Created by: dklinzh

环境:

• PaddlePaddle 1.8.4.post107
• PaddleDetection release/0.4 9e388947
• GPU单卡8G, 内存32G
• Python 3.7.3

错误日志:

2020-08-27 22:15:53,972-INFO: Save model to ../PaddleDetection_Output/model/ppyolo_r18vd_plate/T0/ppyolo_r18vd_plate/model_final. 2020-08-27 22:15:54,901-INFO: Test iter 0 2020-08-27 22:15:56,121-INFO: Test finish iter 26 2020-08-27 22:15:56,121-INFO: Total number of images: 202, inference time: 157.2117341547254 fps. 2020-08-27 22:15:56,121-INFO: Start evaluate... 2020-08-27 22:15:56,144-INFO: Accumulating evaluatation results... 2020-08-27 22:15:56,145-INFO: mAP(0.50, 11point) = 99.13 2020-08-27 22:15:56,145-INFO: Best test box ap: 99.23065809434371, in iter: 25000 terminate called without an active exception W0827 22:15:56.547019 3768 init.cc:226] Warning: PaddlePaddle catches a failure signal, it may not work properly W0827 22:15:56.547036 3768 init.cc:228] You could check whether you killed PaddlePaddle thread/process accidentally or report the case to PaddlePaddle W0827 22:15:56.547042 3768 init.cc:231] The detail failure signal is:

W0827 22:15:56.547049 3768 init.cc:234] *** Aborted at 1598537756 (unix time) try "date -d @1598537756" if you are using GNU date *** W0827 22:15:56.548934 3768 init.cc:234] PC: @ 0x0 (unknown) W0827 22:15:56.548995 3768 init.cc:234] *** SIGABRT (@0x3e800000aff) received by PID 2815 (TID 0x7f9e4d7fe700) from PID 2815; stack trace: *** W0827 22:15:56.550269 3768 init.cc:234] @ 0x7fa16a0ce730 (unknown) W0827 22:15:56.551038 3768 init.cc:234] @ 0x7fa169d497bb gsignal W0827 22:15:56.551915 3768 init.cc:234] @ 0x7fa169d34535 abort W0827 22:15:56.552793 3768 init.cc:234] @ 0x7fa15205f983 (unknown) W0827 22:15:56.553651 3768 init.cc:234] @ 0x7fa1520658c6 (unknown) W0827 22:15:56.554262 3768 init.cc:234] @ 0x7fa152065901 std::terminate() W0827 22:15:56.554885 3768 init.cc:234] @ 0x7fa152065324 __gxx_personality_v0 W0827 22:15:56.555639 3768 init.cc:234] @ 0x7fa166832f28 (unknown) W0827 22:15:56.556443 3768 init.cc:234] @ 0x7fa16683351c _Unwind_ForcedUnwind W0827 22:15:56.557286 3768 init.cc:234] @ 0x7fa16a0cd0a0 __GI___pthread_unwind W0827 22:15:56.558120 3768 init.cc:234] @ 0x7fa16a0c51f5 __pthread_exit W0827 22:15:56.558395 3768 init.cc:234] @ 0x62e585 PyThread_exit_thread W0827 22:15:56.558507 3768 init.cc:234] @ 0x54e368 PyEval_RestoreThread W0827 22:15:56.559154 3768 init.cc:234] @ 0x7fa1302dd5d5 (unknown) W0827 22:15:56.559283 3768 init.cc:234] @ 0x5d7d54 _PyMethodDef_RawFastCallKeywords W0827 22:15:56.559430 3768 init.cc:234] @ 0x54b780 (unknown) W0827 22:15:56.559494 3768 init.cc:234] @ 0x55286a _PyEval_EvalFrameDefault W0827 22:15:56.559576 3768 init.cc:234] @ 0x54c112 _PyEval_EvalCodeWithName W0827 22:15:56.559655 3768 init.cc:234] @ 0x5d9bbe _PyFunction_FastCallDict W0827 22:15:56.559773 3768 init.cc:234] @ 0x58f07b (unknown) W0827 22:15:56.559850 3768 init.cc:234] @ 0x5d94db _PyObject_FastCallKeywords W0827 22:15:56.559898 3768 init.cc:234] @ 0x552ae8 _PyEval_EvalFrameDefault W0827 22:15:56.559947 3768 init.cc:234] @ 0x5d99f6 _PyFunction_FastCallDict W0827 22:15:56.560061 3768 init.cc:234] @ 0x58f07b (unknown) W0827 22:15:56.560139 3768 init.cc:234] @ 0x5d94db _PyObject_FastCallKeywords W0827 22:15:56.560256 3768 init.cc:234] @ 0x54b811 (unknown) W0827 22:15:56.560314 3768 init.cc:234] @ 0x55286a _PyEval_EvalFrameDefault W0827 22:15:56.560420 3768 init.cc:234] @ 0x54c112 _PyEval_EvalCodeWithName W0827 22:15:56.560487 3768 init.cc:234] @ 0x5d9bbe _PyFunction_FastCallDict W0827 22:15:56.560600 3768 init.cc:234] @ 0x4d9fb2 (unknown) W0827 22:15:56.560714 3768 init.cc:234] @ 0x5dc086 PyObject_Call W0827 22:15:56.560829 3768 init.cc:234] @ 0x6233d6 (unknown) Aborted

使用VOC格式的自定义数据集训练, yml配置如下:

architecture: YOLOv3
use_gpu: true
max_iters: 100000
log_smooth_window: 20
log_iter: 20
snapshot_iter: 1000
metric: VOC
map_type: 11point # integral
pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_r18vd.pdparams
weights: ../PaddleDetection_Output/model/ppyolo_r18vd_plate/T0/ppyolo_r18vd_plate/best_model
save_dir: ../PaddleDetection_Output/model/ppyolo_r18vd_plate/T0
num_classes: 1
use_fine_grained_loss: true
use_ema: true
ema_decay: 0.9998

YOLOv3:
  backbone: ResNet
  yolo_head: YOLOv3Head
  use_fine_grained_loss: true

ResNet:
  norm_type: sync_bn
  freeze_at: 0
  freeze_norm: false
  norm_decay: 0.
  depth: 18
  feature_maps: [4, 5]
  variant: d

YOLOv3Head:
  anchor_masks: [[3, 4, 5], [0, 1, 2]]
  anchors: [[10, 14], [23, 27], [37, 58],
            [81, 82], [135, 169], [344, 319]]
  norm_decay: 0.
  conv_block_num: 0
  scale_x_y: 1.05
  yolo_loss: YOLOv3Loss
  nms: MatrixNMS
  drop_block: true

YOLOv3Loss:
  batch_size: 8
  ignore_thresh: 0.7
  scale_x_y: 1.05
  label_smooth: false
  use_fine_grained_loss: true
  iou_loss: IouLoss

IouLoss:
  loss_weight: 2.5
  max_height: 608
  max_width: 608

MatrixNMS:
    background_label: -1
    keep_top_k: 100
    normalized: false
    score_threshold: 0.01
    post_threshold: 0.01

LearningRate:
  base_lr: 0.00025
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 60000
    - 80000
  - !LinearWarmup
    start_factor: 0.
    steps: 1600

OptimizerBuilder:
  optimizer:
    momentum: 0.9
    type: Momentum
  regularizer:
    factor: 0.0005
    type: L2

_READER_: 'ppyolo_reader.yml'
TrainReader:
  inputs_def:
    fields: ['image', 'gt_bbox', 'gt_class', 'gt_score']
    num_max_boxes: 50
  dataset:
    !VOCDataSet
    dataset_dir: ../PaddleDetection_DataSet/plate_new
    anno_path: train.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
      with_mixup: True
    - !MixupImage
      alpha: 1.5
      beta: 1.5
    - !ColorDistort {}
    - !RandomExpand
      fill_value: [123.675, 116.28, 103.53]
    - !RandomCrop {}
    - !RandomFlipImage
      is_normalized: false
    - !NormalizeBox {}
    - !PadBox
      num_max_boxes: 50
    - !BboxXYXY2XYWH {}
  batch_transforms:
  - !RandomShape
    sizes: [320, 352, 384, 416, 448, 480, 512, 544, 576, 608]
    random_inter: True
  - !NormalizeImage
    mean: [0.485, 0.456, 0.406]
    std: [0.229, 0.224, 0.225]
    is_scale: True
    is_channel_first: false
  - !Permute
    to_bgr: false
    channel_first: True
  # Gt2YoloTarget is only used when use_fine_grained_loss set as true,
  # this operator will be deleted automatically if use_fine_grained_loss
  # is set as false
  - !Gt2YoloTarget
    anchor_masks: [[3, 4, 5], [0, 1, 2]]
    anchors: [[10, 14], [23, 27], [37, 58],
              [81, 82], [135, 169], [344, 319]]
    downsample_ratios: [32, 16]
  batch_size: 8
  shuffle: true
  mixup_epoch: 500
  drop_last: true
  worker_num: 16
  bufsize: 8
  use_process: true

EvalReader:
  inputs_def:
    fields: ['image', 'im_size', 'im_id', 'gt_bbox', 'gt_class', 'is_difficult']
    num_max_boxes: 50
  dataset:
    !VOCDataSet
    dataset_dir: ../PaddleDetection_DataSet/plate_new
    anno_path: val.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 608
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !PadBox
      num_max_boxes: 50
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 8
  drop_empty: false
  worker_num: 8
  bufsize: 4

TestReader:
  inputs_def:
    image_shape: [3, 608, 608]
    fields: ['image', 'im_size', 'im_id']
  dataset:
    !ImageFolder
    anno_path: ../PaddleDetection_DataSet/plate_new/label_list.txt
    use_default_label: false
    with_background: false
  sample_transforms:
    - !DecodeImage
      to_rgb: True
    - !ResizeImage
      target_size: 608
      interp: 2
    - !NormalizeImage
      mean: [0.485, 0.456, 0.406]
      std: [0.229, 0.224, 0.225]
      is_scale: True
      is_channel_first: false
    - !Permute
      to_bgr: false
      channel_first: True
  batch_size: 1