4x-tech/easyocr
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

add .gitignore in the alldata directory

Browse Source
This commit is contained in:
haitaoxing
2025-07-21 18:37:41 +08:00
parent c10b0719c7
commit 5343c29e1b
16 changed files with 9860 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files

BIN
trainer/saved_models/4digit/best_accuracy.pth
View File

Binary file not shown.

BIN
trainer/saved_models/4digit/best_accuracy_2507111731.pth Normal file
View File

Binary file not shown.

BIN
trainer/saved_models/4digit/best_norm_ED.pth
View File

Binary file not shown.

135
trainer/saved_models/4digit/log_dataset.txt
View File

@@ -128,3 +128,138 @@ Total_batch_size: 32 = 32
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------
--------------------------------------------------------------------------------
dataset_root: all_data
opt.select_data: ['4digit_train']
opt.batch_ratio: ['1']
--------------------------------------------------------------------------------
dataset_root: all_data dataset: 4digit_train
sub-directory: /4digit_train num samples: 1000
num total samples of 4digit_train: 1000 x 1.0 (total_data_usage_ratio) = 1000
num samples of 4digit_train per batch: 32 x 1.0 (batch_ratio) = 32
--------------------------------------------------------------------------------
Total_batch_size: 32 = 32
--------------------------------------------------------------------------------
dataset_root: all_data/4digit_valid dataset: /
sub-directory: /. num samples: 200
--------------------------------------------------------------------------------

9081
trainer/saved_models/4digit/log_train.txt
View File

File diff suppressed because it is too large Load Diff

414
trainer/saved_models/4digit/opt.txt
View File

@@ -90,3 +90,417 @@ freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model:
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model: saved_models/4digit/best_accuracy.pth
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model: saved_models/4digit/best_accuracy.pth
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 5
saved_model: saved_models/4digit/best_accuracy.pth
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------
------------ Options -------------
number: 0123456789
experiment_name: 4digit
symbol: None
lang_char: None
train_data: all_data
valid_data: all_data/4digit_valid
manualSeed: 1111
workers: 6
batch_size: 32
num_iter: 3000
valInterval: 10
saved_model: saved_models/4digit/best_accuracy.pth
FT: False
optim: False
lr: 1.0
beta1: 0.9
rho: 0.95
eps: 1e-08
grad_clip: 5
select_data: ['4digit_train']
batch_ratio: ['1']
total_data_usage_ratio: 1.0
batch_max_length: 34
imgH: 32
imgW: 128
rgb: True
contrast_adjust: 0.0
sensitive: True
PAD: True
data_filtering_off: False
Transformation: TPS
FeatureExtraction: ResNet
SequenceModeling: BiLSTM
Prediction: CTC
num_fiducial: 20
input_channel: 3
output_channel: 256
hidden_size: 256
decode: greedy
new_prediction: False
freeze_FeatureFxtraction: False
freeze_SequenceModeling: False
character: 0123456789
num_class: 11
---------------------------------------