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

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
--------------------------------------------------------------------------------