eval with alphanumeric and case sensitive setting
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11
test.py
11
test.py
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@ -2,6 +2,7 @@ import os
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import time
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import time
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import string
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import string
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import argparse
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import argparse
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import re
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import torch
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import torch
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import torch.backends.cudnn as cudnn
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import torch.backends.cudnn as cudnn
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@ -133,6 +134,14 @@ def validation(model, criterion, evaluation_loader, converter, opt):
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pred = pred[:pred_EOS] # prune after "end of sentence" token ([s])
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pred = pred[:pred_EOS] # prune after "end of sentence" token ([s])
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pred_max_prob = pred_max_prob[:pred_EOS]
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pred_max_prob = pred_max_prob[:pred_EOS]
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# To evaluate the model with 'alphanumeric and case insensitve setting'
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if opt.sensitive and opt.data_filtering_off:
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pred = pred.lower()
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gt = gt.lower()
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alphanumeric_case_insensitve = '0123456789abcdefghijklmnopqrstuvwxyz'
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out_of_alphanumeric_case_insensitve = f'[^{alphanumeric_case_insensitve}]'
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pred = re.sub(out_of_alphanumeric_case_insensitve, '', pred)
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if pred == gt:
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if pred == gt:
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n_correct += 1
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n_correct += 1
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@ -146,7 +155,7 @@ def validation(model, criterion, evaluation_loader, converter, opt):
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'''
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'''
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# ICDAR2019 Normalized Edit Distance
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# ICDAR2019 Normalized Edit Distance
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if len(gt) == 0 or len(pred) ==0:
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if len(gt) == 0 or len(pred) == 0:
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norm_ED += 0
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norm_ED += 0
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elif len(gt) > len(pred):
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elif len(gt) > len(pred):
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norm_ED += 1 - edit_distance(pred, gt) / len(gt)
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norm_ED += 1 - edit_distance(pred, gt) / len(gt)
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