yolov3_r34.yml 1.6 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
architecture: YOLOv3
train_feed: YoloTrainFeed
eval_feed: YoloEvalFeed
test_feed: YoloTestFeed
use_gpu: yes
max_iters: 500200
log_smooth_window: 20
save_dir: output
snapshot_iter: 2000
metric: COCO
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/ResNet34_pretrained.tar
weights: https://paddlemodels.bj.bcebos.com/yolo/yolo_resnet34.tar.gz

YOLOv3:
  backbone: ResNet
  yolo_head: YOLOv3Head

ResNet:
  norm_type: sync_bn
K
Kaipeng Deng 已提交
20 21
  freeze_at: 0
  freeze_norm: False
22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65
  norm_decay: 0.
  depth: 34
  feature_maps: [3, 4, 5]

YOLOv3Head:
  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]]
  norm_decay: 0.
  ignore_thresh: 0.7
  label_smooth: true
  nms:
    background_label: -1
    keep_top_k: 100
    nms_threshold: 0.45
    nms_top_k: 1000
    normalized: false
    score_threshold: 0.01
  num_classes: 80

LearningRate:
  base_lr: 0.001
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones:
    - 400000
    - 450000
  - !LinearWarmup
    start_factor: 0.
    steps: 4000

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

YoloTrainFeed:
  batch_size: 8
  dataset:
66
    dataset_dir: dataset/coco
67 68 69 70 71 72 73 74 75
    annotation: annotations/instances_train2017.json
    image_dir: train2017
  num_workers: 8
  bufsize: 128
  use_process: true

YoloEvalFeed:
  batch_size: 8
  dataset:
76
    dataset_dir: dataset/coco
77 78 79 80 81 82 83
    annotation: annotations/instances_val2017.json
    image_dir: val2017

YoloTestFeed:
  batch_size: 1
  dataset:
    annotation: annotations/instances_val2017.json