add multi language config file imgs and dict

This commit is contained in:
xmy0916 2021-01-19 15:52:04 +08:00
parent 47eb591f9e
commit 141d50d670
59 changed files with 11267 additions and 0 deletions

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import yaml
from argparse import ArgumentParser, RawDescriptionHelpFormatter
support_list = {
'it':'italian', 'xi':'spanish', 'pu':'portuguese', 'ru':'russian', 'ar':'arabic',
'ta':'tamil', 'ug':'uyghur', 'fa':'persian', 'ur':'urdu', 'rs':'serbian latin',
'oc':'occitan', 'rsc':'serbian cyrillic', 'bg':'bulgarian', 'uk':'ukranian', 'be':'belarusian',
'te':'telugu', 'ka':'kannada', 'chinese_cht':'chinese tradition','hi':'hindi','mr':'marathi',
'ne':'nepali',
}
global_config = yaml.load(open("./rec_multi_language_lite_train.yml", 'rb'), Loader=yaml.Loader)
class ArgsParser(ArgumentParser):
def __init__(self):
super(ArgsParser, self).__init__(
formatter_class=RawDescriptionHelpFormatter)
self.add_argument(
"-o", "--opt", nargs='+', help="set configuration options")
self.add_argument(
"-t", "--type", nargs='+', help="set language type, support {}".format(support_list))
self.add_argument(
"--train",type=str,help="you can use this command to change the default path")
self.add_argument(
"--val",type=str,help="you can use this command to change the default path")
self.add_argument(
"--dict",type=str,help="you can use this command to change the default path")
def parse_args(self, argv=None):
args = super(ArgsParser, self).parse_args(argv)
args.opt = self._parse_opt(args.opt)
args.type,args.config = self._set_language(args.type)
return args
def _parse_opt(self, opts):
config = {}
if not opts:
return config
for s in opts:
s = s.strip()
k, v = s.split('=')
config[k] = yaml.load(v, Loader=yaml.Loader)
return config
def _set_language(self, type):
config={
'Global':{'character_dict_path':None,'save_model_dir':None},
'Train':{'dataset':{'label_file_list':None}},
'Eval': {'dataset': {'label_file_list': None}},
}
assert(type),"please use -t or --type to choose language type"
assert(
type[0] in support_list.keys()
),"the sub_keys(-t or --type) can only be one of support list: \n{},\nbut get: {}, " \
"please check your running command".format(support_list, type)
config['Global']['character_dict_path'] = 'ppocr/utils/dict/{}_dict.txt'.format(type[0])
config['Global']['save_model_dir'] = './output/rec_{}_lite'.format(type[0])
config['Train']['dataset']['label_file_list'] = ["./train_data/{}_train.txt".format(type[0])]
config['Eval']['dataset']['label_file_list'] = ["./train_data/{}_val.txt".format(type[0])]
return type[0],config
def merge_config(global_config,new_config):
"""
Merge config into global config.
Args:
global_config: Source config
new_config (dict): Config to be merged.
Returns: global config
"""
for key, value in new_config.items():
if "." not in key:
if isinstance(value, dict) and key in global_config:
global_config[key].update(value)
else:
global_config[key] = value
else:
sub_keys = key.split('.')
assert (
sub_keys[0] in global_config
), "the sub_keys can only be one of global_config: {}, but get: {}, " \
"please check your running command".format(
global_config.keys(), sub_keys[0])
cur = global_config[sub_keys[0]]
for idx, sub_key in enumerate(sub_keys[1:]):
if idx == len(sub_keys) - 2:
cur[sub_key] = value
else:
cur = cur[sub_key]
return global_config
if __name__ == '__main__':
FLAGS = ArgsParser().parse_args()
global_config = merge_config(global_config,FLAGS.opt)
global_config = merge_config(global_config, FLAGS.config)
if FLAGS.train:
global_config['Train']['dataset']['label_file_list'] = [FLAGS.train]
if FLAGS.val:
global_config['Eval']['dataset']['label_file_list'] = [FLAGS.val]
if FLAGS.dict:
global_config['Global']['character_dict_path'] = FLAGS.dict
print("train list path set to:{}".format(global_config['Train']['dataset']['label_file_list'][0]))
print("Eval list path set to :{}".format(global_config['Eval']['dataset']['label_file_list'][0]))
print("dict path set to :{}".format(global_config['Global']['character_dict_path']))
with open('rec_{}_lite_train.yml'.format(FLAGS.type), 'w') as f:
yaml.dump(dict(global_config), f, default_flow_style=False, sort_keys=False)
print("config file set to :configs/rec/multi_language/rec_{}_lite_train.yml".format(FLAGS.type))

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Global:
use_gpu: True
epoch_num: 500
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/rec_multi_language_lite
save_epoch_step: 3
# evaluation is run every 5000 iterations after the 4000th iteration
eval_batch_step: [0, 2000]
# if pretrained_model is saved in static mode, load_static_weights must set to True
cal_metric_during_train: True
pretrained_model:
checkpoints:
save_inference_dir:
use_visualdl: False
infer_img:
# for data or label process
character_dict_path:
# Set the language of training, if set, select the default dictionary file
character_type:
max_text_length: 25
infer_mode: False
use_space_char: True
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: Cosine
learning_rate: 0.001
regularizer:
name: 'L2'
factor: 0.00001
Architecture:
model_type: rec
algorithm: CRNN
Transform:
Backbone:
name: MobileNetV3
scale: 0.5
model_name: small
small_stride: [1, 2, 2, 2]
Neck:
name: SequenceEncoder
encoder_type: rnn
hidden_size: 48
Head:
name: CTCHead
fc_decay: 0.00001
Loss:
name: CTCLoss
PostProcess:
name: CTCLabelDecode
Metric:
name: RecMetric
main_indicator: acc
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
label_file_list: ["./train_data/train_list.txt"]
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
- RecAug:
- CTCLabelEncode: # Class handling label
- RecResizeImg:
image_shape: [3, 32, 320]
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: True
batch_size_per_card: 256
drop_last: True
num_workers: 8
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
label_file_list: ["./train_data/val_list.txt"]
transforms:
- DecodeImage: # load image
img_mode: BGR
channel_first: False
- CTCLabelEncode: # Class handling label
- RecResizeImg:
image_shape: [3, 32, 320]
- KeepKeys:
keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order
loader:
shuffle: False
drop_last: False
batch_size_per_card: 256
num_workers: 8

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