BookRecogntionKZ / models /best_norm_ED.yaml
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number: '0123456789'
symbol: "!?.,:;'#()<>+-/*=%$»« "
lang_char: 'АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯЁабвгдежзийклмнопрстуфхцчшщъыьэюяёӘҒҚҢӨҰҮІҺәғқңөұүіһABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz'
experiment_name: 'kz_synthtiger_v7'
train_data: '../../synthtiger_kz/results/train_v7'
valid_data: '../../synthtiger_kz/results/test_v7'
manualSeed: 1111
workers: 6
batch_size: 96 #32
num_iter: 100000
valInterval: 1000
saved_model: '' #'saved_models/en_filtered/iter_300000.pth'
FT: False
optim: False # default is Adadelta
lr: 1.
beta1: 0.9
rho: 0.95
eps: 0.00000001
grad_clip: 5
#Data processing
select_data: 'images' # this is dataset folder in train_data
batch_ratio: '1'
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 64
imgW: 600
rgb: False
sensitive: True
PAD: True
contrast_adjust: 0.0
data_filtering_off: False
# Model Architecture
Transformation: 'None'
FeatureExtraction: 'VGG'
SequenceModeling: 'BiLSTM'
Prediction: 'CTC'
num_fiducial: 20
input_channel: 1
output_channel: 256
hidden_size: 256
decode: 'greedy'
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
network_params:
input_channel: 1
output_channel: 256
hidden_size: 256
lang_list:
- 'en'
character_list: 0123456789!?.,:;'#()<>+-/*=%$»« АБВГДЕЖЗИЙКЛМНОПРСТУФХЦЧШЩЪЫЬЭЮЯЁабвгдежзийклмнопрстуфхцчшщъыьэюяёӘҒҚҢӨҰҮІҺәғқңөұүіһABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz