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PaddleDetection

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PaddleDetection
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Opened by saxon_zh@saxon_zhGuest

mAP怪怪的

Created by: Stillremains

我在训练的时候一切都挺正常的，loss也在下降，唯独这个mAP很奇怪啊，0.00 0.01 0.03啥的 反正一直很低 不知道为啥

我的图片大小都是424 * 240的，yml配置的3 * 320 * 320
[Errno 2] No such file or directory: '/home/aistudio/ArtRobot/to/clone/PaddleDetection' /home/aistudio/Robot/to/clone/PaddleDetection /home/aistudio/Robot/to/clone/PaddleDetection DarkNet: [32mnorm_type[0m: sync_bn depth: 53 norm_decay: 0.0 weight_prefix_name: '' EvalReader: batch_size: 8 bufsize: 16 dataset: !VOCDataSet anno_path: val.txt dataset_dir: dataset/voc image_dir: '' label_list: label_list.txt sample_num: -1 use_default_label: false with_background: false drop_empty: false inputs_def: fields: - image - im_size - im_id - gt_bbox - gt_class - is_difficult num_max_boxes: 50 sample_transforms:

  • !DecodeImage to_rgb: true with_mixup: false
  • !ResizeImage interp: 2 max_size: 0 target_size: 608 use_cv2: true
  • !NormalizeImage is_channel_first: false is_scale: true mean:
    • 0.485
    • 0.456
    • 0.406 std:
    • 0.229
    • 0.224
    • 0.225
  • !PadBox num_max_boxes: 50
  • !Permute channel_first: true to_bgr: false worker_num: 8 LearningRate: [32mbase_lr[0m: 5.0e-05 [32mschedulers[0m:
  • !PiecewiseDecay gamma: 0.1 milestones:
    • 15000
    • 18000 values: null
  • !LinearWarmup start_factor: 0.0 steps: 100 OptimizerBuilder: [32mregularizer[0m: factor: 0.0005 type: L2 optimizer: momentum: 0.9 type: Momentum TestReader: batch_size: 1 dataset: !ImageFolder anno_path: dataset/voc/label_list.txt dataset_dir: '' image_dir: '' sample_num: -1 use_default_label: false with_background: false inputs_def: fields:
    • image
    • im_size
    • im_id
    • gt_bbox
    • gt_class
    • is_difficult image_shape:
    • 3
    • 416
    • 416 num_max_boxes: 50 sample_transforms:
  • !DecodeImage to_rgb: true with_mixup: false
  • !ResizeImage interp: 2 max_size: 0 target_size: 608 use_cv2: true
  • !NormalizeImage is_channel_first: false is_scale: true mean:
    • 0.485
    • 0.456
    • 0.406 std:
    • 0.229
    • 0.224
    • 0.225
  • !Permute channel_first: true to_bgr: false TrainReader: batch_size: 1 batch_transforms:
  • !RandomShape random_inter: false sizes:
    • 320
  • !Permute channel_first: true to_bgr: false bufsize: 16 dataset: !VOCDataSet anno_path: train.txt dataset_dir: dataset/voc image_dir: '' label_list: label_list.txt sample_num: -1 use_default_label: false with_background: false drop_last: true inputs_def: fields:
    • image
    • gt_bbox
    • gt_class
    • gt_score image_shape:
    • 3
    • 320
    • 320 num_max_boxes: 50 mixup_epoch: -1 sample_transforms:
  • !DecodeImage to_rgb: true with_mixup: false
  • !NormalizeBox {}
  • !ExpandImage max_ratio: 4.0 mean:
    • 123.675
    • 116.28
    • 103.53 prob: 0.5
  • !RandomInterpImage max_size: 0 target_size: 320
  • !RandomFlipImage is_mask_flip: false is_normalized: true prob: 0.5
  • !NormalizeImage is_channel_first: false is_scale: true mean:
    • 0.485
    • 0.456
    • 0.406 std:
    • 0.229
    • 0.224
    • 0.225
  • !PadBox num_max_boxes: 50
  • !BboxXYXY2XYWH {} shuffle: true use_process: true worker_num: 8 YOLOv3: [32mbackbone[0m: DarkNet use_fine_grained_loss: false yolo_head: YOLOv3Head YOLOv3Head: [32mnms[0m: background_label: -1 keep_top_k: 100 nms_threshold: 0.45 nms_top_k: 1000 normalized: false score_threshold: 0.01 anchor_masks:
    • 6
    • 7
    • 8
    • 3
    • 4
    • 5
    • 0
    • 1
    • 2 anchors:
    • 10
    • 13
    • 16
    • 30
    • 33
    • 23
    • 30
    • 61
    • 62
    • 45
    • 59
    • 119
    • 116
    • 90
    • 156
    • 198
    • 373
    • 326 block_size: 3 drop_block: false keep_prob: 0.9 norm_decay: 0.0 num_classes: 80 weight_prefix_name: '' yolo_loss: YOLOv3Loss YOLOv3Loss: [32mlabel_smooth[0m: false batch_size: 8 ignore_thresh: 0.7 iou_loss: null use_fine_grained_loss: false architecture: YOLOv3 log_smooth_window: 20 map_type: 11point max_iters: 20000 metric: VOC num_classes: 2 pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/DarkNet53_pretrained.tar save_dir: output snapshot_iter: 500 use_gpu: true weights: output/yolov3_darknet_voc/model_final

2020-04-24 17:30:09,905-INFO: 400 samples in file dataset/voc/val.txt 2020-04-24 17:30:09,906-INFO: places would be ommited when DataLoader is not iterable W0424 17:30:10.761812 5432 device_context.cc:237] Please NOTE: device: 0, CUDA Capability: 70, Driver API Version: 10.1, Runtime API Version: 9.0 W0424 17:30:10.766005 5432 device_context.cc:245] device: 0, cuDNN Version: 7.3. 2020-04-24 17:30:12,432-INFO: Found /home/aistudio/.cache/paddle/weights/DarkNet53_pretrained 2020-04-24 17:30:12,432-INFO: Loading parameters from /home/aistudio/.cache/paddle/weights/DarkNet53_pretrained... 2020-04-24 17:30:12,433-WARNING: /home/aistudio/.cache/paddle/weights/DarkNet53_pretrained.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ] 2020-04-24 17:30:12,433-WARNING: /home/aistudio/.cache/paddle/weights/DarkNet53_pretrained.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ] 2020-04-24 17:30:12,872-INFO: 2000 samples in file dataset/voc/train.txt 2020-04-24 17:30:18,408-INFO: places would be ommited when DataLoader is not iterable I0424 17:30:18.952929 5432 parallel_executor.cc:440] The Program will be executed on CUDA using ParallelExecutor, 1 cards are used, so 1 programs are executed in parallel. I0424 17:30:19.038331 5432 build_strategy.cc:365] SeqOnlyAllReduceOps:0, num_trainers:1 I0424 17:30:19.126165 5432 parallel_executor.cc:307] Inplace strategy is enabled, when build_strategy.enable_inplace = True I0424 17:30:19.156368 5432 parallel_executor.cc:375] Garbage collection strategy is enabled, when FLAGS_eager_delete_tensor_gb = 0 2020-04-24 17:30:19,407-INFO: iter: 0, lr: 0.000000, 'loss': '4773.457031', time: 0.481, eta: 2:40:20 2020-04-24 17:30:20,641-INFO: iter: 20, lr: 0.000010, 'loss': '1409.508789', time: 0.084, eta: 0:28:07 2020-04-24 17:30:21,877-INFO: iter: 40, lr: 0.000020, 'loss': '23.782974', time: 0.062, eta: 0:20:31 2020-04-24 17:30:23,082-INFO: iter: 60, lr: 0.000030, 'loss': '17.599674', time: 0.060, eta: 0:20:03 2020-04-24 17:30:24,301-INFO: iter: 80, lr: 0.000040, 'loss': '15.050756', time: 0.061, eta: 0:20:13 2020-04-24 17:30:25,534-INFO: iter: 100, lr: 0.000050, 'loss': '14.313501', time: 0.061, eta: 0:20:21 2020-04-24 17:30:26,763-INFO: iter: 120, lr: 0.000050, 'loss': '14.838196', time: 0.062, eta: 0:20:27 2020-04-24 17:30:27,982-INFO: iter: 140, lr: 0.000050, 'loss': '14.684652', time: 0.061, eta: 0:20:09 2020-04-24 17:30:29,233-INFO: iter: 160, lr: 0.000050, 'loss': '13.258968', time: 0.063, eta: 0:20:42 2020-04-24 17:30:30,451-INFO: iter: 180, lr: 0.000050, 'loss': '13.263744', time: 0.061, eta: 0:20:06 2020-04-24 17:30:31,713-INFO: iter: 200, lr: 0.000050, 'loss': '10.825136', time: 0.063, eta: 0:20:44 2020-04-24 17:30:32,988-INFO: iter: 220, lr: 0.000050, 'loss': '11.288977', time: 0.064, eta: 0:21:06 2020-04-24 17:30:34,257-INFO: iter: 240, lr: 0.000050, 'loss': '10.903563', time: 0.063, eta: 0:20:53 2020-04-24 17:30:35,506-INFO: iter: 260, lr: 0.000050, 'loss': '9.900716', time: 0.062, eta: 0:20:32 2020-04-24 17:30:36,773-INFO: iter: 280, lr: 0.000050, 'loss': '9.340356', time: 0.063, eta: 0:20:47 2020-04-24 17:30:38,098-INFO: iter: 300, lr: 0.000050, 'loss': '9.690082', time: 0.066, eta: 0:21:43 2020-04-24 17:30:39,352-INFO: iter: 320, lr: 0.000050, 'loss': '8.055832', time: 0.062, eta: 0:20:25 2020-04-24 17:30:40,632-INFO: iter: 340, lr: 0.000050, 'loss': '9.590485', time: 0.065, eta: 0:21:10 2020-04-24 17:30:41,883-INFO: iter: 360, lr: 0.000050, 'loss': '10.166349', time: 0.062, eta: 0:20:24 2020-04-24 17:30:43,123-INFO: iter: 380, lr: 0.000050, 'loss': '10.168574', time: 0.062, eta: 0:20:18 2020-04-24 17:30:44,400-INFO: iter: 400, lr: 0.000050, 'loss': '7.831622', time: 0.064, eta: 0:20:51 2020-04-24 17:30:45,723-INFO: iter: 420, lr: 0.000050, 'loss': '9.169244', time: 0.066, eta: 0:21:31 2020-04-24 17:30:47,123-INFO: iter: 440, lr: 0.000050, 'loss': '7.621997', time: 0.070, eta: 0:22:45 2020-04-24 17:30:48,479-INFO: iter: 460, lr: 0.000050, 'loss': '8.698738', time: 0.068, eta: 0:22:07 2020-04-24 17:30:49,812-INFO: iter: 480, lr: 0.000050, 'loss': '7.786939', time: 0.067, eta: 0:21:44 2020-04-24 17:30:51,805-INFO: iter: 500, lr: 0.000050, 'loss': '7.212985', time: 0.096, eta: 0:31:03 2020-04-24 17:30:51,806-INFO: Save model to output/yolov3_darknet_voc/500. I0424 17:31:01.150171 5432 parallel_executor.cc:440] The Program will be executed on CUDA using ParallelExecutor, 1 cards are used, so 1 programs are executed in parallel. I0424 17:31:01.165114 5432 build_strategy.cc:365] SeqOnlyAllReduceOps:0, num_trainers:1 2020-04-24 17:31:01,582-INFO: Test iter 0 2020-04-24 17:31:06,532-INFO: Test finish iter 50 2020-04-24 17:31:06,532-INFO: Total number of images: 330, inference time: 61.14727857519788 fps. 2020-04-24 17:31:06,532-INFO: Start evaluate... 2020-04-24 17:31:06,543-INFO: Accumulating evaluatation results... 2020-04-24 17:31:06,544-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:31:06,545-INFO: Best test box ap: 0.0, in iter: 0 2020-04-24 17:31:07,881-INFO: iter: 520, lr: 0.000050, 'loss': '7.609744', time: 0.808, eta: 4:22:17 2020-04-24 17:31:09,181-INFO: iter: 540, lr: 0.000050, 'loss': '6.739043', time: 0.065, eta: 0:21:06 2020-04-24 17:31:10,447-INFO: iter: 560, lr: 0.000050, 'loss': '6.488116', time: 0.063, eta: 0:20:28 2020-04-24 17:31:11,725-INFO: iter: 580, lr: 0.000050, 'loss': '6.817792', time: 0.064, eta: 0:20:43 2020-04-24 17:31:12,997-INFO: iter: 600, lr: 0.000050, 'loss': '6.678132', time: 0.064, eta: 0:20:33 2020-04-24 17:31:14,245-INFO: iter: 620, lr: 0.000050, 'loss': '7.531629', time: 0.062, eta: 0:20:09 2020-04-24 17:31:15,520-INFO: iter: 640, lr: 0.000050, 'loss': '7.095046', time: 0.064, eta: 0:20:32 2020-04-24 17:31:16,802-INFO: iter: 660, lr: 0.000050, 'loss': '6.469002', time: 0.064, eta: 0:20:37 2020-04-24 17:31:18,029-INFO: iter: 680, lr: 0.000050, 'loss': '7.422760', time: 0.062, eta: 0:19:48 2020-04-24 17:31:19,256-INFO: iter: 700, lr: 0.000050, 'loss': '7.083989', time: 0.061, eta: 0:19:44 2020-04-24 17:31:20,513-INFO: iter: 720, lr: 0.000050, 'loss': '6.064008', time: 0.063, eta: 0:20:06 2020-04-24 17:31:21,766-INFO: iter: 740, lr: 0.000050, 'loss': '6.777224', time: 0.063, eta: 0:20:11 2020-04-24 17:31:23,025-INFO: iter: 760, lr: 0.000050, 'loss': '6.657913', time: 0.063, eta: 0:20:07 2020-04-24 17:31:24,285-INFO: iter: 780, lr: 0.000050, 'loss': '6.082125', time: 0.063, eta: 0:20:12 2020-04-24 17:31:25,566-INFO: iter: 800, lr: 0.000050, 'loss': '7.032570', time: 0.064, eta: 0:20:29 2020-04-24 17:31:26,876-INFO: iter: 820, lr: 0.000050, 'loss': '6.071781', time: 0.065, eta: 0:20:54 2020-04-24 17:31:28,104-INFO: iter: 840, lr: 0.000050, 'loss': '5.644063', time: 0.062, eta: 0:19:42 2020-04-24 17:31:29,328-INFO: iter: 860, lr: 0.000050, 'loss': '5.783629', time: 0.061, eta: 0:19:31 2020-04-24 17:31:30,584-INFO: iter: 880, lr: 0.000050, 'loss': '6.077067', time: 0.063, eta: 0:19:58 2020-04-24 17:31:31,877-INFO: iter: 900, lr: 0.000050, 'loss': '6.488541', time: 0.065, eta: 0:20:35 2020-04-24 17:31:33,123-INFO: iter: 920, lr: 0.000050, 'loss': '6.573437', time: 0.062, eta: 0:19:48 2020-04-24 17:31:34,390-INFO: iter: 940, lr: 0.000050, 'loss': '6.228198', time: 0.063, eta: 0:20:06 2020-04-24 17:31:35,642-INFO: iter: 960, lr: 0.000050, 'loss': '6.231107', time: 0.062, eta: 0:19:48 2020-04-24 17:31:36,906-INFO: iter: 980, lr: 0.000050, 'loss': '6.189282', time: 0.063, eta: 0:20:03 2020-04-24 17:31:38,211-INFO: iter: 1000, lr: 0.000050, 'loss': '5.421929', time: 0.065, eta: 0:20:41 2020-04-24 17:31:38,211-INFO: Save model to output/yolov3_darknet_voc/1000. 2020-04-24 17:31:43,979-INFO: Test iter 0 2020-04-24 17:31:48,530-INFO: Test finish iter 50 2020-04-24 17:31:48,530-INFO: Total number of images: 400, inference time: 84.8747262740581 fps. 2020-04-24 17:31:48,530-INFO: Start evaluate... 2020-04-24 17:31:48,566-INFO: Accumulating evaluatation results... 2020-04-24 17:31:48,569-INFO: mAP(0.50, 11point) = 1.70 2020-04-24 17:31:48,570-INFO: Save model to output/yolov3_darknet_voc/best_model. 2020-04-24 17:31:54,048-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:31:55,334-INFO: iter: 1020, lr: 0.000050, 'loss': '6.135723', time: 0.856, eta: 4:30:48 2020-04-24 17:31:56,595-INFO: iter: 1040, lr: 0.000050, 'loss': '5.716703', time: 0.063, eta: 0:19:52 2020-04-24 17:31:57,892-INFO: iter: 1060, lr: 0.000050, 'loss': '5.570798', time: 0.065, eta: 0:20:31 2020-04-24 17:31:59,190-INFO: iter: 1080, lr: 0.000050, 'loss': '5.764952', time: 0.065, eta: 0:20:28 2020-04-24 17:32:00,481-INFO: iter: 1100, lr: 0.000050, 'loss': '4.758157', time: 0.065, eta: 0:20:19 2020-04-24 17:32:01,787-INFO: iter: 1120, lr: 0.000050, 'loss': '5.529131', time: 0.065, eta: 0:20:27 2020-04-24 17:32:03,079-INFO: iter: 1140, lr: 0.000050, 'loss': '5.184276', time: 0.065, eta: 0:20:24 2020-04-24 17:32:04,317-INFO: iter: 1160, lr: 0.000050, 'loss': '5.358259', time: 0.062, eta: 0:19:25 2020-04-24 17:32:05,583-INFO: iter: 1180, lr: 0.000050, 'loss': '5.288213', time: 0.063, eta: 0:19:43 2020-04-24 17:32:06,877-INFO: iter: 1200, lr: 0.000050, 'loss': '5.238584', time: 0.065, eta: 0:20:20 2020-04-24 17:32:08,127-INFO: iter: 1220, lr: 0.000050, 'loss': '5.148386', time: 0.063, eta: 0:19:36 2020-04-24 17:32:09,392-INFO: iter: 1240, lr: 0.000050, 'loss': '5.641284', time: 0.063, eta: 0:19:49 2020-04-24 17:32:10,659-INFO: iter: 1260, lr: 0.000050, 'loss': '4.579816', time: 0.063, eta: 0:19:38 2020-04-24 17:32:11,953-INFO: iter: 1280, lr: 0.000050, 'loss': '5.127717', time: 0.065, eta: 0:20:12 2020-04-24 17:32:13,225-INFO: iter: 1300, lr: 0.000050, 'loss': '4.734833', time: 0.064, eta: 0:19:53 2020-04-24 17:32:14,479-INFO: iter: 1320, lr: 0.000050, 'loss': '5.967862', time: 0.063, eta: 0:19:29 2020-04-24 17:32:15,736-INFO: iter: 1340, lr: 0.000050, 'loss': '5.260326', time: 0.063, eta: 0:19:34 2020-04-24 17:32:17,002-INFO: iter: 1360, lr: 0.000050, 'loss': '4.766984', time: 0.063, eta: 0:19:40 2020-04-24 17:32:18,262-INFO: iter: 1380, lr: 0.000050, 'loss': '5.429349', time: 0.063, eta: 0:19:32 2020-04-24 17:32:19,552-INFO: iter: 1400, lr: 0.000050, 'loss': '4.848065', time: 0.065, eta: 0:20:00 2020-04-24 17:32:20,814-INFO: iter: 1420, lr: 0.000050, 'loss': '4.363996', time: 0.063, eta: 0:19:31 2020-04-24 17:32:22,089-INFO: iter: 1440, lr: 0.000050, 'loss': '4.136049', time: 0.064, eta: 0:19:44 2020-04-24 17:32:23,324-INFO: iter: 1460, lr: 0.000050, 'loss': '4.752804', time: 0.062, eta: 0:19:03 2020-04-24 17:32:24,566-INFO: iter: 1480, lr: 0.000050, 'loss': '4.147980', time: 0.062, eta: 0:19:11 2020-04-24 17:32:25,824-INFO: iter: 1500, lr: 0.000050, 'loss': '4.594424', time: 0.063, eta: 0:19:23 2020-04-24 17:32:25,824-INFO: Save model to output/yolov3_darknet_voc/1500. 2020-04-24 17:32:31,548-INFO: Test iter 0 2020-04-24 17:32:36,132-INFO: Test finish iter 50 2020-04-24 17:32:36,132-INFO: Total number of images: 379, inference time: 79.89329957557031 fps. 2020-04-24 17:32:36,133-INFO: Start evaluate... 2020-04-24 17:32:36,179-INFO: Accumulating evaluatation results... 2020-04-24 17:32:36,181-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:32:36,182-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:32:37,468-INFO: iter: 1520, lr: 0.000050, 'loss': '4.950881', time: 0.582, eta: 2:59:11 2020-04-24 17:32:38,727-INFO: iter: 1540, lr: 0.000050, 'loss': '5.070341', time: 0.063, eta: 0:19:28 2020-04-24 17:32:39,996-INFO: iter: 1560, lr: 0.000050, 'loss': '4.386658', time: 0.063, eta: 0:19:29 2020-04-24 17:32:41,298-INFO: iter: 1580, lr: 0.000050, 'loss': '6.025648', time: 0.065, eta: 0:19:50 2020-04-24 17:32:42,558-INFO: iter: 1600, lr: 0.000050, 'loss': '4.983917', time: 0.063, eta: 0:19:23 2020-04-24 17:32:43,846-INFO: iter: 1620, lr: 0.000050, 'loss': '4.397292', time: 0.065, eta: 0:19:45 2020-04-24 17:32:45,166-INFO: iter: 1640, lr: 0.000050, 'loss': '5.149240', time: 0.066, eta: 0:20:16 2020-04-24 17:32:46,489-INFO: iter: 1660, lr: 0.000050, 'loss': '4.536232', time: 0.066, eta: 0:20:05 2020-04-24 17:32:47,768-INFO: iter: 1680, lr: 0.000050, 'loss': '5.557236', time: 0.064, eta: 0:19:37 2020-04-24 17:32:49,015-INFO: iter: 1700, lr: 0.000050, 'loss': '4.213097', time: 0.062, eta: 0:18:53 2020-04-24 17:32:50,300-INFO: iter: 1720, lr: 0.000050, 'loss': '4.521544', time: 0.064, eta: 0:19:36 2020-04-24 17:32:51,622-INFO: iter: 1740, lr: 0.000050, 'loss': '5.162963', time: 0.066, eta: 0:20:12 2020-04-24 17:32:52,877-INFO: iter: 1760, lr: 0.000050, 'loss': '5.276527', time: 0.062, eta: 0:18:59 2020-04-24 17:32:54,134-INFO: iter: 1780, lr: 0.000050, 'loss': '4.523553', time: 0.063, eta: 0:19:10 2020-04-24 17:32:55,399-INFO: iter: 1800, lr: 0.000050, 'loss': '5.220922', time: 0.063, eta: 0:19:00 2020-04-24 17:32:56,682-INFO: iter: 1820, lr: 0.000050, 'loss': '4.543086', time: 0.064, eta: 0:19:27 2020-04-24 17:32:57,934-INFO: iter: 1840, lr: 0.000050, 'loss': '5.097485', time: 0.063, eta: 0:19:03 2020-04-24 17:32:59,201-INFO: iter: 1860, lr: 0.000050, 'loss': '4.963557', time: 0.063, eta: 0:19:05 2020-04-24 17:33:00,486-INFO: iter: 1880, lr: 0.000050, 'loss': '4.227762', time: 0.064, eta: 0:19:28 2020-04-24 17:33:01,749-INFO: iter: 1900, lr: 0.000050, 'loss': '4.564885', time: 0.063, eta: 0:19:03 2020-04-24 17:33:03,010-INFO: iter: 1920, lr: 0.000050, 'loss': '5.124654', time: 0.063, eta: 0:18:59 2020-04-24 17:33:04,334-INFO: iter: 1940, lr: 0.000050, 'loss': '4.680788', time: 0.066, eta: 0:19:51 2020-04-24 17:33:05,641-INFO: iter: 1960, lr: 0.000050, 'loss': '4.832697', time: 0.066, eta: 0:19:42 2020-04-24 17:33:06,941-INFO: iter: 1980, lr: 0.000050, 'loss': '5.309194', time: 0.065, eta: 0:19:28 2020-04-24 17:33:08,185-INFO: iter: 2000, lr: 0.000050, 'loss': '4.407988', time: 0.062, eta: 0:18:43 2020-04-24 17:33:08,185-INFO: Save model to output/yolov3_darknet_voc/2000. 2020-04-24 17:33:13,928-INFO: Test iter 0 2020-04-24 17:33:18,429-INFO: Test finish iter 50 2020-04-24 17:33:18,429-INFO: Total number of images: 393, inference time: 84.39176058310929 fps. 2020-04-24 17:33:18,429-INFO: Start evaluate... 2020-04-24 17:33:18,454-INFO: Accumulating evaluatation results... 2020-04-24 17:33:18,456-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:33:18,456-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:33:19,701-INFO: iter: 2020, lr: 0.000050, 'loss': '3.878085', time: 0.576, eta: 2:52:31 2020-04-24 17:33:20,970-INFO: iter: 2040, lr: 0.000050, 'loss': '4.676570', time: 0.063, eta: 0:18:58 2020-04-24 17:33:22,236-INFO: iter: 2060, lr: 0.000050, 'loss': '4.356619', time: 0.063, eta: 0:18:51 2020-04-24 17:33:23,525-INFO: iter: 2080, lr: 0.000050, 'loss': '4.460249', time: 0.065, eta: 0:19:20 2020-04-24 17:33:24,801-INFO: iter: 2100, lr: 0.000050, 'loss': '4.970535', time: 0.064, eta: 0:18:58 2020-04-24 17:33:26,046-INFO: iter: 2120, lr: 0.000050, 'loss': '4.742765', time: 0.063, eta: 0:18:38 2020-04-24 17:33:27,309-INFO: iter: 2140, lr: 0.000050, 'loss': '4.687847', time: 0.063, eta: 0:18:47 2020-04-24 17:33:28,553-INFO: iter: 2160, lr: 0.000050, 'loss': '3.581655', time: 0.062, eta: 0:18:22 2020-04-24 17:33:29,861-INFO: iter: 2180, lr: 0.000050, 'loss': '3.991680', time: 0.065, eta: 0:19:23 2020-04-24 17:33:31,137-INFO: iter: 2200, lr: 0.000050, 'loss': '3.999994', time: 0.064, eta: 0:19:03 2020-04-24 17:33:32,372-INFO: iter: 2220, lr: 0.000050, 'loss': '4.434382', time: 0.062, eta: 0:18:18 2020-04-24 17:33:33,634-INFO: iter: 2240, lr: 0.000050, 'loss': '4.732727', time: 0.063, eta: 0:18:34 2020-04-24 17:33:34,874-INFO: iter: 2260, lr: 0.000050, 'loss': '4.424267', time: 0.062, eta: 0:18:19 2020-04-24 17:33:36,121-INFO: iter: 2280, lr: 0.000050, 'loss': '4.294651', time: 0.063, eta: 0:18:30 2020-04-24 17:33:37,371-INFO: iter: 2300, lr: 0.000050, 'loss': '4.137033', time: 0.063, eta: 0:18:27 2020-04-24 17:33:38,633-INFO: iter: 2320, lr: 0.000050, 'loss': '4.550075', time: 0.063, eta: 0:18:33 2020-04-24 17:33:39,874-INFO: iter: 2340, lr: 0.000050, 'loss': '4.238888', time: 0.062, eta: 0:18:14 2020-04-24 17:33:41,145-INFO: iter: 2360, lr: 0.000050, 'loss': '5.045639', time: 0.063, eta: 0:18:40 2020-04-24 17:33:42,397-INFO: iter: 2380, lr: 0.000050, 'loss': '4.404350', time: 0.063, eta: 0:18:27 2020-04-24 17:33:43,657-INFO: iter: 2400, lr: 0.000050, 'loss': '4.916344', time: 0.063, eta: 0:18:24 2020-04-24 17:33:44,882-INFO: iter: 2420, lr: 0.000050, 'loss': '5.149046', time: 0.061, eta: 0:18:01 2020-04-24 17:33:46,128-INFO: iter: 2440, lr: 0.000050, 'loss': '4.403241', time: 0.062, eta: 0:18:13 2020-04-24 17:33:47,386-INFO: iter: 2460, lr: 0.000050, 'loss': '3.845775', time: 0.063, eta: 0:18:20 2020-04-24 17:33:48,642-INFO: iter: 2480, lr: 0.000050, 'loss': '3.618093', time: 0.063, eta: 0:18:22 2020-04-24 17:33:49,903-INFO: iter: 2500, lr: 0.000050, 'loss': '4.390198', time: 0.063, eta: 0:18:22 2020-04-24 17:33:49,903-INFO: Save model to output/yolov3_darknet_voc/2500. 2020-04-24 17:33:55,466-INFO: Test iter 0 2020-04-24 17:33:59,967-INFO: Test finish iter 50 2020-04-24 17:33:59,967-INFO: Total number of images: 295, inference time: 63.39115944854206 fps. 2020-04-24 17:33:59,968-INFO: Start evaluate... 2020-04-24 17:33:59,983-INFO: Accumulating evaluatation results... 2020-04-24 17:33:59,984-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:33:59,985-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:34:01,272-INFO: iter: 2520, lr: 0.000050, 'loss': '3.677579', time: 0.568, eta: 2:45:34 2020-04-24 17:34:02,557-INFO: iter: 2540, lr: 0.000050, 'loss': '3.887392', time: 0.064, eta: 0:18:44 2020-04-24 17:34:03,836-INFO: iter: 2560, lr: 0.000050, 'loss': '4.133051', time: 0.064, eta: 0:18:28 2020-04-24 17:34:05,141-INFO: iter: 2580, lr: 0.000050, 'loss': '4.074432', time: 0.066, eta: 0:19:02 2020-04-24 17:34:06,501-INFO: iter: 2600, lr: 0.000050, 'loss': '3.974929', time: 0.068, eta: 0:19:40 2020-04-24 17:34:07,730-INFO: iter: 2620, lr: 0.000050, 'loss': '3.798744', time: 0.062, eta: 0:17:52 2020-04-24 17:34:08,969-INFO: iter: 2640, lr: 0.000050, 'loss': '4.136965', time: 0.062, eta: 0:17:52 2020-04-24 17:34:10,262-INFO: iter: 2660, lr: 0.000050, 'loss': '4.826468', time: 0.064, eta: 0:18:36 2020-04-24 17:34:11,562-INFO: iter: 2680, lr: 0.000050, 'loss': '3.941839', time: 0.065, eta: 0:18:51 2020-04-24 17:34:12,873-INFO: iter: 2700, lr: 0.000050, 'loss': '4.404241', time: 0.066, eta: 0:18:53 2020-04-24 17:34:14,155-INFO: iter: 2720, lr: 0.000050, 'loss': '3.813055', time: 0.064, eta: 0:18:27 2020-04-24 17:34:15,457-INFO: iter: 2740, lr: 0.000050, 'loss': '4.170776', time: 0.065, eta: 0:18:46 2020-04-24 17:34:16,698-INFO: iter: 2760, lr: 0.000050, 'loss': '4.172401', time: 0.062, eta: 0:17:50 2020-04-24 17:34:17,965-INFO: iter: 2780, lr: 0.000050, 'loss': '4.235612', time: 0.063, eta: 0:18:04 2020-04-24 17:34:19,267-INFO: iter: 2800, lr: 0.000050, 'loss': '4.621957', time: 0.065, eta: 0:18:43 2020-04-24 17:34:20,521-INFO: iter: 2820, lr: 0.000050, 'loss': '3.950712', time: 0.063, eta: 0:17:57 2020-04-24 17:34:21,768-INFO: iter: 2840, lr: 0.000050, 'loss': '4.592880', time: 0.062, eta: 0:17:51 2020-04-24 17:34:23,016-INFO: iter: 2860, lr: 0.000050, 'loss': '4.211164', time: 0.062, eta: 0:17:49 2020-04-24 17:34:24,268-INFO: iter: 2880, lr: 0.000050, 'loss': '3.842400', time: 0.063, eta: 0:17:51 2020-04-24 17:34:25,522-INFO: iter: 2900, lr: 0.000050, 'loss': '3.910372', time: 0.063, eta: 0:17:51 2020-04-24 17:34:26,780-INFO: iter: 2920, lr: 0.000050, 'loss': '4.204413', time: 0.063, eta: 0:17:54 2020-04-24 17:34:27,998-INFO: iter: 2940, lr: 0.000050, 'loss': '4.185066', time: 0.061, eta: 0:17:20 2020-04-24 17:34:29,250-INFO: iter: 2960, lr: 0.000050, 'loss': '4.126792', time: 0.063, eta: 0:17:46 2020-04-24 17:34:30,503-INFO: iter: 2980, lr: 0.000050, 'loss': '4.319037', time: 0.063, eta: 0:17:45 2020-04-24 17:34:31,756-INFO: iter: 3000, lr: 0.000050, 'loss': '4.234204', time: 0.063, eta: 0:17:44 2020-04-24 17:34:31,756-INFO: Save model to output/yolov3_darknet_voc/3000. 2020-04-24 17:34:37,192-INFO: Test iter 0 2020-04-24 17:34:41,735-INFO: Test finish iter 50 2020-04-24 17:34:41,736-INFO: Total number of images: 295, inference time: 62.70573926017223 fps. 2020-04-24 17:34:41,736-INFO: Start evaluate... 2020-04-24 17:34:41,751-INFO: Accumulating evaluatation results... 2020-04-24 17:34:41,752-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:34:41,753-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:34:43,030-INFO: iter: 3020, lr: 0.000050, 'loss': '3.677397', time: 0.564, eta: 2:39:32 2020-04-24 17:34:44,290-INFO: iter: 3040, lr: 0.000050, 'loss': '4.367497', time: 0.063, eta: 0:17:46 2020-04-24 17:34:45,551-INFO: iter: 3060, lr: 0.000050, 'loss': '4.018065', time: 0.063, eta: 0:17:48 2020-04-24 17:34:46,818-INFO: iter: 3080, lr: 0.000050, 'loss': '3.782524', time: 0.063, eta: 0:17:51 2020-04-24 17:34:48,078-INFO: iter: 3100, lr: 0.000050, 'loss': '3.648066', time: 0.063, eta: 0:17:43 2020-04-24 17:34:49,327-INFO: iter: 3120, lr: 0.000050, 'loss': '4.028178', time: 0.062, eta: 0:17:34 2020-04-24 17:34:50,588-INFO: iter: 3140, lr: 0.000050, 'loss': '3.712103', time: 0.063, eta: 0:17:44 2020-04-24 17:34:51,848-INFO: iter: 3160, lr: 0.000050, 'loss': '3.744527', time: 0.063, eta: 0:17:41 2020-04-24 17:34:53,129-INFO: iter: 3180, lr: 0.000050, 'loss': '3.641301', time: 0.064, eta: 0:17:52 2020-04-24 17:34:54,396-INFO: iter: 3200, lr: 0.000050, 'loss': '4.225049', time: 0.063, eta: 0:17:42 2020-04-24 17:34:55,650-INFO: iter: 3220, lr: 0.000050, 'loss': '4.591234', time: 0.063, eta: 0:17:38 2020-04-24 17:34:56,917-INFO: iter: 3240, lr: 0.000050, 'loss': '4.941355', time: 0.063, eta: 0:17:41 2020-04-24 17:34:58,182-INFO: iter: 3260, lr: 0.000050, 'loss': '4.361785', time: 0.063, eta: 0:17:37 2020-04-24 17:34:59,454-INFO: iter: 3280, lr: 0.000050, 'loss': '4.044730', time: 0.063, eta: 0:17:38 2020-04-24 17:35:00,696-INFO: iter: 3300, lr: 0.000050, 'loss': '4.055280', time: 0.062, eta: 0:17:21 2020-04-24 17:35:01,948-INFO: iter: 3320, lr: 0.000050, 'loss': '3.779968', time: 0.063, eta: 0:17:23 2020-04-24 17:35:03,213-INFO: iter: 3340, lr: 0.000050, 'loss': '3.972363', time: 0.063, eta: 0:17:32 2020-04-24 17:35:04,562-INFO: iter: 3360, lr: 0.000050, 'loss': '3.513335', time: 0.067, eta: 0:18:37 2020-04-24 17:35:05,822-INFO: iter: 3380, lr: 0.000050, 'loss': '3.236209', time: 0.063, eta: 0:17:33 2020-04-24 17:35:07,056-INFO: iter: 3400, lr: 0.000050, 'loss': '3.346684', time: 0.062, eta: 0:17:06 2020-04-24 17:35:08,299-INFO: iter: 3420, lr: 0.000050, 'loss': '3.462277', time: 0.062, eta: 0:17:01 2020-04-24 17:35:09,527-INFO: iter: 3440, lr: 0.000050, 'loss': '3.696031', time: 0.062, eta: 0:17:06 2020-04-24 17:35:10,776-INFO: iter: 3460, lr: 0.000050, 'loss': '3.872711', time: 0.062, eta: 0:17:11 2020-04-24 17:35:12,022-INFO: iter: 3480, lr: 0.000050, 'loss': '4.090693', time: 0.062, eta: 0:17:10 2020-04-24 17:35:13,296-INFO: iter: 3500, lr: 0.000050, 'loss': '3.955009', time: 0.063, eta: 0:17:27 2020-04-24 17:35:13,296-INFO: Save model to output/yolov3_darknet_voc/3500. 2020-04-24 17:35:18,885-INFO: Test iter 0 2020-04-24 17:35:23,427-INFO: Test finish iter 50 2020-04-24 17:35:23,427-INFO: Total number of images: 253, inference time: 53.88793293180902 fps. 2020-04-24 17:35:23,428-INFO: Start evaluate... 2020-04-24 17:35:23,437-INFO: Accumulating evaluatation results... 2020-04-24 17:35:23,437-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:35:23,438-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:35:24,721-INFO: iter: 3520, lr: 0.000050, 'loss': '3.986967', time: 0.571, eta: 2:36:52 2020-04-24 17:35:26,058-INFO: iter: 3540, lr: 0.000050, 'loss': '4.015666', time: 0.067, eta: 0:18:17 2020-04-24 17:35:27,334-INFO: iter: 3560, lr: 0.000050, 'loss': '4.229417', time: 0.064, eta: 0:17:31 2020-04-24 17:35:28,576-INFO: iter: 3580, lr: 0.000050, 'loss': '4.065807', time: 0.062, eta: 0:17:03 2020-04-24 17:35:29,849-INFO: iter: 3600, lr: 0.000050, 'loss': '3.542905', time: 0.064, eta: 0:17:23 2020-04-24 17:35:31,100-INFO: iter: 3620, lr: 0.000050, 'loss': '3.862190', time: 0.063, eta: 0:17:04 2020-04-24 17:35:32,405-INFO: iter: 3640, lr: 0.000050, 'loss': '3.813509', time: 0.065, eta: 0:17:44 2020-04-24 17:35:33,738-INFO: iter: 3660, lr: 0.000050, 'loss': '3.870656', time: 0.067, eta: 0:18:08 2020-04-24 17:35:35,060-INFO: iter: 3680, lr: 0.000050, 'loss': '4.449153', time: 0.066, eta: 0:17:58 2020-04-24 17:35:36,354-INFO: iter: 3700, lr: 0.000050, 'loss': '3.878476', time: 0.065, eta: 0:17:34 2020-04-24 17:35:37,663-INFO: iter: 3720, lr: 0.000050, 'loss': '3.861081', time: 0.066, eta: 0:17:48 2020-04-24 17:35:38,952-INFO: iter: 3740, lr: 0.000050, 'loss': '3.699723', time: 0.065, eta: 0:17:29 2020-04-24 17:35:40,268-INFO: iter: 3760, lr: 0.000050, 'loss': '3.784134', time: 0.066, eta: 0:17:47 2020-04-24 17:35:41,541-INFO: iter: 3780, lr: 0.000050, 'loss': '3.079592', time: 0.064, eta: 0:17:10 2020-04-24 17:35:42,824-INFO: iter: 3800, lr: 0.000050, 'loss': '3.752543', time: 0.064, eta: 0:17:16 2020-04-24 17:35:44,100-INFO: iter: 3820, lr: 0.000050, 'loss': '3.995926', time: 0.064, eta: 0:17:08 2020-04-24 17:35:45,401-INFO: iter: 3840, lr: 0.000050, 'loss': '3.735324', time: 0.066, eta: 0:17:38 2020-04-24 17:35:46,708-INFO: iter: 3860, lr: 0.000050, 'loss': '3.492469', time: 0.065, eta: 0:17:33 2020-04-24 17:35:47,987-INFO: iter: 3880, lr: 0.000050, 'loss': '4.250998', time: 0.064, eta: 0:17:14 2020-04-24 17:35:49,241-INFO: iter: 3900, lr: 0.000050, 'loss': '3.767215', time: 0.063, eta: 0:16:46 2020-04-24 17:35:50,511-INFO: iter: 3920, lr: 0.000050, 'loss': '4.088290', time: 0.063, eta: 0:17:00 2020-04-24 17:35:51,769-INFO: iter: 3940, lr: 0.000050, 'loss': '3.392008', time: 0.063, eta: 0:16:51 2020-04-24 17:35:53,037-INFO: iter: 3960, lr: 0.000050, 'loss': '3.524767', time: 0.063, eta: 0:16:50 2020-04-24 17:35:54,267-INFO: iter: 3980, lr: 0.000050, 'loss': '3.789393', time: 0.062, eta: 0:16:33 2020-04-24 17:35:55,512-INFO: iter: 4000, lr: 0.000050, 'loss': '4.084249', time: 0.062, eta: 0:16:35 2020-04-24 17:35:55,512-INFO: Save model to output/yolov3_darknet_voc/4000. 2020-04-24 17:36:01,219-INFO: Test iter 0 2020-04-24 17:36:05,835-INFO: Test finish iter 50 2020-04-24 17:36:05,835-INFO: Total number of images: 225, inference time: 47.037228265867356 fps. 2020-04-24 17:36:05,836-INFO: Start evaluate... 2020-04-24 17:36:05,844-INFO: Accumulating evaluatation results... 2020-04-24 17:36:05,844-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:36:05,845-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:36:07,135-INFO: iter: 4020, lr: 0.000050, 'loss': '3.758350', time: 0.581, eta: 2:34:44 2020-04-24 17:36:08,421-INFO: iter: 4040, lr: 0.000050, 'loss': '4.207700', time: 0.064, eta: 0:17:08 2020-04-24 17:36:09,649-INFO: iter: 4060, lr: 0.000050, 'loss': '3.793053', time: 0.061, eta: 0:16:18 2020-04-24 17:36:10,942-INFO: iter: 4080, lr: 0.000050, 'loss': '3.398545', time: 0.064, eta: 0:17:03 2020-04-24 17:36:12,247-INFO: iter: 4100, lr: 0.000050, 'loss': '3.700174', time: 0.065, eta: 0:17:17 2020-04-24 17:36:13,555-INFO: iter: 4120, lr: 0.000050, 'loss': '3.585165', time: 0.065, eta: 0:17:08 2020-04-24 17:36:14,850-INFO: iter: 4140, lr: 0.000050, 'loss': '3.582839', time: 0.066, eta: 0:17:22 2020-04-24 17:36:16,098-INFO: iter: 4160, lr: 0.000050, 'loss': '3.046422', time: 0.062, eta: 0:16:25 2020-04-24 17:36:17,373-INFO: iter: 4180, lr: 0.000050, 'loss': '3.401401', time: 0.064, eta: 0:16:50 2020-04-24 17:36:18,636-INFO: iter: 4200, lr: 0.000050, 'loss': '3.720748', time: 0.063, eta: 0:16:32 2020-04-24 17:36:19,885-INFO: iter: 4220, lr: 0.000050, 'loss': '3.703779', time: 0.063, eta: 0:16:32 2020-04-24 17:36:21,146-INFO: iter: 4240, lr: 0.000050, 'loss': '3.484643', time: 0.063, eta: 0:16:27 2020-04-24 17:36:22,407-INFO: iter: 4260, lr: 0.000050, 'loss': '3.560898', time: 0.063, eta: 0:16:37 2020-04-24 17:36:23,661-INFO: iter: 4280, lr: 0.000050, 'loss': '3.542098', time: 0.063, eta: 0:16:26 2020-04-24 17:36:24,937-INFO: iter: 4300, lr: 0.000050, 'loss': '3.348787', time: 0.064, eta: 0:16:42 2020-04-24 17:36:26,200-INFO: iter: 4320, lr: 0.000050, 'loss': '3.510291', time: 0.063, eta: 0:16:26 2020-04-24 17:36:27,472-INFO: iter: 4340, lr: 0.000050, 'loss': '3.666212', time: 0.064, eta: 0:16:35 2020-04-24 17:36:28,713-INFO: iter: 4360, lr: 0.000050, 'loss': '3.797819', time: 0.062, eta: 0:16:08 2020-04-24 17:36:29,974-INFO: iter: 4380, lr: 0.000050, 'loss': '3.945305', time: 0.063, eta: 0:16:29 2020-04-24 17:36:31,235-INFO: iter: 4400, lr: 0.000050, 'loss': '3.535756', time: 0.063, eta: 0:16:18 2020-04-24 17:36:32,481-INFO: iter: 4420, lr: 0.000050, 'loss': '3.490065', time: 0.063, eta: 0:16:16 2020-04-24 17:36:33,730-INFO: iter: 4440, lr: 0.000050, 'loss': '3.691013', time: 0.062, eta: 0:16:05 2020-04-24 17:36:34,966-INFO: iter: 4460, lr: 0.000050, 'loss': '3.553645', time: 0.062, eta: 0:16:05 2020-04-24 17:36:36,225-INFO: iter: 4480, lr: 0.000050, 'loss': '3.839829', time: 0.063, eta: 0:16:14 2020-04-24 17:36:37,511-INFO: iter: 4500, lr: 0.000050, 'loss': '3.846769', time: 0.064, eta: 0:16:34 2020-04-24 17:36:37,511-INFO: Save model to output/yolov3_darknet_voc/4500. 2020-04-24 17:36:43,267-INFO: Test iter 0 2020-04-24 17:36:47,838-INFO: Test finish iter 50 2020-04-24 17:36:47,838-INFO: Total number of images: 386, inference time: 81.4749819927355 fps. 2020-04-24 17:36:47,838-INFO: Start evaluate... 2020-04-24 17:36:47,858-INFO: Accumulating evaluatation results... 2020-04-24 17:36:47,860-INFO: mAP(0.50, 11point) = 0.07 2020-04-24 17:36:47,860-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:36:49,136-INFO: iter: 4520, lr: 0.000050, 'loss': '3.163689', time: 0.582, eta: 2:30:04 2020-04-24 17:36:50,392-INFO: iter: 4540, lr: 0.000050, 'loss': '3.469370', time: 0.063, eta: 0:16:08 2020-04-24 17:36:51,645-INFO: iter: 4560, lr: 0.000050, 'loss': '3.841788', time: 0.062, eta: 0:16:03 2020-04-24 17:36:52,881-INFO: iter: 4580, lr: 0.000050, 'loss': '3.766765', time: 0.062, eta: 0:15:51 2020-04-24 17:36:54,117-INFO: iter: 4600, lr: 0.000050, 'loss': '3.452003', time: 0.062, eta: 0:15:57 2020-04-24 17:36:55,350-INFO: iter: 4620, lr: 0.000050, 'loss': '3.419397', time: 0.062, eta: 0:15:46 2020-04-24 17:36:56,582-INFO: iter: 4640, lr: 0.000050, 'loss': '3.332407', time: 0.062, eta: 0:15:47 2020-04-24 17:36:57,827-INFO: iter: 4660, lr: 0.000050, 'loss': '3.428831', time: 0.062, eta: 0:15:54 2020-04-24 17:36:59,085-INFO: iter: 4680, lr: 0.000050, 'loss': '4.268382', time: 0.063, eta: 0:16:03 2020-04-24 17:37:00,391-INFO: iter: 4700, lr: 0.000050, 'loss': '3.485666', time: 0.065, eta: 0:16:38 2020-04-24 17:37:01,642-INFO: iter: 4720, lr: 0.000050, 'loss': '3.760272', time: 0.063, eta: 0:15:56 2020-04-24 17:37:02,931-INFO: iter: 4740, lr: 0.000050, 'loss': '3.887499', time: 0.064, eta: 0:16:24 2020-04-24 17:37:04,195-INFO: iter: 4760, lr: 0.000050, 'loss': '3.782166', time: 0.063, eta: 0:16:03 2020-04-24 17:37:05,472-INFO: iter: 4780, lr: 0.000050, 'loss': '3.811396', time: 0.064, eta: 0:16:09 2020-04-24 17:37:06,764-INFO: iter: 4800, lr: 0.000050, 'loss': '3.546153', time: 0.065, eta: 0:16:21 2020-04-24 17:37:08,017-INFO: iter: 4820, lr: 0.000050, 'loss': '3.723100', time: 0.063, eta: 0:15:54 2020-04-24 17:37:09,269-INFO: iter: 4840, lr: 0.000050, 'loss': '3.450723', time: 0.063, eta: 0:15:49 2020-04-24 17:37:10,510-INFO: iter: 4860, lr: 0.000050, 'loss': '3.723860', time: 0.062, eta: 0:15:38 2020-04-24 17:37:11,760-INFO: iter: 4880, lr: 0.000050, 'loss': '3.553896', time: 0.062, eta: 0:15:43 2020-04-24 17:37:13,089-INFO: iter: 4900, lr: 0.000050, 'loss': '3.351804', time: 0.066, eta: 0:16:42 2020-04-24 17:37:14,335-INFO: iter: 4920, lr: 0.000050, 'loss': '3.891120', time: 0.062, eta: 0:15:42 2020-04-24 17:37:15,597-INFO: iter: 4940, lr: 0.000050, 'loss': '3.428214', time: 0.063, eta: 0:15:50 2020-04-24 17:37:16,864-INFO: iter: 4960, lr: 0.000050, 'loss': '3.330782', time: 0.063, eta: 0:15:51 2020-04-24 17:37:18,134-INFO: iter: 4980, lr: 0.000050, 'loss': '3.386735', time: 0.064, eta: 0:15:55 2020-04-24 17:37:19,399-INFO: iter: 5000, lr: 0.000050, 'loss': '3.567228', time: 0.063, eta: 0:15:46 2020-04-24 17:37:19,400-INFO: Save model to output/yolov3_darknet_voc/5000. 2020-04-24 17:37:25,233-INFO: Test iter 0 2020-04-24 17:37:29,840-INFO: Test finish iter 50 2020-04-24 17:37:29,840-INFO: Total number of images: 386, inference time: 81.00914311761852 fps. 2020-04-24 17:37:29,840-INFO: Start evaluate... 2020-04-24 17:37:29,858-INFO: Accumulating evaluatation results... 2020-04-24 17:37:29,859-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:37:29,860-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:37:31,127-INFO: iter: 5020, lr: 0.000050, 'loss': '3.453389', time: 0.586, eta: 2:26:21 2020-04-24 17:37:32,479-INFO: iter: 5040, lr: 0.000050, 'loss': '3.389300', time: 0.068, eta: 0:16:51 2020-04-24 17:37:33,755-INFO: iter: 5060, lr: 0.000050, 'loss': '3.250560', time: 0.064, eta: 0:15:58 2020-04-24 17:37:35,034-INFO: iter: 5080, lr: 0.000050, 'loss': '3.315282', time: 0.064, eta: 0:15:54 2020-04-24 17:37:36,322-INFO: iter: 5100, lr: 0.000050, 'loss': '3.260192', time: 0.064, eta: 0:15:58 2020-04-24 17:37:37,625-INFO: iter: 5120, lr: 0.000050, 'loss': '3.638357', time: 0.065, eta: 0:16:01 2020-04-24 17:37:38,903-INFO: iter: 5140, lr: 0.000050, 'loss': '3.509134', time: 0.064, eta: 0:15:55 2020-04-24 17:37:40,153-INFO: iter: 5160, lr: 0.000050, 'loss': '3.396525', time: 0.063, eta: 0:15:30 2020-04-24 17:37:41,425-INFO: iter: 5180, lr: 0.000050, 'loss': '3.273350', time: 0.063, eta: 0:15:39 2020-04-24 17:37:42,682-INFO: iter: 5200, lr: 0.000050, 'loss': '3.643520', time: 0.063, eta: 0:15:29 2020-04-24 17:37:43,907-INFO: iter: 5220, lr: 0.000050, 'loss': '3.876294', time: 0.062, eta: 0:15:09 2020-04-24 17:37:45,138-INFO: iter: 5240, lr: 0.000050, 'loss': '3.493153', time: 0.062, eta: 0:15:08 2020-04-24 17:37:46,399-INFO: iter: 5260, lr: 0.000050, 'loss': '3.738557', time: 0.063, eta: 0:15:24 2020-04-24 17:37:47,682-INFO: iter: 5280, lr: 0.000050, 'loss': '3.554138', time: 0.064, eta: 0:15:46 2020-04-24 17:37:48,965-INFO: iter: 5300, lr: 0.000050, 'loss': '3.810281', time: 0.064, eta: 0:15:44 2020-04-24 17:37:50,225-INFO: iter: 5320, lr: 0.000050, 'loss': '3.253931', time: 0.063, eta: 0:15:24 2020-04-24 17:37:51,519-INFO: iter: 5340, lr: 0.000050, 'loss': '3.243005', time: 0.065, eta: 0:15:47 2020-04-24 17:37:52,781-INFO: iter: 5360, lr: 0.000050, 'loss': '3.515703', time: 0.063, eta: 0:15:25 2020-04-24 17:37:54,046-INFO: iter: 5380, lr: 0.000050, 'loss': '3.450956', time: 0.063, eta: 0:15:24 2020-04-24 17:37:55,287-INFO: iter: 5400, lr: 0.000050, 'loss': '3.525292', time: 0.062, eta: 0:15:04 2020-04-24 17:37:56,559-INFO: iter: 5420, lr: 0.000050, 'loss': '3.550826', time: 0.063, eta: 0:15:24 2020-04-24 17:37:57,841-INFO: iter: 5440, lr: 0.000050, 'loss': '3.331095', time: 0.064, eta: 0:15:37 2020-04-24 17:37:59,113-INFO: iter: 5460, lr: 0.000050, 'loss': '3.410345', time: 0.064, eta: 0:15:23 2020-04-24 17:38:00,377-INFO: iter: 5480, lr: 0.000050, 'loss': '3.535499', time: 0.063, eta: 0:15:15 2020-04-24 17:38:01,660-INFO: iter: 5500, lr: 0.000050, 'loss': '3.143191', time: 0.064, eta: 0:15:32 2020-04-24 17:38:01,660-INFO: Save model to output/yolov3_darknet_voc/5500. 2020-04-24 17:38:07,517-INFO: Test iter 0 2020-04-24 17:38:12,136-INFO: Test finish iter 50 2020-04-24 17:38:12,137-INFO: Total number of images: 365, inference time: 76.25575758203671 fps. 2020-04-24 17:38:12,137-INFO: Start evaluate... 2020-04-24 17:38:12,152-INFO: Accumulating evaluatation results... 2020-04-24 17:38:12,153-INFO: mAP(0.50, 11point) = 0.00 2020-04-24 17:38:12,153-INFO: Best test box ap: 1.7039429287573509, in iter: 1000 2020-04-24 17:38:13,401-INFO: iter: 5520, lr: 0.000050, 'loss': '3.344422', time: 0.587, eta: 2:21:41 2020-04-24 17:38:14,639-INFO: iter: 5540, lr: 0.000050, 'loss': '3.501547', time: 0.062, eta: 0:14:55 2020-04-24 17:38:15,904-INFO: iter: 5560, lr: 0.000050, 'loss': '3.503700', time: 0.063, eta: 0:15:07 2020-04-24 17:38:17,194-INFO: iter: 5580, lr: 0.000050, 'loss': '3.501959', time: 0.065, eta: 0:15:31 2020-04-24 17:38:18,445-INFO: iter: 5600, lr: 0.000050, 'loss': '3.417392', time: 0.063, eta: 0:15:02 2020-04-24 17:38:19,735-INFO: iter: 5620, lr: 0.000050, 'loss': '3.444615', time: 0.064, eta: 0:15:26 2020-04-24 17:38:21,052-INFO: iter: 5640, lr: 0.000050, 'loss': '3.577362', time: 0.066, eta: 0:15:45 2020-04-24 17:38:22,329-INFO: iter: 5660, lr: 0.000050, 'loss': '3.356668', time: 0.064, eta: 0:15:18 2020-04-24 17:38:23,619-INFO: iter: 5680, lr: 0.000050, 'loss': '3.073082', time: 0.064, eta: 0:15:23 2020-04-24 17:38:24,876-INFO: iter: 5700, lr: 0.000050, 'loss': '3.488874', time: 0.063, eta: 0:14:59 2020-04-24 17:38:26,168-INFO: iter: 5720, lr: 0.000050, 'loss': '3.532371', time: 0.065, eta: 0:15:22 2020-04-24 17:38:27,429-INFO: iter: 5740, lr: 0.000050, 'loss': '3.542585', time: 0.063, eta: 0:14:57 2020-04-24 17:38:28,711-INFO: iter: 5760, lr: 0.000050, 'loss': '3.143624', time: 0.064, eta: 0:15:15 2020-04-24 17:38:29,976-INFO: iter: 5780, lr: 0.000050, 'loss': '3.738636', time: 0.063, eta: 0:14:58 2020-04-24 17:38:31,253-INFO: iter: 5800, lr: 0.000050, 'loss': '3.627708', time: 0.064, eta: 0:15:06 2020-04-24 17:38:32,551-INFO: iter: 5820, lr: 0.000050, 'loss': '3.114335', time: 0.065, eta: 0:15:18 2020-04-24 17:38:33,854-INFO: iter: 5840, lr: 0.000050, 'loss': '3.489221', time: 0.065, eta: 0:15:24 2020-04-24 17:38:35,128-INFO: iter: 5860, lr: 0.000050, 'loss': '3.341849', time: 0.064, eta: 0:15:00 2020-04-24 17:38:36,400-INFO: iter: 5880, lr: 0.000050, 'loss': '3.928839', time: 0.064, eta: 0:14:59 2020-04-24 17:38:37,701-INFO: iter: 5900, lr: 0.000050, 'loss': '3.130453', time: 0.065, eta: 0:15:16 2020-04-24 17:38:38,956-INFO: iter: 5920, lr: 0.000050, 'loss': '4.121333', time: 0.063, eta: 0:14:44 2020-04-24 17:38:40,236-INFO: iter: 5940, lr: 0.000050, 'loss': '3.682073', time: 0.064, eta: 0:14: