[CF]提交文件

This commit is contained in:
songbingle 2025-06-06 15:44:52 +08:00
parent 74acac6b03
commit 421ef71e66
36 changed files with 101 additions and 4 deletions

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@ -4,3 +4,98 @@ epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),met
3,50.8526,0.84409,2.14524,0.93347,0.01141,0.97872,0.95462,0.65143,0.72545,2.96458,0.86384,0.000509704,0.000509704,0.000509704 3,50.8526,0.84409,2.14524,0.93347,0.01141,0.97872,0.95462,0.65143,0.72545,2.96458,0.86384,0.000509704,0.000509704,0.000509704
4,68.8891,0.92823,1.93303,0.99896,1,0.17404,0.8576,0.66888,0.93772,3.1365,0.99018,0.00067921,0.00067921,0.00067921 4,68.8891,0.92823,1.93303,0.99896,1,0.17404,0.8576,0.66888,0.93772,3.1365,0.99018,0.00067921,0.00067921,0.00067921
5,88.2008,0.86695,1.72383,0.99086,1,0.14981,0.89164,0.65259,0.85707,3.08949,0.94664,0.000845152,0.000845152,0.000845152 5,88.2008,0.86695,1.72383,0.99086,1,0.14981,0.89164,0.65259,0.85707,3.08949,0.94664,0.000845152,0.000845152,0.000845152
6,108.889,0.9233,1.64537,0.99611,0.00313,0.97872,0.22074,0.15359,1.19903,3.67627,1.40338,0.00100753,0.00100753,0.00100753
7,126.63,0.92474,1.74874,1.01005,1,0.22478,0.9398,0.74549,0.6995,3.02254,1.07775,0.00116634,0.00116634,0.00116634
8,143.386,0.89439,1.541,1.01516,0.96934,0.67287,0.93016,0.70384,0.84448,2.79319,1.07622,0.00132159,0.00132159,0.00132159
9,160.154,1.01923,1.37768,1.04767,0.95661,0.42553,0.84458,0.65549,1.14153,3.14578,1.50441,0.00147328,0.00147328,0.00147328
10,176.531,0.85462,1.4615,1.00649,0.82488,0.401,0.59884,0.42863,0.95452,3.05086,1.07771,0.0016214,0.0016214,0.0016214
11,193.027,0.88501,1.53296,0.99892,0.91788,0.95141,0.96457,0.73447,1.01148,1.98069,1.07153,0.00176596,0.00176596,0.00176596
12,209.352,0.936,1.39373,1.03826,0.86628,0.82979,0.90199,0.67733,1.08629,1.81286,1.03771,0.0017822,0.0017822,0.0017822
13,225.621,0.95074,1.5498,1.01222,0.94283,0.61702,0.78999,0.61324,0.93039,2.10289,0.96341,0.0017624,0.0017624,0.0017624
14,241.911,0.87627,1.35058,0.98415,0.82171,0.82979,0.89473,0.66946,0.96415,1.78842,0.98676,0.0017426,0.0017426,0.0017426
15,258.455,0.89969,1.26147,0.99252,0.88159,0.85106,0.92253,0.6623,1.0348,1.97623,1.03837,0.0017228,0.0017228,0.0017228
16,274.784,0.9107,1.19701,1.04842,0.81433,0.87234,0.91067,0.64013,1.07749,2.33723,1.13321,0.001703,0.001703,0.001703
17,291.033,0.8797,1.19339,1.01255,0.90187,0.93617,0.95235,0.72838,1.0545,1.88516,1.22758,0.0016832,0.0016832,0.0016832
18,307.447,0.86492,1.23953,1.00577,0.9374,0.95587,0.93494,0.6668,0.94737,1.63386,0.95875,0.0016634,0.0016634,0.0016634
19,323.927,0.81989,1.14224,0.9353,0.97176,0.97872,0.96568,0.74768,0.79084,2.04213,0.91647,0.0016436,0.0016436,0.0016436
20,340.644,0.82661,1.05057,1.01933,0.86772,0.97701,0.89158,0.69948,0.80194,2.04703,0.98656,0.0016238,0.0016238,0.0016238
21,356.877,0.82623,1.07653,0.95122,0.91797,0.97872,0.93621,0.74577,0.87056,1.6536,1.23575,0.001604,0.001604,0.001604
22,373.893,0.93091,1.1046,1.00084,0.99713,0.97872,0.97504,0.81712,0.88174,1.24998,1.43402,0.0015842,0.0015842,0.0015842
23,390.374,0.79185,0.97892,0.98414,1,0.9766,0.97504,0.83856,0.85541,1.15924,1.39651,0.0015644,0.0015644,0.0015644
24,406.837,0.77858,0.96501,0.9412,1,0.97516,0.97504,0.82906,0.8962,1.0739,1.39967,0.0015446,0.0015446,0.0015446
25,423.408,0.69471,0.8921,0.92449,0.97863,0.97449,0.97462,0.80796,0.8924,1.12536,1.39023,0.0015248,0.0015248,0.0015248
26,439.924,0.79448,0.94583,1.01777,0.94546,0.97872,0.97254,0.83029,0.85951,1.08172,1.27858,0.001505,0.001505,0.001505
27,456.303,0.75574,0.89269,0.95814,0.99662,0.97872,0.97504,0.8358,0.64848,1.03876,1.01015,0.0014852,0.0014852,0.0014852
28,472.56,0.71507,0.83409,0.94143,0.99683,0.97872,0.97504,0.87181,0.57235,0.98598,0.99489,0.0014654,0.0014654,0.0014654
29,489.005,0.78166,0.86555,0.98982,0.97822,0.97872,0.97504,0.83676,0.78144,1.05176,1.13006,0.0014456,0.0014456,0.0014456
30,505.365,0.74249,0.86108,0.95286,0.9974,0.97872,0.97504,0.84753,0.83641,1.0551,1.25554,0.0014258,0.0014258,0.0014258
31,521.68,0.70916,0.87682,0.97448,0.9963,0.95745,0.97421,0.82212,0.93208,0.98694,1.32275,0.001406,0.001406,0.001406
32,538.031,0.77631,0.87153,0.97965,0.97698,0.97872,0.97462,0.81106,0.89517,0.93599,1.31376,0.0013862,0.0013862,0.0013862
33,554.543,0.74973,0.83324,0.96358,0.99792,0.97872,0.97504,0.84652,0.77113,0.83692,1.18537,0.0013664,0.0013664,0.0013664
34,570.984,0.80141,0.80779,0.97662,0.99646,0.97872,0.97504,0.84518,0.76637,0.95064,1.21416,0.0013466,0.0013466,0.0013466
35,587.277,0.85547,0.88575,1.08871,0.99951,0.97872,0.97504,0.83551,0.76647,1.01295,1.15899,0.0013268,0.0013268,0.0013268
36,604.325,0.767,0.7671,0.95181,1,0.97769,0.97504,0.85141,0.67728,0.95316,1.06362,0.001307,0.001307,0.001307
37,621.429,0.71542,0.79484,0.98779,0.9981,0.95745,0.97421,0.84222,0.73423,0.93986,1.13184,0.0012872,0.0012872,0.0012872
38,637.85,0.76685,0.74774,0.94989,0.99776,0.95745,0.97274,0.80365,0.81724,0.92326,1.21423,0.0012674,0.0012674,0.0012674
39,654.193,0.71727,0.77154,0.93576,1,0.97778,0.97504,0.81219,0.79632,0.79607,1.241,0.0012476,0.0012476,0.0012476
40,670.47,0.73679,0.76367,0.96723,0.9987,0.97872,0.97505,0.82224,0.66771,0.84454,1.02726,0.0012278,0.0012278,0.0012278
41,687.289,0.69753,0.70766,0.93616,0.99866,0.97872,0.97505,0.84836,0.58592,0.78201,0.95605,0.001208,0.001208,0.001208
42,703.805,0.69078,0.75505,0.94243,0.99862,0.97872,0.97505,0.86063,0.55282,0.76261,0.93304,0.0011882,0.0011882,0.0011882
43,720.098,0.69355,0.6699,0.94703,0.99818,0.97872,0.97505,0.87101,0.53047,0.81548,0.94703,0.0011684,0.0011684,0.0011684
44,736.487,0.61083,0.66366,0.89841,0.99775,0.97872,0.97505,0.86761,0.51186,0.74653,0.95031,0.0011486,0.0011486,0.0011486
45,752.747,0.70031,0.70279,0.98732,0.99804,0.97872,0.97505,0.8701,0.50757,0.70518,0.94971,0.0011288,0.0011288,0.0011288
46,769.296,0.62004,0.65034,0.90191,0.99812,0.97872,0.97505,0.8481,0.49729,0.65358,0.95067,0.001109,0.001109,0.001109
47,785.564,0.69383,0.66827,0.93709,0.99739,0.97872,0.97505,0.87732,0.48397,0.63065,0.94863,0.0010892,0.0010892,0.0010892
48,801.985,0.59658,0.59829,0.90597,0.99596,0.97872,0.97505,0.85898,0.51329,0.64556,0.93802,0.0010694,0.0010694,0.0010694
49,818.235,0.62114,0.61166,0.90013,0.99836,0.97872,0.97505,0.87547,0.51048,0.70061,0.93659,0.0010496,0.0010496,0.0010496
50,834.536,0.62591,0.62487,0.9242,0.9987,0.97872,0.97505,0.86005,0.52268,0.71765,0.93612,0.0010298,0.0010298,0.0010298
51,850.84,0.60417,0.59436,0.89844,0.99859,0.97872,0.97505,0.88784,0.50296,0.68031,0.9205,0.00101,0.00101,0.00101
52,867.235,0.67345,0.68685,0.95226,0.99746,0.97872,0.97505,0.87982,0.48112,0.64511,0.9015,0.0009902,0.0009902,0.0009902
53,883.477,0.65875,0.63211,0.89805,0.99761,0.97872,0.97505,0.8855,0.44319,0.64272,0.88555,0.0009704,0.0009704,0.0009704
54,899.777,0.61886,0.64051,0.92091,0.99779,0.97872,0.97505,0.89959,0.39967,0.62697,0.87383,0.0009506,0.0009506,0.0009506
55,916.129,0.58662,0.57316,0.8766,0.99787,0.97872,0.97505,0.90367,0.40999,0.58972,0.87969,0.0009308,0.0009308,0.0009308
56,932.473,0.56885,0.55402,0.86806,0.99816,0.97872,0.97505,0.88802,0.43791,0.56277,0.88202,0.000911,0.000911,0.000911
57,948.702,0.61308,0.631,0.94614,0.99754,0.97872,0.97505,0.86903,0.51987,0.59688,0.89673,0.0008912,0.0008912,0.0008912
58,965.014,0.62221,0.62787,0.93053,0.99653,0.97872,0.97505,0.86344,0.53093,0.6724,0.92493,0.0008714,0.0008714,0.0008714
59,981.468,0.59869,0.61537,0.91599,0.99832,0.97872,0.97505,0.88686,0.53637,0.6404,0.94102,0.0008516,0.0008516,0.0008516
60,997.948,0.67699,0.64553,0.93616,0.99839,0.97872,0.97505,0.89016,0.53426,0.60405,0.93235,0.0008318,0.0008318,0.0008318
61,1014.54,0.54223,0.54748,0.86316,0.99856,0.97872,0.97506,0.9013,0.54016,0.60719,0.93491,0.000812,0.000812,0.000812
62,1030.81,0.57035,0.56477,0.90542,0.99863,0.97872,0.97506,0.87968,0.51468,0.61519,0.90362,0.0007922,0.0007922,0.0007922
63,1047.14,0.56914,0.5558,0.91865,0.99866,0.97872,0.97506,0.88691,0.51397,0.54698,0.90837,0.0007724,0.0007724,0.0007724
64,1063.47,0.55618,0.54987,0.88579,0.99865,0.97872,0.97506,0.90335,0.49993,0.51709,0.89065,0.0007526,0.0007526,0.0007526
65,1079.7,0.53892,0.53695,0.90014,0.99861,0.97872,0.97506,0.90518,0.53615,0.51287,0.90089,0.0007328,0.0007328,0.0007328
66,1096.03,0.52733,0.51237,0.87921,0.99753,0.97872,0.97506,0.89833,0.54082,0.5022,0.90117,0.000713,0.000713,0.000713
67,1112.36,0.51289,0.51338,0.8675,0.99761,0.97872,0.97507,0.91082,0.4392,0.50289,0.87438,0.0006932,0.0006932,0.0006932
68,1129.26,0.51701,0.50177,0.90627,0.99755,0.97872,0.97507,0.90628,0.43663,0.50467,0.87736,0.0006734,0.0006734,0.0006734
69,1145.59,0.55644,0.53077,0.89669,0.99734,0.97872,0.97507,0.9091,0.44588,0.54371,0.88767,0.0006536,0.0006536,0.0006536
70,1162.7,0.5669,0.52751,0.90383,0.99726,0.97872,0.97507,0.91448,0.43112,0.53961,0.88243,0.0006338,0.0006338,0.0006338
71,1179.38,0.52945,0.53576,0.91008,0.99701,0.97872,0.97507,0.91338,0.40923,0.50713,0.86706,0.000614,0.000614,0.000614
72,1195.76,0.5045,0.5,0.83861,0.99672,0.97872,0.97507,0.92336,0.39388,0.45782,0.85291,0.0005942,0.0005942,0.0005942
73,1212.84,0.52684,0.5122,0.86863,0.99873,0.97872,0.97507,0.92278,0.40641,0.50211,0.8596,0.0005744,0.0005744,0.0005744
74,1229.11,0.55294,0.54271,0.88696,0.99862,0.97872,0.97507,0.90759,0.47393,0.51367,0.88525,0.0005546,0.0005546,0.0005546
75,1245.48,0.51732,0.50029,0.85483,0.99845,0.97872,0.97506,0.91187,0.53175,0.48527,0.94813,0.0005348,0.0005348,0.0005348
76,1261.78,0.5022,0.51302,0.8886,0.99847,0.97872,0.97506,0.90642,0.53595,0.47371,0.96317,0.000515,0.000515,0.000515
77,1277.95,0.50634,0.52206,0.87813,0.99855,0.97872,0.97506,0.91129,0.53131,0.4618,0.96477,0.0004952,0.0004952,0.0004952
78,1294.36,0.52087,0.47526,0.84153,0.9986,0.97872,0.97507,0.91053,0.54476,0.44952,0.97,0.0004754,0.0004754,0.0004754
79,1310.72,0.50821,0.45477,0.87197,0.99864,0.97872,0.97507,0.90609,0.53997,0.44403,0.96696,0.0004556,0.0004556,0.0004556
80,1326.99,0.47979,0.47719,0.84969,0.99869,0.97872,0.97507,0.91254,0.51575,0.4359,0.95256,0.0004358,0.0004358,0.0004358
81,1343.24,0.48129,0.44147,0.86231,0.99872,0.97872,0.97507,0.91279,0.48954,0.41942,0.93704,0.000416,0.000416,0.000416
82,1359.76,0.49291,0.45548,0.9074,0.99874,0.97872,0.97507,0.90741,0.48763,0.41879,0.92965,0.0003962,0.0003962,0.0003962
83,1376.02,0.47079,0.46955,0.86087,0.99879,0.97872,0.97507,0.90904,0.50732,0.44106,0.91512,0.0003764,0.0003764,0.0003764
84,1392.31,0.4745,0.45542,0.84629,0.99879,0.97872,0.97507,0.92615,0.49742,0.45247,0.9043,0.0003566,0.0003566,0.0003566
85,1408.71,0.49559,0.46153,0.88865,0.99879,0.97872,0.97507,0.91666,0.48863,0.45425,0.8999,0.0003368,0.0003368,0.0003368
86,1426.04,0.456,0.45025,0.84546,0.99879,0.97872,0.97507,0.9125,0.47711,0.45384,0.89409,0.000317,0.000317,0.000317
87,1446.38,0.49383,0.47862,0.89165,0.9988,0.97872,0.97507,0.91593,0.46283,0.44674,0.88744,0.0002972,0.0002972,0.0002972
88,1466.22,0.44404,0.44401,0.87019,0.9988,0.97872,0.97507,0.91409,0.46104,0.44208,0.88486,0.0002774,0.0002774,0.0002774
89,1483.27,0.46838,0.44705,0.87652,0.99879,0.97872,0.97507,0.91786,0.45794,0.43956,0.88153,0.0002576,0.0002576,0.0002576
90,1499.55,0.47186,0.45836,0.88991,0.99877,0.97872,0.97507,0.91223,0.43885,0.43136,0.87476,0.0002378,0.0002378,0.0002378
91,1515.78,0.41417,0.49508,0.85674,0.99878,0.97872,0.97506,0.91813,0.39452,0.42742,0.86201,0.000218,0.000218,0.000218
92,1531.92,0.37769,0.462,0.83662,0.99877,0.97872,0.97506,0.91767,0.38334,0.43829,0.85263,0.0001982,0.0001982,0.0001982
93,1548.32,0.3924,0.45598,0.82236,0.99877,0.97872,0.97506,0.9216,0.37609,0.43095,0.84625,0.0001784,0.0001784,0.0001784
94,1564.44,0.39674,0.46733,0.83448,0.99875,0.97872,0.97506,0.93113,0.38405,0.42572,0.84928,0.0001586,0.0001586,0.0001586
95,1580.61,0.38629,0.47264,0.87183,0.99876,0.97872,0.97506,0.92702,0.38576,0.43328,0.85016,0.0001388,0.0001388,0.0001388
96,1596.73,0.36293,0.45807,0.83221,0.99876,0.97872,0.97506,0.93093,0.38964,0.44193,0.85438,0.000119,0.000119,0.000119
97,1612.83,0.36518,0.46312,0.85978,0.99875,0.97872,0.97506,0.93213,0.38821,0.44448,0.85668,9.92e-05,9.92e-05,9.92e-05
98,1628.96,0.37402,0.4537,0.8557,0.99877,0.97872,0.97506,0.93936,0.38717,0.44483,0.85828,7.94e-05,7.94e-05,7.94e-05
99,1645.2,0.38499,0.46885,0.83431,0.99875,0.97872,0.97506,0.93932,0.37754,0.43566,0.855,5.96e-05,5.96e-05,5.96e-05
100,1661.36,0.3862,0.45546,0.86118,0.99876,0.97872,0.97506,0.93925,0.37097,0.43227,0.85101,3.98e-05,3.98e-05,3.98e-05

1 epoch time train/box_loss train/cls_loss train/dfl_loss metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B) val/box_loss val/cls_loss val/dfl_loss lr/pg0 lr/pg1 lr/pg2
4 3 50.8526 0.84409 2.14524 0.93347 0.01141 0.97872 0.95462 0.65143 0.72545 2.96458 0.86384 0.000509704 0.000509704 0.000509704
5 4 68.8891 0.92823 1.93303 0.99896 1 0.17404 0.8576 0.66888 0.93772 3.1365 0.99018 0.00067921 0.00067921 0.00067921
6 5 88.2008 0.86695 1.72383 0.99086 1 0.14981 0.89164 0.65259 0.85707 3.08949 0.94664 0.000845152 0.000845152 0.000845152
7 6 108.889 0.9233 1.64537 0.99611 0.00313 0.97872 0.22074 0.15359 1.19903 3.67627 1.40338 0.00100753 0.00100753 0.00100753
8 7 126.63 0.92474 1.74874 1.01005 1 0.22478 0.9398 0.74549 0.6995 3.02254 1.07775 0.00116634 0.00116634 0.00116634
9 8 143.386 0.89439 1.541 1.01516 0.96934 0.67287 0.93016 0.70384 0.84448 2.79319 1.07622 0.00132159 0.00132159 0.00132159
10 9 160.154 1.01923 1.37768 1.04767 0.95661 0.42553 0.84458 0.65549 1.14153 3.14578 1.50441 0.00147328 0.00147328 0.00147328
11 10 176.531 0.85462 1.4615 1.00649 0.82488 0.401 0.59884 0.42863 0.95452 3.05086 1.07771 0.0016214 0.0016214 0.0016214
12 11 193.027 0.88501 1.53296 0.99892 0.91788 0.95141 0.96457 0.73447 1.01148 1.98069 1.07153 0.00176596 0.00176596 0.00176596
13 12 209.352 0.936 1.39373 1.03826 0.86628 0.82979 0.90199 0.67733 1.08629 1.81286 1.03771 0.0017822 0.0017822 0.0017822
14 13 225.621 0.95074 1.5498 1.01222 0.94283 0.61702 0.78999 0.61324 0.93039 2.10289 0.96341 0.0017624 0.0017624 0.0017624
15 14 241.911 0.87627 1.35058 0.98415 0.82171 0.82979 0.89473 0.66946 0.96415 1.78842 0.98676 0.0017426 0.0017426 0.0017426
16 15 258.455 0.89969 1.26147 0.99252 0.88159 0.85106 0.92253 0.6623 1.0348 1.97623 1.03837 0.0017228 0.0017228 0.0017228
17 16 274.784 0.9107 1.19701 1.04842 0.81433 0.87234 0.91067 0.64013 1.07749 2.33723 1.13321 0.001703 0.001703 0.001703
18 17 291.033 0.8797 1.19339 1.01255 0.90187 0.93617 0.95235 0.72838 1.0545 1.88516 1.22758 0.0016832 0.0016832 0.0016832
19 18 307.447 0.86492 1.23953 1.00577 0.9374 0.95587 0.93494 0.6668 0.94737 1.63386 0.95875 0.0016634 0.0016634 0.0016634
20 19 323.927 0.81989 1.14224 0.9353 0.97176 0.97872 0.96568 0.74768 0.79084 2.04213 0.91647 0.0016436 0.0016436 0.0016436
21 20 340.644 0.82661 1.05057 1.01933 0.86772 0.97701 0.89158 0.69948 0.80194 2.04703 0.98656 0.0016238 0.0016238 0.0016238
22 21 356.877 0.82623 1.07653 0.95122 0.91797 0.97872 0.93621 0.74577 0.87056 1.6536 1.23575 0.001604 0.001604 0.001604
23 22 373.893 0.93091 1.1046 1.00084 0.99713 0.97872 0.97504 0.81712 0.88174 1.24998 1.43402 0.0015842 0.0015842 0.0015842
24 23 390.374 0.79185 0.97892 0.98414 1 0.9766 0.97504 0.83856 0.85541 1.15924 1.39651 0.0015644 0.0015644 0.0015644
25 24 406.837 0.77858 0.96501 0.9412 1 0.97516 0.97504 0.82906 0.8962 1.0739 1.39967 0.0015446 0.0015446 0.0015446
26 25 423.408 0.69471 0.8921 0.92449 0.97863 0.97449 0.97462 0.80796 0.8924 1.12536 1.39023 0.0015248 0.0015248 0.0015248
27 26 439.924 0.79448 0.94583 1.01777 0.94546 0.97872 0.97254 0.83029 0.85951 1.08172 1.27858 0.001505 0.001505 0.001505
28 27 456.303 0.75574 0.89269 0.95814 0.99662 0.97872 0.97504 0.8358 0.64848 1.03876 1.01015 0.0014852 0.0014852 0.0014852
29 28 472.56 0.71507 0.83409 0.94143 0.99683 0.97872 0.97504 0.87181 0.57235 0.98598 0.99489 0.0014654 0.0014654 0.0014654
30 29 489.005 0.78166 0.86555 0.98982 0.97822 0.97872 0.97504 0.83676 0.78144 1.05176 1.13006 0.0014456 0.0014456 0.0014456
31 30 505.365 0.74249 0.86108 0.95286 0.9974 0.97872 0.97504 0.84753 0.83641 1.0551 1.25554 0.0014258 0.0014258 0.0014258
32 31 521.68 0.70916 0.87682 0.97448 0.9963 0.95745 0.97421 0.82212 0.93208 0.98694 1.32275 0.001406 0.001406 0.001406
33 32 538.031 0.77631 0.87153 0.97965 0.97698 0.97872 0.97462 0.81106 0.89517 0.93599 1.31376 0.0013862 0.0013862 0.0013862
34 33 554.543 0.74973 0.83324 0.96358 0.99792 0.97872 0.97504 0.84652 0.77113 0.83692 1.18537 0.0013664 0.0013664 0.0013664
35 34 570.984 0.80141 0.80779 0.97662 0.99646 0.97872 0.97504 0.84518 0.76637 0.95064 1.21416 0.0013466 0.0013466 0.0013466
36 35 587.277 0.85547 0.88575 1.08871 0.99951 0.97872 0.97504 0.83551 0.76647 1.01295 1.15899 0.0013268 0.0013268 0.0013268
37 36 604.325 0.767 0.7671 0.95181 1 0.97769 0.97504 0.85141 0.67728 0.95316 1.06362 0.001307 0.001307 0.001307
38 37 621.429 0.71542 0.79484 0.98779 0.9981 0.95745 0.97421 0.84222 0.73423 0.93986 1.13184 0.0012872 0.0012872 0.0012872
39 38 637.85 0.76685 0.74774 0.94989 0.99776 0.95745 0.97274 0.80365 0.81724 0.92326 1.21423 0.0012674 0.0012674 0.0012674
40 39 654.193 0.71727 0.77154 0.93576 1 0.97778 0.97504 0.81219 0.79632 0.79607 1.241 0.0012476 0.0012476 0.0012476
41 40 670.47 0.73679 0.76367 0.96723 0.9987 0.97872 0.97505 0.82224 0.66771 0.84454 1.02726 0.0012278 0.0012278 0.0012278
42 41 687.289 0.69753 0.70766 0.93616 0.99866 0.97872 0.97505 0.84836 0.58592 0.78201 0.95605 0.001208 0.001208 0.001208
43 42 703.805 0.69078 0.75505 0.94243 0.99862 0.97872 0.97505 0.86063 0.55282 0.76261 0.93304 0.0011882 0.0011882 0.0011882
44 43 720.098 0.69355 0.6699 0.94703 0.99818 0.97872 0.97505 0.87101 0.53047 0.81548 0.94703 0.0011684 0.0011684 0.0011684
45 44 736.487 0.61083 0.66366 0.89841 0.99775 0.97872 0.97505 0.86761 0.51186 0.74653 0.95031 0.0011486 0.0011486 0.0011486
46 45 752.747 0.70031 0.70279 0.98732 0.99804 0.97872 0.97505 0.8701 0.50757 0.70518 0.94971 0.0011288 0.0011288 0.0011288
47 46 769.296 0.62004 0.65034 0.90191 0.99812 0.97872 0.97505 0.8481 0.49729 0.65358 0.95067 0.001109 0.001109 0.001109
48 47 785.564 0.69383 0.66827 0.93709 0.99739 0.97872 0.97505 0.87732 0.48397 0.63065 0.94863 0.0010892 0.0010892 0.0010892
49 48 801.985 0.59658 0.59829 0.90597 0.99596 0.97872 0.97505 0.85898 0.51329 0.64556 0.93802 0.0010694 0.0010694 0.0010694
50 49 818.235 0.62114 0.61166 0.90013 0.99836 0.97872 0.97505 0.87547 0.51048 0.70061 0.93659 0.0010496 0.0010496 0.0010496
51 50 834.536 0.62591 0.62487 0.9242 0.9987 0.97872 0.97505 0.86005 0.52268 0.71765 0.93612 0.0010298 0.0010298 0.0010298
52 51 850.84 0.60417 0.59436 0.89844 0.99859 0.97872 0.97505 0.88784 0.50296 0.68031 0.9205 0.00101 0.00101 0.00101
53 52 867.235 0.67345 0.68685 0.95226 0.99746 0.97872 0.97505 0.87982 0.48112 0.64511 0.9015 0.0009902 0.0009902 0.0009902
54 53 883.477 0.65875 0.63211 0.89805 0.99761 0.97872 0.97505 0.8855 0.44319 0.64272 0.88555 0.0009704 0.0009704 0.0009704
55 54 899.777 0.61886 0.64051 0.92091 0.99779 0.97872 0.97505 0.89959 0.39967 0.62697 0.87383 0.0009506 0.0009506 0.0009506
56 55 916.129 0.58662 0.57316 0.8766 0.99787 0.97872 0.97505 0.90367 0.40999 0.58972 0.87969 0.0009308 0.0009308 0.0009308
57 56 932.473 0.56885 0.55402 0.86806 0.99816 0.97872 0.97505 0.88802 0.43791 0.56277 0.88202 0.000911 0.000911 0.000911
58 57 948.702 0.61308 0.631 0.94614 0.99754 0.97872 0.97505 0.86903 0.51987 0.59688 0.89673 0.0008912 0.0008912 0.0008912
59 58 965.014 0.62221 0.62787 0.93053 0.99653 0.97872 0.97505 0.86344 0.53093 0.6724 0.92493 0.0008714 0.0008714 0.0008714
60 59 981.468 0.59869 0.61537 0.91599 0.99832 0.97872 0.97505 0.88686 0.53637 0.6404 0.94102 0.0008516 0.0008516 0.0008516
61 60 997.948 0.67699 0.64553 0.93616 0.99839 0.97872 0.97505 0.89016 0.53426 0.60405 0.93235 0.0008318 0.0008318 0.0008318
62 61 1014.54 0.54223 0.54748 0.86316 0.99856 0.97872 0.97506 0.9013 0.54016 0.60719 0.93491 0.000812 0.000812 0.000812
63 62 1030.81 0.57035 0.56477 0.90542 0.99863 0.97872 0.97506 0.87968 0.51468 0.61519 0.90362 0.0007922 0.0007922 0.0007922
64 63 1047.14 0.56914 0.5558 0.91865 0.99866 0.97872 0.97506 0.88691 0.51397 0.54698 0.90837 0.0007724 0.0007724 0.0007724
65 64 1063.47 0.55618 0.54987 0.88579 0.99865 0.97872 0.97506 0.90335 0.49993 0.51709 0.89065 0.0007526 0.0007526 0.0007526
66 65 1079.7 0.53892 0.53695 0.90014 0.99861 0.97872 0.97506 0.90518 0.53615 0.51287 0.90089 0.0007328 0.0007328 0.0007328
67 66 1096.03 0.52733 0.51237 0.87921 0.99753 0.97872 0.97506 0.89833 0.54082 0.5022 0.90117 0.000713 0.000713 0.000713
68 67 1112.36 0.51289 0.51338 0.8675 0.99761 0.97872 0.97507 0.91082 0.4392 0.50289 0.87438 0.0006932 0.0006932 0.0006932
69 68 1129.26 0.51701 0.50177 0.90627 0.99755 0.97872 0.97507 0.90628 0.43663 0.50467 0.87736 0.0006734 0.0006734 0.0006734
70 69 1145.59 0.55644 0.53077 0.89669 0.99734 0.97872 0.97507 0.9091 0.44588 0.54371 0.88767 0.0006536 0.0006536 0.0006536
71 70 1162.7 0.5669 0.52751 0.90383 0.99726 0.97872 0.97507 0.91448 0.43112 0.53961 0.88243 0.0006338 0.0006338 0.0006338
72 71 1179.38 0.52945 0.53576 0.91008 0.99701 0.97872 0.97507 0.91338 0.40923 0.50713 0.86706 0.000614 0.000614 0.000614
73 72 1195.76 0.5045 0.5 0.83861 0.99672 0.97872 0.97507 0.92336 0.39388 0.45782 0.85291 0.0005942 0.0005942 0.0005942
74 73 1212.84 0.52684 0.5122 0.86863 0.99873 0.97872 0.97507 0.92278 0.40641 0.50211 0.8596 0.0005744 0.0005744 0.0005744
75 74 1229.11 0.55294 0.54271 0.88696 0.99862 0.97872 0.97507 0.90759 0.47393 0.51367 0.88525 0.0005546 0.0005546 0.0005546
76 75 1245.48 0.51732 0.50029 0.85483 0.99845 0.97872 0.97506 0.91187 0.53175 0.48527 0.94813 0.0005348 0.0005348 0.0005348
77 76 1261.78 0.5022 0.51302 0.8886 0.99847 0.97872 0.97506 0.90642 0.53595 0.47371 0.96317 0.000515 0.000515 0.000515
78 77 1277.95 0.50634 0.52206 0.87813 0.99855 0.97872 0.97506 0.91129 0.53131 0.4618 0.96477 0.0004952 0.0004952 0.0004952
79 78 1294.36 0.52087 0.47526 0.84153 0.9986 0.97872 0.97507 0.91053 0.54476 0.44952 0.97 0.0004754 0.0004754 0.0004754
80 79 1310.72 0.50821 0.45477 0.87197 0.99864 0.97872 0.97507 0.90609 0.53997 0.44403 0.96696 0.0004556 0.0004556 0.0004556
81 80 1326.99 0.47979 0.47719 0.84969 0.99869 0.97872 0.97507 0.91254 0.51575 0.4359 0.95256 0.0004358 0.0004358 0.0004358
82 81 1343.24 0.48129 0.44147 0.86231 0.99872 0.97872 0.97507 0.91279 0.48954 0.41942 0.93704 0.000416 0.000416 0.000416
83 82 1359.76 0.49291 0.45548 0.9074 0.99874 0.97872 0.97507 0.90741 0.48763 0.41879 0.92965 0.0003962 0.0003962 0.0003962
84 83 1376.02 0.47079 0.46955 0.86087 0.99879 0.97872 0.97507 0.90904 0.50732 0.44106 0.91512 0.0003764 0.0003764 0.0003764
85 84 1392.31 0.4745 0.45542 0.84629 0.99879 0.97872 0.97507 0.92615 0.49742 0.45247 0.9043 0.0003566 0.0003566 0.0003566
86 85 1408.71 0.49559 0.46153 0.88865 0.99879 0.97872 0.97507 0.91666 0.48863 0.45425 0.8999 0.0003368 0.0003368 0.0003368
87 86 1426.04 0.456 0.45025 0.84546 0.99879 0.97872 0.97507 0.9125 0.47711 0.45384 0.89409 0.000317 0.000317 0.000317
88 87 1446.38 0.49383 0.47862 0.89165 0.9988 0.97872 0.97507 0.91593 0.46283 0.44674 0.88744 0.0002972 0.0002972 0.0002972
89 88 1466.22 0.44404 0.44401 0.87019 0.9988 0.97872 0.97507 0.91409 0.46104 0.44208 0.88486 0.0002774 0.0002774 0.0002774
90 89 1483.27 0.46838 0.44705 0.87652 0.99879 0.97872 0.97507 0.91786 0.45794 0.43956 0.88153 0.0002576 0.0002576 0.0002576
91 90 1499.55 0.47186 0.45836 0.88991 0.99877 0.97872 0.97507 0.91223 0.43885 0.43136 0.87476 0.0002378 0.0002378 0.0002378
92 91 1515.78 0.41417 0.49508 0.85674 0.99878 0.97872 0.97506 0.91813 0.39452 0.42742 0.86201 0.000218 0.000218 0.000218
93 92 1531.92 0.37769 0.462 0.83662 0.99877 0.97872 0.97506 0.91767 0.38334 0.43829 0.85263 0.0001982 0.0001982 0.0001982
94 93 1548.32 0.3924 0.45598 0.82236 0.99877 0.97872 0.97506 0.9216 0.37609 0.43095 0.84625 0.0001784 0.0001784 0.0001784
95 94 1564.44 0.39674 0.46733 0.83448 0.99875 0.97872 0.97506 0.93113 0.38405 0.42572 0.84928 0.0001586 0.0001586 0.0001586
96 95 1580.61 0.38629 0.47264 0.87183 0.99876 0.97872 0.97506 0.92702 0.38576 0.43328 0.85016 0.0001388 0.0001388 0.0001388
97 96 1596.73 0.36293 0.45807 0.83221 0.99876 0.97872 0.97506 0.93093 0.38964 0.44193 0.85438 0.000119 0.000119 0.000119
98 97 1612.83 0.36518 0.46312 0.85978 0.99875 0.97872 0.97506 0.93213 0.38821 0.44448 0.85668 9.92e-05 9.92e-05 9.92e-05
99 98 1628.96 0.37402 0.4537 0.8557 0.99877 0.97872 0.97506 0.93936 0.38717 0.44483 0.85828 7.94e-05 7.94e-05 7.94e-05
100 99 1645.2 0.38499 0.46885 0.83431 0.99875 0.97872 0.97506 0.93932 0.37754 0.43566 0.855 5.96e-05 5.96e-05 5.96e-05
101 100 1661.36 0.3862 0.45546 0.86118 0.99876 0.97872 0.97506 0.93925 0.37097 0.43227 0.85101 3.98e-05 3.98e-05 3.98e-05

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@ -1,3 +1,3 @@
from ultralytics import YOLO from ultralytics import YOLO
model = YOLO(r"C:\workspace\le-yolo\runs\detect\train39\weights\best.pt") model = YOLO(r"C:\workspace\le-yolo\runs\detect\train40\weights\best.pt")
results = model.predict("../res/4.mp4", show=True, save=True) results = model.predict("../res/5.mp4", show=True, save=True)

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@ -1,10 +1,12 @@
from ultralytics import YOLO from ultralytics import YOLO
import time import time
start_time = time.time() start_time = time.time()
model = YOLO("yolov8n.pt") # model = YOLO("yolov8n.pt")
model = YOLO(r"C:\workspace\le-yolo\runs\detect\train40\weights\last.pt")
model.train(data="data.yaml", epochs=100, batch=8, device='cpu', imgsz=640, augment = True) model.train(data="data.yaml", epochs=100, batch=8, device='cpu', imgsz=640, augment = True)
model.val() model.val()
print('训练完成') print('训练完成')
end_time = time.time() end_time = time.time()
run_time = end_time - start_time run_time = end_time - start_time
print('运行时间:', run_time, '') min = run_time // 60
print('运行时间:', min, '分钟')