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ssd_cbr50_300_voc.yml
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ssd_cbr50_300_voc.yml
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architecture: SSD
use_gpu: true
max_iters: 150001
snapshot_iter: 10000
log_smooth_window: 20
log_iter: 20
metric: VOC
map_type: 11point
pretrain_weights: https://paddle-imagenet-models-name.bj.bcebos.com/CBResNet50_vd_pretrained.tar
save_dir: output
weights: output/ssd_vgg16_300_voc/model_final
# 20(label_class) + 1(background)
num_classes: 21
SSD:
backbone: CBResNet
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
CBResNet:
norm_type: bn
norm_decay: 0.
depth: 50
feature_maps: [2, 3, 4, 5]
freeze_at: 2
variant: d
repeat_num: 2
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: [110000, 130000]
- !LinearWarmup
start_factor: 0.
steps: 1000
OptimizerBuilder:
optimizer:
momentum: 0.9
type: Momentum
regularizer:
factor: 0.0005
type: L2
TrainReader:
inputs_def:
image_shape: [3, 300, 300]
fields: ['image', 'gt_bbox', 'gt_class']
dataset:
!VOCDataSet
dataset_dir: dataset/voc/pascalvoc
anno_path: trainval.txt
use_default_label: true
sample_transforms:
- !DecodeImage
to_rgb: true
- !RandomDistort
brightness_lower: 0.875
brightness_upper: 1.125
is_order: true
- !RandomExpand
fill_value: [104, 117, 123]
- !RandomCrop
allow_no_crop: true
- !NormalizeBox {}
- !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]
batch_size: 16
shuffle: true
worker_num: 8
bufsize: 16
use_process: true
EvalReader:
inputs_def:
image_shape: [3, 300, 300]
fields: ['image', 'gt_bbox', 'gt_class', 'im_shape', 'im_id', 'is_difficult']
dataset:
!VOCDataSet
anno_path: test.txt
dataset_dir: dataset/voc/pascalvoc
use_default_label: true
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]
batch_size: 32
worker_num: 8
bufsize: 16
TestReader:
inputs_def:
image_shape: [3,300,300]
fields: ['image', 'im_id', 'im_shape']
dataset:
!ImageFolder
anno_path: test.txt
use_default_label: true
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]
batch_size: 1