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class Config:
FeatureExtraction = 'HRNet' # or any other feature extraction method
SequenceModeling = 'DBiLSTM' # or any other sequential model
Prediction = 'CTC' # or 'Attn'
input_channel = 1 # e.g., RGB image has 3 channels
output_channel = 32 # Adjust based on your architecture
hidden_size = 256 # Adjust based on your architecture
num_class = 182 # Number of output classes
device = 'cpu' # or 'cuda' for GPU
batch_max_length = 8 # Maximum sequence length for prediction
# Adam optimizer
adam = False
lr = 0.1
batch_size = 4
beta1 = 0.9
workers = 4
num_epochs = 5
rho = 0.95
eps = 1e-8
imgH = 32
imgW = 400
train_data = 'result/train/' # path to train data
valid_data = 'result/validate/' # path to validation data
saved_model = 'model/'
character =''
rgb = False
grad_clip = 5
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