113 lines
2.8 KiB
YAML
113 lines
2.8 KiB
YAML
Global:
|
|
use_gpu: true
|
|
epoch_num: 10000
|
|
log_smooth_window: 20
|
|
print_batch_step: 2
|
|
save_model_dir: ./output/east_r50_vd/
|
|
save_epoch_step: 1000
|
|
# evaluation is run every 5000 iterations after the 4000th iteration
|
|
eval_batch_step: [4000, 5000]
|
|
# 1. If pretrained_model is saved in static mode, such as classification pretrained model
|
|
# from static branch, load_static_weights must be set as True.
|
|
# 2. If you want to finetune the pretrained models we provide in the docs,
|
|
# you should set load_static_weights as False.
|
|
load_static_weights: True
|
|
cal_metric_during_train: False
|
|
pretrained_model: ./pretrain_models/ResNet50_vd_pretrained/
|
|
checkpoints:
|
|
save_inference_dir:
|
|
use_visualdl: False
|
|
infer_img:
|
|
save_res_path: ./output/det_east/predicts_east.txt
|
|
|
|
Architecture:
|
|
model_type: det
|
|
algorithm: EAST
|
|
Transform:
|
|
Backbone:
|
|
name: ResNet
|
|
layers: 50
|
|
Neck:
|
|
name: EASTFPN
|
|
model_name: large
|
|
Head:
|
|
name: EASTHead
|
|
model_name: large
|
|
|
|
Loss:
|
|
name: EASTLoss
|
|
|
|
Optimizer:
|
|
name: Adam
|
|
beta1: 0.9
|
|
beta2: 0.999
|
|
lr:
|
|
# name: Cosine
|
|
learning_rate: 0.001
|
|
# warmup_epoch: 0
|
|
regularizer:
|
|
name: 'L2'
|
|
factor: 0
|
|
|
|
PostProcess:
|
|
name: EASTPostProcess
|
|
score_thresh: 0.8
|
|
cover_thresh: 0.1
|
|
nms_thresh: 0.2
|
|
|
|
Metric:
|
|
name: DetMetric
|
|
main_indicator: hmean
|
|
|
|
Train:
|
|
dataset:
|
|
name: SimpleDataSet
|
|
data_dir: ./train_data/icdar2015/text_localization/
|
|
label_file_list:
|
|
- ./train_data/icdar2015/text_localization/train_icdar2015_label.txt
|
|
ratio_list: [1.0]
|
|
transforms:
|
|
- DecodeImage: # load image
|
|
img_mode: BGR
|
|
channel_first: False
|
|
- DetLabelEncode: # Class handling label
|
|
- EASTProcessTrain:
|
|
image_shape: [512, 512]
|
|
background_ratio: 0.125
|
|
min_crop_side_ratio: 0.1
|
|
min_text_size: 10
|
|
- KeepKeys:
|
|
keep_keys: ['image', 'score_map', 'geo_map', 'training_mask'] # dataloader will return list in this order
|
|
loader:
|
|
shuffle: True
|
|
drop_last: False
|
|
batch_size_per_card: 8
|
|
num_workers: 8
|
|
|
|
Eval:
|
|
dataset:
|
|
name: SimpleDataSet
|
|
data_dir: ./train_data/icdar2015/text_localization/
|
|
label_file_list:
|
|
- ./train_data/icdar2015/text_localization/test_icdar2015_label.txt
|
|
transforms:
|
|
- DecodeImage: # load image
|
|
img_mode: BGR
|
|
channel_first: False
|
|
- DetLabelEncode: # Class handling label
|
|
- DetResizeForTest:
|
|
limit_side_len: 2400
|
|
limit_type: max
|
|
- NormalizeImage:
|
|
scale: 1./255.
|
|
mean: [0.485, 0.456, 0.406]
|
|
std: [0.229, 0.224, 0.225]
|
|
order: 'hwc'
|
|
- ToCHWImage:
|
|
- KeepKeys:
|
|
keep_keys: ['image', 'shape', 'polys', 'ignore_tags']
|
|
loader:
|
|
shuffle: False
|
|
drop_last: False
|
|
batch_size_per_card: 1 # must be 1
|
|
num_workers: 2 |