ssd_vgg16_300_voc.yml 3.2 KB
Newer Older
1 2 3 4 5 6 7 8 9 10
architecture: SSD
train_feed: SSDTrainFeed
eval_feed: SSDEvalFeed
test_feed: SSDTestFeed
use_gpu: true
max_iters: 120001
snapshot_iter: 10000
log_smooth_window: 20
log_iter: 20
metric: VOC
11
map_type: 11point
12 13 14 15 16 17 18 19 20 21 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 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/VGG16_caffe_pretrained.tar
save_dir: output
weights: output/ssd_vgg16_300_voc/model_final/
num_classes: 21

SSD:
  backbone: VGG
  multi_box_head: MultiBoxHead
  output_decoder:
    background_label: 0
    keep_top_k: 200
    nms_eta: 1.0
    nms_threshold: 0.45
    nms_top_k: 400
    score_threshold: 0.01

VGG:
  depth: 16
  with_extra_blocks: true
  normalizations: [20., -1, -1, -1, -1, -1]

MultiBoxHead:
  base_size: 300
  aspect_ratios: [[2.], [2., 3.], [2., 3.], [2., 3.], [2.], [2.]]
  min_ratio: 20
  max_ratio: 90
  min_sizes: [30.0, 60.0, 111.0, 162.0, 213.0, 264.0]
  max_sizes: [60.0, 111.0, 162.0, 213.0, 264.0, 315.0]
  steps: [8, 16, 32, 64, 100, 300]
  offset: 0.5
  flip: true
  min_max_aspect_ratios_order: true
  kernel_size: 3
  pad: 1

LearningRate:
  base_lr: 0.001
  schedulers:
  - !PiecewiseDecay
    gamma: 0.1
    milestones: [80000, 100000]

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

SSDTrainFeed:
  batch_size: 8
  dataset:
    dataset_dir: dataset/voc
    annotation: VOCdevkit/VOC_all/ImageSets/Main/train.txt
    image_dir: VOCdevkit/VOC_all/JPEGImages
    use_default_label: true
  image_shape: [3, 300, 300]
  sample_transforms:
  - !DecodeImage
    to_rgb: true
    with_mixup: false
  - !NormalizeBox {}
  - !RandomDistort
    brightness_lower: 0.875
    brightness_upper: 1.125
    is_order: true
  - !ExpandImage
    max_ratio: 4
    mean: [104, 117, 123]
    prob: 0.5
  - !CropImage
    avoid_no_bbox: true
    batch_sampler:
    - [1, 1, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.1, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.3, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.5, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.7, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.9, 0.0]
    - [1, 50, 0.3, 1.0, 0.5, 2.0, 0.0, 1.0]
    satisfy_all: false
  - !ResizeImage
    interp: 1
    target_size: 300
    use_cv2: False
  - !RandomFlipImage
    is_normalized: true
  - !Permute
    to_bgr: false
  - !NormalizeImage
    is_scale: false
    mean: [104, 117, 123]
    std: [1, 1, 1]

SSDEvalFeed:
  batch_size: 32
  dataset:
    dataset_dir: dataset/voc
    annotation: VOCdevkit/VOC_all/ImageSets/Main/val.txt
    image_dir: VOCdevkit/VOC_all/JPEGImages
    use_default_label: true
  drop_last: false
  image_shape: [3, 300, 300]
  sample_transforms:
  - !DecodeImage
    to_rgb: true
    with_mixup: false
  - !NormalizeBox {}
  - !ResizeImage
    interp: 1
    target_size: 300
    use_cv2: false
  - !Permute
    to_bgr: false
  - !NormalizeImage
    is_scale: false
    mean: [104, 117, 123]  
    std: [1, 1, 1]

SSDTestFeed:
  batch_size: 1
  dataset:
    use_default_label: true
  drop_last: false
  image_shape: [3, 300, 300]
  sample_transforms:
  - !DecodeImage
    to_rgb: true
    with_mixup: false
  - !ResizeImage
    interp: 1
    max_size: 0
    target_size: 300
    use_cv2: false
  - !Permute
    to_bgr: false
  - !NormalizeImage
    is_scale: false
    mean: [104, 117, 123]
    std: [1, 1, 1]