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faster_rcnn_r50_vd_fpn_roadsign_kunlun.yml
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architecture: FasterRCNN
use_gpu: false
use_xpu: true
max_iters: 2000
log_iter: 1
save_dir: output
snapshot_iter: 500
metric: VOC
pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/faster_rcnn_r50_vd_fpn_2x.tar
weights: output/faster_rcnn_r50_vd_fpn_roadsign_kunlun/model_final
num_classes: 5
finetune_exclude_pretrained_params: ['cls_score, bbox_pred']
FasterRCNN:
backbone: ResNet
fpn: FPN
rpn_head: FPNRPNHead
roi_extractor: FPNRoIAlign
bbox_head: BBoxHead
bbox_assigner: BBoxAssigner
ResNet:
norm_type: affine_channel
depth: 50
feature_maps: [2, 3, 4, 5]
freeze_at: 2
variant: d
ResNetC5:
depth: 50
norm_type: affine_channel
variant: d
FPN:
max_level: 6
min_level: 2
num_chan: 256
spatial_scale: [0.03125, 0.0625, 0.125, 0.25]
FPNRPNHead:
anchor_generator:
anchor_sizes: [32, 64, 128, 256, 512]
aspect_ratios: [0.5, 1.0, 2.0]
stride: [16.0, 16.0]
variance: [1.0, 1.0, 1.0, 1.0]
anchor_start_size: 32
min_level: 2
max_level: 6
num_chan: 256
rpn_target_assign:
rpn_batch_size_per_im: 256
rpn_fg_fraction: 0.5
rpn_negative_overlap: 0.3
rpn_positive_overlap: 0.7
rpn_straddle_thresh: 0.0
use_random: true
train_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 2000
post_nms_top_n: 2000
test_proposal:
min_size: 0.0
nms_thresh: 0.7
pre_nms_top_n: 1000
post_nms_top_n: 1000
FPNRoIAlign:
canconical_level: 4
canonical_size: 224
max_level: 5
min_level: 2
sampling_ratio: 2
box_resolution: 7
mask_resolution: 14
BBoxAssigner:
batch_size_per_im: 512
bbox_reg_weights: [0.1, 0.1, 0.2, 0.2]
bg_thresh_hi: 0.5
bg_thresh_lo: 0.0
fg_fraction: 0.25
fg_thresh: 0.5
BBoxHead:
head: TwoFCHead
nms:
keep_top_k: 100
nms_threshold: 0.5
score_threshold: 0.05
TwoFCHead:
mlp_dim: 1024
LearningRate:
base_lr: 0.0001
schedulers:
- !PiecewiseDecay
gamma: 0.1
milestones:
- 1300
- 1800
- !LinearWarmup
start_factor: 0.3333333333333333
steps: 100
OptimizerBuilder:
optimizer:
momentum: 0.9
type: Momentum
regularizer:
factor: 0.0001
type: L2
TrainReader:
inputs_def:
fields: ['image', 'im_info', 'im_id', 'gt_bbox', 'gt_class', 'is_crowd']
dataset:
!VOCDataSet
dataset_dir: dataset/roadsign_voc
anno_path: train.txt
with_background: true
batch_size: 1
bufsize: 2
shuffle: true
drop_empty: true
drop_last: true
mixup_epoch: -1
use_process: false
worker_num: 2
sample_transforms:
- !DecodeImage
to_rgb: true
- !RandomFlipImage
is_normalized: true
prob: 0.5
- !NormalizeImage
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
is_scale: true
is_channel_first: false
- !ResizeImage
target_size: 800
max_size: 1333
interp: 1
use_cv2: true
- !Permute
channel_first: true
to_bgr: false
batch_transforms:
- !PadBatch
pad_to_stride: 32
use_padded_im_info: false
EvalReader:
batch_size: 1
bufsize: 1
shuffle: false
drop_empty: false
drop_last: false
use_process: false
worker_num: 1
inputs_def:
fields: ['image', 'im_info', 'im_id', 'im_shape', 'gt_bbox', 'gt_class', 'is_difficult']
dataset:
!VOCDataSet
dataset_dir: dataset/roadsign_voc
anno_path: valid.txt
with_background: true
sample_transforms:
- !DecodeImage
to_rgb: true
- !NormalizeImage
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
is_scale: true
is_channel_first: false
- !ResizeImage
target_size: 800
max_size: 1333
interp: 1
use_cv2: true
- !Permute
to_bgr: false
channel_first: true
batch_transforms:
- !PadBatch
pad_to_stride: 32
use_padded_im_info: true
TestReader:
batch_size: 1
drop_empty: false
drop_last: false
inputs_def:
fields: ['image', 'im_info', 'im_id', 'im_shape']
dataset:
!ImageFolder
anno_path: dataset/roadsign_voc/label_list.txt
with_background: true
sample_transforms:
- !DecodeImage
to_rgb: true
with_mixup: false
- !NormalizeImage
mean: [0.485, 0.456, 0.406]
std: [0.229, 0.224, 0.225]
is_scale: true
is_channel_first: false
- !ResizeImage
target_size: 800
max_size: 1333
interp: 1
use_cv2: true
- !Permute
to_bgr: false
channel_first: true
batch_transforms:
- !PadBatch
pad_to_stride: 32
use_padded_im_info: true