提交 5f3558c9 编写于 作者: L LDOUBLEV

restore yml file

上级 5c26d2e8
...@@ -76,12 +76,14 @@ Train: ...@@ -76,12 +76,14 @@ Train:
- { 'type': Fliplr, 'args': { 'p': 0.5 } } - { 'type': Fliplr, 'args': { 'p': 0.5 } }
- { 'type': Affine, 'args': { 'rotate': [-10, 10] } } - { 'type': Affine, 'args': { 'rotate': [-10, 10] } }
- { 'type': Resize, 'args': { 'size': [0.5, 3] } } - { 'type': Resize, 'args': { 'size': [0.5, 3] } }
- Resize: - EastRandomCropData:
size: [640, 640] size: [640, 640]
# - EastRandomCropData: max_tries: 50
# size: [640, 640] keep_ratio: true
# max_tries: 50 - EastRandomCropData:
# keep_ratio: true size: [640, 640]
max_tries: 50
keep_ratio: true
- MakeBorderMap: - MakeBorderMap:
shrink_ratio: 0.4 shrink_ratio: 0.4
thresh_min: 0.3 thresh_min: 0.3
......
Global:
use_gpu: true
epoch_num: 5
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/db_mv3/
save_epoch_step: 1200
# evaluation is run every 2000 iterations
eval_batch_step: [0, 2000]
cal_metric_during_train: False
pretrained_model: ./pretrain_models/MobileNetV3_large_x0_5_pretrained
checkpoints:
save_inference_dir:
use_visualdl: False
infer_img: doc/imgs_en/img_10.jpg
save_res_path: ./output/det_db/predicts_db.txt
Architecture:
model_type: det
algorithm: DB
Transform:
Backbone:
name: MobileNetV3
scale: 0.5
model_name: large
Neck:
name: DBFPN
out_channels: 256
Head:
name: DBHead
k: 50
Loss:
name: DBLoss
balance_loss: true
main_loss_type: DiceLoss
alpha: 5
beta: 10
ohem_ratio: 3
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
learning_rate: 0.001
regularizer:
name: 'L2'
factor: 0
PostProcess:
name: DBPostProcess
thresh: 0.3
box_thresh: 0.6
max_candidates: 1000
unclip_ratio: 1.5
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
# - IaaAugment:
# augmenter_args:
# - { 'type': Fliplr, 'args': { 'p': 0.5 } }
# - { 'type': Affine, 'args': { 'rotate': [-10, 10] } }
# - { 'type': Resize, 'args': { 'size': [0.5, 3] } }
- Resize:
size: [640, 640]
- MakeBorderMap:
shrink_ratio: 0.4
thresh_min: 0.3
thresh_max: 0.7
- MakeShrinkMap:
shrink_ratio: 0.4
min_text_size: 8
- 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', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list
loader:
shuffle: False
drop_last: False
batch_size_per_card: 1
num_workers: 0
use_shared_memory: False
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:
image_shape: [736, 1280]
- 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: 8
use_shared_memory: False
...@@ -75,12 +75,14 @@ Train: ...@@ -75,12 +75,14 @@ Train:
- { 'type': Fliplr, 'args': { 'p': 0.5 } } - { 'type': Fliplr, 'args': { 'p': 0.5 } }
- { 'type': Affine, 'args': { 'rotate': [-10, 10] } } - { 'type': Affine, 'args': { 'rotate': [-10, 10] } }
- { 'type': Resize, 'args': { 'size': [0.5, 3] } } - { 'type': Resize, 'args': { 'size': [0.5, 3] } }
- Resize: - EastRandomCropData:
size: [640, 640] size: [640, 640]
# - EastRandomCropData: max_tries: 50
# size: [640, 640] keep_ratio: true
# max_tries: 50 - EastRandomCropData:
# keep_ratio: true size: [640, 640]
max_tries: 50
keep_ratio: true
- MakeBorderMap: - MakeBorderMap:
shrink_ratio: 0.4 shrink_ratio: 0.4
thresh_min: 0.3 thresh_min: 0.3
...@@ -97,7 +99,7 @@ Train: ...@@ -97,7 +99,7 @@ Train:
- KeepKeys: - KeepKeys:
keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list keep_keys: ['image', 'threshold_map', 'threshold_mask', 'shrink_map', 'shrink_mask'] # the order of the dataloader list
loader: loader:
shuffle: False shuffle: True
drop_last: False drop_last: False
batch_size_per_card: 4 batch_size_per_card: 4
num_workers: 2 num_workers: 2
......
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