基于 ResNet 网络对100种体育项目识别【包含数据集、完整代码、训练的结果、混淆矩阵等等】

[train hyper-parameters: Namespace(batch_size=32, epochs=50, lr=0.001, lrf=0.01, num_classes=100)] [train mean: [0.471 0.47 0.455],train std:[0.293 0.285 0.299]] [epoch: 1] train loss:0.1382 train accuracy:0.0594 train loss:0.1382 test accuracy:0.0620 [epoch: 2] train loss:0.1233 train accuracy:0.1271 train loss:0.1233 test accuracy:0.1200 [epoch: 3] train loss:0.1127 train accuracy:0.1656 train loss:0.1127 test accuracy:0.1580 [epoch: 4] train loss:0.1061 train accuracy:0.1894 train loss:0.1061 test accuracy:0.1960 [epoch: 5] train loss:0.1015 train accuracy:0.2267 train loss:0.1015 test accuracy:0.2120 [epoch: 6] train loss:0.0966 train accuracy:0.2389 train loss:0.0966 test accuracy:0.2240 [epoch: 7] train loss:0.0931 train accuracy:0.2776 train loss:0.0931 test accuracy:0.2720 [epoch: 8] train loss:0.0895 train accuracy:0.2928 train loss:0.0895 test accuracy:0.2880 [epoch: 9] train loss:0.0860 train accuracy:0.3143 train loss:0.0860 test accuracy:0.3100 [epoch: 10] train loss:0.0827 train accuracy:0.3469 train loss:0.0827 test accuracy:0.3320 [epoch: 11] train loss:0.0803 train accuracy:0.3398 train loss:0.0803 test accuracy:0.3460 [epoch: 12] train loss:0.0775 train accuracy:0.3801 train loss:0.0775 test accuracy:0.3940 [epoch: 13] train loss:0.0753 train accuracy:0.3969 train loss:0.0753 test accuracy:0.4100 [epoch: 14] train loss:0.0726 train accuracy:0.3712 train loss:0.0726 test accuracy:0.3700 [epoch: 15] train loss:0.0702 train accuracy:0.4272 train loss:0.0702 test accuracy:0.4140 [epoch: 16] train loss:0.0682 train accuracy:0.4340 train loss:0.0682 test accuracy:0.4000 [epoch: 17] train loss:0.0662 train accuracy:0.4727 train loss:0.0662 test accuracy:0.4420 [epoch: 18] train loss:0.0638 train accuracy:0.4764 train loss:0.0638 test accuracy:0.4380 [epoch: 19] train loss:0.0627 train accuracy:0.5073 train loss:0.0627 test accuracy:0.4820 [epoch: 20] train loss:0.0605 train accuracy:0.5291 train loss:0.0605 test accuracy:0.5020 [epoch: 21] train loss:0.0589 train accuracy:0.5208 train loss:0.0589 test accuracy:0.4880 [epoch: 22] train loss:0.0573 train accuracy:0.5224 train loss:0.0573 test accuracy:0.4900 [epoch: 23] train loss:0.0553 train accuracy:0.5350 train loss:0.0553 test accuracy:0.5000 [epoch: 24] train loss:0.0539 train accuracy:0.5727 train loss:0.0539 test accuracy:0.5280 [epoch: 25] train loss:0.0525 train accuracy:0.5726 train loss:0.0525 test accuracy:0.4960 [epoch: 26] train loss:0.0510 train accuracy:0.5881 train loss:0.0510 test accuracy:0.5460 [epoch: 27] train loss:0.0499 train accuracy:0.6095 train loss:0.0499 test accuracy:0.5500 [epoch: 28] train loss:0.0485 train accuracy:0.6270 train loss:0.0485 test accuracy:0.5660 [epoch: 29] train loss:0.0477 train accuracy:0.6321 train loss:0.0477 test accuracy:0.5560 [epoch: 30] train loss:0.0462 train accuracy:0.6408 train loss:0.0462 test accuracy:0.5440 [epoch: 31] train loss:0.0454 train accuracy:0.6555 train loss:0.0454 test accuracy:0.5540 [epoch: 32] train loss:0.0442 train accuracy:0.6523 train loss:0.0442 test accuracy:0.5600 [epoch: 33] train loss:0.0430 train accuracy:0.6709 train loss:0.0430 test accuracy:0.5560 [epoch: 34] train loss:0.0422 train accuracy:0.6799 train loss:0.0422 test accuracy:0.5900 [epoch: 35] train loss:0.0417 train accuracy:0.6927 train loss:0.0417 test accuracy:0.5740 [epoch: 36] train loss:0.0403 train accuracy:0.7013 train loss:0.0403 test accuracy:0.5740 [epoch: 37] train loss:0.0396 train accuracy:0.7103 train loss:0.0396 test accuracy:0.5920 [epoch: 38] train loss:0.0393 train accuracy:0.7096 train loss:0.0393 test accuracy:0.5900 [epoch: 39] train loss:0.0387 train accuracy:0.7120 train loss:0.0387 test accuracy:0.5880 [epoch: 40] train loss:0.0381 train accuracy:0.7185 train loss:0.0381 test accuracy:0.5840 [epoch: 41] train loss:0.0375 train accuracy:0.7289 train loss:0.0375 test accuracy:0.6060 [epoch: 42] train loss:0.0370 train accuracy:0.7287 train loss:0.0370 test accuracy:0.5940 [epoch: 43] train loss:0.0364 train accuracy:0.7387 train loss:0.0364 test accuracy:0.5900 [epoch: 44] train loss:0.0362 train accuracy:0.7376 train loss:0.0362 test accuracy:0.5940 [epoch: 45] train loss:0.0359 train accuracy:0.7401 train loss:0.0359 test accuracy:0.6080 [epoch: 46] train loss:0.0356 train accuracy:0.7417 train loss:0.0356 test accuracy:0.6080 [epoch: 47] train loss:0.0355 train accuracy:0.7441 train loss:0.0355 test accuracy:0.5920 [epoch: 48] train loss:0.0356 train accuracy:0.7428 train loss:0.0356 test accuracy:0.5940 [epoch: 49] train loss:0.0352 train accuracy:0.7489 train loss:0.0352 test accuracy:0.6000 [epoch: 50] train loss:0.0351 train accuracy:0.7433 train loss:0.0351 test accuracy:0.6040