0.132323 0.307500 0.938503 04:41
96 0.110975 0.281596 0.913604 0.045401 0.219968 0.016228 0.182799 0.271500 0.913604 04:39
97 0.137016 0.178768 0.950799 0.038754 0.124168 0.015847 0.106345 0.304000 0.950799 04:39
98 0.134312 0.208802 0.943562 0.044228 0.149622 0.014952 0.130435 0.385000 0.943562 04:36
99 0.136337 0.178562 0.962772 0.039064 0.122319 0.017179 0.103858 0.258000 0.962772 04:40
100 0.122893 0.183780 0.940092 0.043687 0.122852 0.017242 0.107662 0.221000 0.940092 04:39
101 0.134159 0.196005 0.956618 0.038617 0.141561 0.015828 0.119306 0.396500 0.956618 04:39
102 0.114882 0.225477 0.963191 0.039846 0.169361 0.016271 0.140634 0.331500 0.963191 04:40
103 0.125989 0.203896 0.918097 0.035930 0.153425 0.014542 0.127474 0.389500 0.918097 04:39
104 0.120106 0.184987 0.965017 0.040252 0.129131 0.015604 0.111433 0.339500 0.965017 04:40
105 0.136907 0.204692 0.957192 0.038823 0.149435 0.016433 0.124760 0.254500 0.957192 04:40
106 0.147546 0.291626 0.951552 0.041585 0.234377 0.015664 0.191307 0.326500 0.951552 04:41
107 0.372598 0.201593 0.947389 0.046870 0.139780 0.014943 0.125045 0.357500 0.947389 04:41
108 0.121295 0.189618 0.953973 0.039269 0.134829 0.015520 0.115053 0.340500 0.953973 04:41
109 0.109155 0.177106 0.956813 0.037708 0.122441 0.016958 0.103153 0.252000 0.956813 04:41
110 0.111040 0.212543 0.955270 0.042335 0.150066 0.020142 0.124158 0.188500 0.955270 04:40
111 0.125227 0.201385 0.947159 0.038268 0.145709 0.017408 0.120575 0.279500 0.947159 04:40
112 0.114964 0.201367 0.939172 0.044779 0.140439 0.016149 0.122765 0.284500 0.939172 04:40
113 0.112271 0.220891 0.930691 0.048382 0.155217 0.017292 0.135407 0.316500 0.930691 04:39
114 0.120581 0.190376 0.931197 0.038950 0.135539 0.015886 0.114981 0.333500 0.931197 04:40
115 0.116819 0.212193 0.952629 0.042305 0.154009 0.015879 0.131357 0.320500 0.952629 04:41
116 0.151188 0.195947 0.952565 0.039917 0.140683 0.015347 0.120103 0.326000 0.952565 04:40
117 0.113476 0.230768 0.945555 0.036548 0.179414 0.014806 0.147165 0.410500 0.945555 04:39
118 0.098747 0.236197 0.941359 0.042683 0.177102 0.016412 0.148427 0.249000 0.941359 04:40
119 0.119915 0.209336 0.958719 0.042855 0.151412 0.015069 0.130632 0.373500 0.958719 04:40
120 0.114365 0.181502 0.965282 0.040438 0.125013 0.016052 0.108036 0.309500 0.965282 04:41
121 0.117941 0.197289 0.941160 0.040243 0.140833 0.016213 0.119594 0.290000 0.941160 04:41
122 0.096139 0.552260 0.943592 0.035965 0.500501 0.015794 0.386555 0.314000 0.943592 04:40
123 0.127164 0.175807 0.959735 0.038272 0.122145 0.015389 0.104924 0.363000 0.959735 04:40
124 0.096579 0.209624 0.957389 0.041025 0.153727 0.014872 0.131192 0.399500 0.957389 04:41
125 0.118317 0.183046 0.951172 0.039188 0.129143 0.014715 0.111533 0.403000 0.951172 04:41
126 0.103399 0.205166 0.942465 0.040970 0.148367 0.015829 0.126174 0.314000 0.942465 04:41
127 0.101435 0.194475 0.955980 0.036799 0.141671 0.016005 0.117848 0.281000 0.955980 04:41
128 0.102088 0.187990 0.945449 0.035907 0.134858 0.017225 0.110849 0.284000 0.945449 04:42
129 0.098437 0.856650 0.955877 0.037770 0.802758 0.016122 0.614274 0.256500 0.955877 04:42
130 0.096596 0.185124 0.958848 0.040357 0.131326 0.013441 0.115321 0.421500 0.958848 04:42
131 0.100013 0.206874 0.938703 0.036957 0.154297 0.015620 0.127821 0.318000 0.938703 04:41
132 0.107007 0.201512 0.951709 0.039248 0.146260 0.016004 0.123128 0.313000 0.951709 04:42
133 0.113583 0.184317 0.946862 0.037286 0.130789 0.016242 0.109814 0.284500 0.946862 04:41
134 0.097388 0.184101 0.958423 0.038728 0.128322 0.017051 0.108237 0.240500 0.958423 04:42
135 0.085454 0.197828 0.956510 0.040150 0.141635 0.016042 0.120297 0.292500 0.956510 04:42
136 0.105328 0.183154 0.956231 0.040204 0.127476 0.015474 0.110287 0.346000 0.956231 04:49
137 0.096226 0.215639 0.940306 0.038909 0.159970 0.016760 0.132399 0.292500 0.940306 04:54
138 0.098154 0.183644 0.961170 0.037469 0.130214 0.015961 0.109802 0.298000 0.961170 04:51
139 0.093971 0.201110 0.943272 0.041491 0.143804 0.015814 0.123157 0.328000 0.943272 04:48
140 0.083270 0.189820 0.958757 0.037109 0.140375 0.012336 0.120777 0.513000 0.958757 04:51
141 0.098914 0.182260 0.954193 0.037346 0.129928 0.014987 0.110468 0.378000 0.954193 04:50
142 0.077391 0.219728 0.951431 0.040115 0.163940 0.015673 0.137368 0.337500 0.951431 04:49
143 0.096102 0.168688 0.943726 0.035525 0.116736 0.016427 0.097769 0.290000 0.943726 04:49
Better model found at epoch 143 with total value: 0.09776861220598221.
144 0.094300 0.189119 0.942578 0.035220 0.136192 0.017707 0.110852 0.277500 0.942578 04:47
145 0.092052 0.162262 0.945067 0.039021 0.107420 0.015820 0.094011 0.299000 0.945067 04:42
Better model found at epoch 145 with total value: 0.09401094913482666.
146 0.088274 0.187951 0.944375 0.037093 0.133730 0.017129 0.110988 0.215500 0.944375 04:42
147 0.095171 0.204087 0.956507 0.035841 0.152058 0.016187 0.124737 0.270500 0.956507 04:42
148 0.088965 0.206030 0.936347 0.038430 0.149573 0.018027 0.122975 0.242000 0.936347 04:42
149 0.097582 0.192821 0.944700 0.038650 0.137276 0.016895 0.115050 0.252000 0.944700 04:42
150 0.096938 0.185611 0.956914 0.044542 0.124933 0.016136 0.110971 0.264000 0.956914 04:41
151 0.086486 0.245326 0.938044 0.039749 0.189695 0.015882 0.156201 0.348000 0.938044 04:42
152 0.077055 0.222055 0.949954 0.037463 0.169020 0.015572 0.139291 0.308500 0.949954 04:41
153 0.083291 0.185139 0.953293 0.039853 0.128375 0.016912 0.109259 0.272500 0.953293 04:42
154 0.094479 0.179118 0.941715 0.036134 0.126636 0.016348 0.105729 0.255000 0.941715 04:41
155 0.083417 0.192812 0.947840 0.037576 0.138610 0.016627 0.115512 0.234500 0.947840 04:41
156 0.093022 0.175765 0.955580 0.034677 0.125116 0.015972 0.103873 0.319000 0.955580 04:41
157 0.100234 0.204923 0.944169 0.038705 0.151343 0.014874 0.127662 0.388000 0.944169 04:41
158 0.072664 0.237324 0.949212 0.038611 0.182809 0.015903 0.150162 0.282000 0.949212 04:41
159 0.086279 0.209794 0.947191 0.041186 0.152529 0.016078 0.129209 0.261000 0.947191 04:41
160 0.095580 0.175932 0.960151 0.036544 0.123670 0.015719 0.104441 0.331500 0.960151 04:41
161 0.078650 0.194813 0.956329 0.040617 0.137913 0.016283 0.117614 0.275000 0.956329 04:41
162 0.085086 0.200761 0.948708 0.041245 0.143302 0.016214 0.122196 0.306500 0.948708 04:41
163 0.084111 0.212135 0.948223 0.039692 0.156472 0.015972 0.131151 0.285000 0.948223 04:41
164 0.093526 0.196454 0.938987 0.037314 0.143250 0.015890 0.119533 0.291000 0.938987 04:41
165 0.087800 0.191732 0.937500 0.038256 0.137535 0.015942 0.115901 0.283500 0.937500 04:41
166 0.090100 0.214589 0.945305 0.037079 0.161629 0.015881 0.133150 0.274000 0.945305 04:41
167 0.088303 0.195450 0.954410 0.036996 0.142788 0.015667 0.119171 0.348000 0.954410 04:41
168 0.069431 0.187785 0.949960 0.039381 0.132866 0.015538 0.113647 0.359500 0.949960 04:40
169 0.086145 0.180941 0.957234 0.037594 0.127677 0.015670 0.108283 0.331000 0.957234 04:41
170 0.073757 0.221506 0.954738 0.038582 0.166900 0.016025 0.138086 0.297000 0.954738 04:41
171 0.098995 0.209120 0.952302 0.037685 0.155223 0.016212 0.128469 0.292000 0.952302 04:41
172 0.081653 0.202188 0.947124 0.037304 0.148981 0.015903 0.123811 0.293500 0.947124 04:40
173 0.077004 0.212156 0.941345 0.034953 0.161438 0.015765 0.131529 0.323000 0.941345 04:40
174 0.072520 0.192403 0.953131 0.037626 0.138811 0.015966 0.116362 0.303000 0.953131 04:40
175 0.081657 0.185333 0.943647 0.036804 0.132911 0.015618 0.111669 0.333000 0.943647 04:40
176 0.073755 0.214307 0.951647 0.040487 0.158114 0.015706 0.133244 0.308500 0.951647 04:40
177 0.073110 0.245446 0.949097 0.035771 0.193520 0.016155 0.155814 0.276500 0.949097 04:50
178 0.083714 0.226262 0.942498 0.039632 0.170825 0.015806 0.142037 0.309500 0.942498 04:46
179 0.072813 0.211184 0.945893 0.038751 0.156497 0.015936 0.130500 0.326000 0.945893 04:44
180 0.081544 0.207568 0.955574 0.036302 0.155196 0.016070 0.127553 0.295500 0.955574 04:44
181 0.070548 0.210342 0.963228 0.035853 0.158099 0.016390 0.129075 0.255000 0.963228 04:43
182 0.078953 0.193935 0.947417 0.036749 0.140748 0.016438 0.116685 0.253000 0.947417 04:44
183 0.082916 0.198010 0.956960 0.036024 0.145684 0.016302 0.119979 0.256000 0.956960 04:43
184 0.074588 0.249540 0.944067 0.039287 0.193984 0.016269 0.158684 0.270000 0.944067 04:41
185 0.082477 0.215001 0.955480 0.036390 0.162589 0.016022 0.133212 0.325000 0.955480 04:41
186 0.078518 0.213460 0.947624 0.036022 0.161354 0.016084 0.131948 0.299000 0.947624 04:50
187 0.078276 0.212622 0.943323 0.034626 0.161943 0.016054 0.131373 0.313000 0.943323 04:59
188 0.102532 0.289659 0.929094 0.036452 0.237158 0.016049 0.189158 0.302000 0.929094 04:59
189 0.103186 0.294890 0.960607 0.042828 0.236151 0.015911 0.193323 0.312000 0.960607 04:54
190 0.084295 0.227399 0.942876 0.038936 0.172526 0.015937 0.142660 0.338500 0.942876 04:54
191 0.080735 0.198275 0.958823 0.035594 0.146504 0.016176 0.120397 0.290000 0.958823 04:57
192 0.081973 0.214822 0.949846 0.035695 0.163057 0.016070 0.132994 0.296500 0.949846 04:57
193 0.093528 0.236086 0.942166 0.038842 0.181096 0.016148 0.148805 0.286500 0.942166 04:44
194 0.076362 0.241348 0.949359 0.036218 0.188955 0.016175 0.152704 0.283500 0.949359 04:47
195 0.080417 0.330995 0.958705 0.036631 0.278227 0.016137 0.220007 0.283000 0.958705 04:43
196 0.084029 0.226262 0.948254 0.038368 0.171705 0.016189 0.141365 0.276500 0.948254 04:46
197 0.081667 0.210475 0.954809 0.037743 0.156563 0.016168 0.129562 0.291000 0.954809 04:46
198 0.076088 0.211807 0.928583 0.039940 0.155625 0.016241 0.130432 0.269500 0.928583 04:46
199 0.080302 0.223791 0.945904 0.036197 0.171338 0.016257 0.139394 0.262500 0.945904 04:45
Saved model as DA_RetinaNet
Our aim is comparing our proposed methodology with yours.
So Could you help me with issue?