2023-02-21 10:37:20.122 | INFO | yolox.core.trainer:before_train:126 - args: Namespace(batch_size=8, ckpt='bytetrack_x_mot17.pth.tar', devices=2, dist_backend='nccl', dist_url=None, exp_file='exps/example/mot/yolox_x_mot17_half.py', experiment_name='yolox_x_mot17_half', fp16=True, local_rank=0, machine_rank=0, name=None, num_machines=1, occupy=True, opts=[], resume=False, start_epoch=None) 2023-02-21 10:37:20.125 | INFO | yolox.core.trainer:before_train:127 - exp value: ╒══════════════════╤══════════════════════╕ │ keys │ values │ ╞══════════════════╪══════════════════════╡ │ seed │ None │ ├──────────────────┼──────────────────────┤ │ output_dir │ './YOLOX_outputs' │ ├──────────────────┼──────────────────────┤ │ print_interval │ 20 │ ├──────────────────┼──────────────────────┤ │ eval_interval │ 5 │ ├──────────────────┼──────────────────────┤ │ num_classes │ 1 │ ├──────────────────┼──────────────────────┤ │ depth │ 1.33 │ ├──────────────────┼──────────────────────┤ │ width │ 1.25 │ ├──────────────────┼──────────────────────┤ │ data_num_workers │ 4 │ ├──────────────────┼──────────────────────┤ │ input_size │ (800, 1440) │ ├──────────────────┼──────────────────────┤ │ random_size │ (18, 32) │ ├──────────────────┼──────────────────────┤ │ train_ann │ 'train.json' │ ├──────────────────┼──────────────────────┤ │ val_ann │ 'val_half.json' │ ├──────────────────┼──────────────────────┤ │ degrees │ 10.0 │ ├──────────────────┼──────────────────────┤ │ translate │ 0.1 │ ├──────────────────┼──────────────────────┤ │ scale │ (0.1, 2) │ ├──────────────────┼──────────────────────┤ │ mscale │ (0.8, 1.6) │ ├──────────────────┼──────────────────────┤ │ shear │ 2.0 │ ├──────────────────┼──────────────────────┤ │ perspective │ 0.0 │ ├──────────────────┼──────────────────────┤ │ enable_mixup │ True │ ├──────────────────┼──────────────────────┤ │ warmup_epochs │ 1 │ ├──────────────────┼──────────────────────┤ │ max_epoch │ 80 │ ├──────────────────┼──────────────────────┤ │ warmup_lr │ 0 │ ├──────────────────┼──────────────────────┤ │ basic_lr_per_img │ 1.5625e-05 │ ├──────────────────┼──────────────────────┤ │ scheduler │ 'yoloxwarmcos' │ ├──────────────────┼──────────────────────┤ │ no_aug_epochs │ 10 │ ├──────────────────┼──────────────────────┤ │ min_lr_ratio │ 0.05 │ ├──────────────────┼──────────────────────┤ │ ema │ True │ ├──────────────────┼──────────────────────┤ │ weight_decay │ 0.0005 │ ├──────────────────┼──────────────────────┤ │ momentum │ 0.9 │ ├──────────────────┼──────────────────────┤ │ exp_name │ 'yolox_x_mot17_half' │ ├──────────────────┼──────────────────────┤ │ test_size │ (800, 1440) │ ├──────────────────┼──────────────────────┤ │ test_conf │ 0.1 │ ├──────────────────┼──────────────────────┤ │ nmsthre │ 0.7 │ ╘══════════════════╧══════════════════════╛ 2023-02-21 10:37:21.199 | INFO | yolox.core.trainer:before_train:132 - Model Summary: Params: 99.00M, Gflops: 793.21 2023-02-21 10:37:21.295 | INFO | yolox.core.trainer:resume_train:291 - loading checkpoint for fine tuning 2023-02-21 10:37:22.144 | INFO | yolox.data.datasets.mot:__init__:39 - loading annotations into memory... 2023-02-21 10:37:22.600 | INFO | yolox.data.datasets.mot:__init__:39 - Done (t=0.46s) 2023-02-21 10:37:22.601 | INFO | pycocotools.coco:__init__:88 - creating index... 2023-02-21 10:37:22.668 | INFO | pycocotools.coco:__init__:88 - index created! 2023-02-21 10:37:23.296 | INFO | yolox.core.trainer:before_train:150 - init prefetcher, this might take one minute or less... 2023-02-21 10:37:31.821 | INFO | yolox.data.datasets.mot:__init__:39 - loading annotations into memory... 2023-02-21 10:37:32.221 | INFO | yolox.data.datasets.mot:__init__:39 - Done (t=0.40s) 2023-02-21 10:37:32.222 | INFO | pycocotools.coco:__init__:88 - creating index... 2023-02-21 10:37:32.254 | INFO | pycocotools.coco:__init__:88 - index created! 2023-02-21 10:37:32.434 | INFO | yolox.core.trainer:before_train:178 - Training start... 2023-02-21 10:37:32.435 | INFO | yolox.core.trainer:before_epoch:189 - ---> start train epoch1 2023-02-21 10:37:52.030 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 20/665, mem: 43899Mb, iter_time: 0.979s, data_time: 0.004s, total_loss: 2.534, iou_loss: 1.463, l1_loss: 0.000, conf_loss: 0.641, cls_loss: 0.430, lr: 1.131e-07, size: 640, ETA: 14:27:28 2023-02-21 10:38:10.942 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 40/665, mem: 43899Mb, iter_time: 0.944s, data_time: 0.002s, total_loss: 2.825, iou_loss: 1.517, l1_loss: 0.000, conf_loss: 0.861, cls_loss: 0.446, lr: 4.523e-07, size: 1024, ETA: 14:11:58 2023-02-21 10:38:27.519 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 60/665, mem: 43899Mb, iter_time: 0.826s, data_time: 0.005s, total_loss: 2.301, iou_loss: 1.365, l1_loss: 0.000, conf_loss: 0.532, cls_loss: 0.404, lr: 1.018e-06, size: 800, ETA: 13:31:44 2023-02-21 10:38:42.803 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 80/665, mem: 43899Mb, iter_time: 0.763s, data_time: 0.006s, total_loss: 2.974, iou_loss: 1.728, l1_loss: 0.000, conf_loss: 0.765, cls_loss: 0.481, lr: 1.809e-06, size: 608, ETA: 12:57:28 2023-02-21 10:38:54.736 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 100/665, mem: 43899Mb, iter_time: 0.595s, data_time: 0.009s, total_loss: 2.284, iou_loss: 1.330, l1_loss: 0.000, conf_loss: 0.553, cls_loss: 0.401, lr: 2.827e-06, size: 864, ETA: 12:06:59 2023-02-21 10:39:08.625 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 120/665, mem: 43899Mb, iter_time: 0.692s, data_time: 0.004s, total_loss: 2.511, iou_loss: 1.484, l1_loss: 0.000, conf_loss: 0.593, cls_loss: 0.434, lr: 4.070e-06, size: 608, ETA: 11:47:40 2023-02-21 10:39:20.548 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 140/665, mem: 43899Mb, iter_time: 0.593s, data_time: 0.006s, total_loss: 2.706, iou_loss: 1.555, l1_loss: 0.000, conf_loss: 0.713, cls_loss: 0.438, lr: 5.540e-06, size: 672, ETA: 11:21:16 2023-02-21 10:39:36.477 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 160/665, mem: 43899Mb, iter_time: 0.794s, data_time: 0.010s, total_loss: 2.583, iou_loss: 1.468, l1_loss: 0.000, conf_loss: 0.687, cls_loss: 0.429, lr: 7.236e-06, size: 800, ETA: 11:23:36 2023-02-21 10:39:46.081 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 180/665, mem: 43899Mb, iter_time: 0.479s, data_time: 0.015s, total_loss: 2.777, iou_loss: 1.519, l1_loss: 0.000, conf_loss: 0.820, cls_loss: 0.437, lr: 9.158e-06, size: 672, ETA: 10:54:27 2023-02-21 10:39:55.607 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 200/665, mem: 43899Mb, iter_time: 0.474s, data_time: 0.012s, total_loss: 2.464, iou_loss: 1.426, l1_loss: 0.000, conf_loss: 0.620, cls_loss: 0.418, lr: 1.131e-05, size: 640, ETA: 10:30:42 2023-02-21 10:40:06.839 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 220/665, mem: 43899Mb, iter_time: 0.560s, data_time: 0.008s, total_loss: 2.679, iou_loss: 1.427, l1_loss: 0.000, conf_loss: 0.836, cls_loss: 0.416, lr: 1.368e-05, size: 896, ETA: 10:18:05 2023-02-21 10:40:24.250 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 240/665, mem: 43899Mb, iter_time: 0.869s, data_time: 0.012s, total_loss: 2.520, iou_loss: 1.436, l1_loss: 0.000, conf_loss: 0.665, cls_loss: 0.418, lr: 1.628e-05, size: 832, ETA: 10:30:16 2023-02-21 10:40:33.622 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 260/665, mem: 43899Mb, iter_time: 0.467s, data_time: 0.009s, total_loss: 2.392, iou_loss: 1.355, l1_loss: 0.000, conf_loss: 0.631, cls_loss: 0.405, lr: 1.911e-05, size: 832, ETA: 10:13:18 2023-02-21 10:40:50.565 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 280/665, mem: 43899Mb, iter_time: 0.844s, data_time: 0.004s, total_loss: 2.304, iou_loss: 1.353, l1_loss: 0.000, conf_loss: 0.541, cls_loss: 0.409, lr: 2.216e-05, size: 960, ETA: 10:22:28 2023-02-21 10:41:06.419 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 300/665, mem: 43899Mb, iter_time: 0.792s, data_time: 0.009s, total_loss: 2.742, iou_loss: 1.660, l1_loss: 0.000, conf_loss: 0.619, cls_loss: 0.464, lr: 2.544e-05, size: 768, ETA: 10:27:16 2023-02-21 10:41:16.950 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 320/665, mem: 43899Mb, iter_time: 0.525s, data_time: 0.015s, total_loss: 2.063, iou_loss: 1.288, l1_loss: 0.000, conf_loss: 0.376, cls_loss: 0.399, lr: 2.894e-05, size: 864, ETA: 10:16:47 2023-02-21 10:41:26.358 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 340/665, mem: 43899Mb, iter_time: 0.467s, data_time: 0.009s, total_loss: 2.526, iou_loss: 1.505, l1_loss: 0.000, conf_loss: 0.584, cls_loss: 0.438, lr: 3.268e-05, size: 640, ETA: 10:04:30 2023-02-21 10:41:42.196 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 360/665, mem: 43899Mb, iter_time: 0.789s, data_time: 0.003s, total_loss: 2.435, iou_loss: 1.465, l1_loss: 0.000, conf_loss: 0.548, cls_loss: 0.421, lr: 3.663e-05, size: 576, ETA: 10:09:19 2023-02-21 10:41:50.621 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 380/665, mem: 43899Mb, iter_time: 0.420s, data_time: 0.008s, total_loss: 2.071, iou_loss: 1.224, l1_loss: 0.000, conf_loss: 0.469, cls_loss: 0.378, lr: 4.082e-05, size: 960, ETA: 9:56:28 2023-02-21 10:42:01.798 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 400/665, mem: 43899Mb, iter_time: 0.555s, data_time: 0.007s, total_loss: 3.230, iou_loss: 1.536, l1_loss: 0.000, conf_loss: 1.256, cls_loss: 0.438, lr: 4.523e-05, size: 992, ETA: 9:50:51 2023-02-21 10:42:16.863 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 420/665, mem: 43899Mb, iter_time: 0.752s, data_time: 0.018s, total_loss: 2.939, iou_loss: 1.678, l1_loss: 0.000, conf_loss: 0.789, cls_loss: 0.472, lr: 4.986e-05, size: 960, ETA: 9:53:59 2023-02-21 10:42:26.939 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 440/665, mem: 43899Mb, iter_time: 0.502s, data_time: 0.007s, total_loss: 2.639, iou_loss: 1.511, l1_loss: 0.000, conf_loss: 0.693, cls_loss: 0.435, lr: 5.472e-05, size: 992, ETA: 9:46:50 2023-02-21 10:42:39.208 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 460/665, mem: 43899Mb, iter_time: 0.612s, data_time: 0.030s, total_loss: 2.254, iou_loss: 1.353, l1_loss: 0.000, conf_loss: 0.496, cls_loss: 0.405, lr: 5.981e-05, size: 960, ETA: 9:44:30 2023-02-21 10:42:49.741 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 480/665, mem: 43899Mb, iter_time: 0.524s, data_time: 0.006s, total_loss: 2.647, iou_loss: 1.607, l1_loss: 0.000, conf_loss: 0.586, cls_loss: 0.454, lr: 6.513e-05, size: 576, ETA: 9:39:08 2023-02-21 10:42:57.514 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 500/665, mem: 43899Mb, iter_time: 0.370s, data_time: 0.019s, total_loss: 2.603, iou_loss: 1.595, l1_loss: 0.000, conf_loss: 0.557, cls_loss: 0.451, lr: 7.067e-05, size: 576, ETA: 9:28:46 2023-02-21 10:43:05.304 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 520/665, mem: 43899Mb, iter_time: 0.387s, data_time: 0.008s, total_loss: 2.234, iou_loss: 1.333, l1_loss: 0.000, conf_loss: 0.500, cls_loss: 0.400, lr: 7.643e-05, size: 672, ETA: 9:19:45 2023-02-21 10:43:13.573 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 540/665, mem: 43899Mb, iter_time: 0.412s, data_time: 0.007s, total_loss: 2.253, iou_loss: 1.383, l1_loss: 0.000, conf_loss: 0.456, cls_loss: 0.415, lr: 8.242e-05, size: 896, ETA: 9:12:11 2023-02-21 10:43:24.586 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 560/665, mem: 43899Mb, iter_time: 0.547s, data_time: 0.015s, total_loss: 2.652, iou_loss: 1.466, l1_loss: 0.000, conf_loss: 0.757, cls_loss: 0.430, lr: 8.864e-05, size: 832, ETA: 9:09:23 2023-02-21 10:43:34.975 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 580/665, mem: 43899Mb, iter_time: 0.516s, data_time: 0.004s, total_loss: 2.050, iou_loss: 1.234, l1_loss: 0.000, conf_loss: 0.434, cls_loss: 0.383, lr: 9.509e-05, size: 704, ETA: 9:05:50 2023-02-21 10:43:44.724 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 600/665, mem: 43899Mb, iter_time: 0.483s, data_time: 0.009s, total_loss: 2.739, iou_loss: 1.609, l1_loss: 0.000, conf_loss: 0.680, cls_loss: 0.450, lr: 1.018e-04, size: 832, ETA: 9:01:33 2023-02-21 10:43:56.520 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 620/665, mem: 43899Mb, iter_time: 0.587s, data_time: 0.008s, total_loss: 2.248, iou_loss: 1.297, l1_loss: 0.000, conf_loss: 0.545, cls_loss: 0.406, lr: 1.087e-04, size: 992, ETA: 9:00:28 2023-02-21 10:44:07.420 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 640/665, mem: 43899Mb, iter_time: 0.544s, data_time: 0.002s, total_loss: 2.452, iou_loss: 1.433, l1_loss: 0.000, conf_loss: 0.595, cls_loss: 0.424, lr: 1.158e-04, size: 928, ETA: 8:58:16 2023-02-21 10:44:19.377 | INFO | yolox.core.trainer:after_iter:244 - epoch: 1/80, iter: 660/665, mem: 43899Mb, iter_time: 0.595s, data_time: 0.007s, total_loss: 2.413, iou_loss: 1.436, l1_loss: 0.000, conf_loss: 0.553, cls_loss: 0.423, lr: 1.231e-04, size: 672, ETA: 8:57:33 2023-02-21 10:44:21.490 | INFO | yolox.core.trainer:save_ckpt:318 - Save weights to ./YOLOX_outputs/yolox_x_mot17_half 2023-02-21 10:44:23.125 | INFO | yolox.core.trainer:before_epoch:189 - ---> start train epoch2 2023-02-21 10:44:33.345 | INFO | yolox.core.trainer:after_iter:244 - epoch: 2/80, iter: 20/665, mem: 43899Mb, iter_time: 0.510s, data_time: 0.011s, total_loss: 2.354, iou_loss: 1.412, l1_loss: 0.000, conf_loss: 0.527, cls_loss: 0.416, lr: 1.250e-04, size: 800, ETA: 8:53:20 2023-02-21 10:44:38.270 | INFO | yolox.core.trainer:after_train:182 - Training of experiment is done and the best AP is 0.00