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svtr_tiny_ch.yaml
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svtr_tiny_ch.yaml
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system:
mode: 0 # 0 for graph mode, 1 for pynative mode in MindSpore
distribute: True
amp_level: O2
amp_level_infer: O2 # running inference in O2 mode
seed: 42
log_interval: 100
val_while_train: True
drop_overflow_update: False
ckpt_max_keep: 5
common:
character_dict_path: &character_dict_path mindocr/utils/dict/ch_dict.txt
num_classes: &num_classes 6624 # num_chars_in_dict + 1
max_text_len: &max_text_len 40
use_space_char: &use_space_char False
batch_size: &batch_size 256
model:
type: rec
transform: null
backbone:
name: SVTRNet
pretrained: False
img_size: [32, 320]
out_channels: 96
patch_merging: Conv
embed_dim: [64, 128, 256]
depth: [3, 6, 3]
num_heads: [2, 4, 8]
mixer:
[
"Local",
"Local",
"Local",
"Local",
"Local",
"Local",
"Global",
"Global",
"Global",
"Global",
"Global",
"Global",
]
local_mixer: [[7, 11], [7, 11], [7, 11]]
last_stage: True
prenorm: False
neck:
name: Img2Seq
head:
name: CTCHead
out_channels: *num_classes
postprocess:
name: RecCTCLabelDecode
character_dict_path: *character_dict_path
use_space_char: *use_space_char
metric:
name: RecMetric
main_indicator: acc
lower: False
character_dict_path: *character_dict_path
ignore_space: True
print_flag: False
loss:
name: CTCLoss
pred_seq_len: 80 # 320 / 4
max_label_len: *max_text_len # this value should be smaller than pre_seq_len
batch_size: *batch_size
scheduler:
scheduler: warmup_cosine_decay
min_lr: 0.00001
lr: 0.001
num_epochs: 60
warmup_epochs: 6
decay_epochs: 54
optimizer:
opt: adamw
grouping_strategy: svtr
filter_bias_and_bn: False
weight_decay: 0.05
loss_scaler:
type: dynamic
loss_scale: 512
scale_factor: 2.0
scale_window: 1000
train:
ckpt_save_dir: ./tmp_rec
dataset_sink_mode: False
clip_grad: True
clip_norm: 0.1
dataset:
type: LMDBDataset
dataset_root: path/to/data_lmdb_release/
data_dir: training/
label_file: null
sample_ratio: 1.0
shuffle: True
filter_max_len: True
max_text_len: *max_text_len
transform_pipeline:
- DecodeImage:
img_mode: BGR
to_float32: False
- RecCTCLabelEncode:
max_text_len: *max_text_len
character_dict_path: *character_dict_path
use_space_char: *use_space_char
lower: False
- Rotate90IfVertical:
threshold: 2.0
direction: counterclockwise
- SVTRRecResizeImg:
image_shape: [32, 320]
padding: True
- NormalizeImage:
bgr_to_rgb: True
is_hwc: True
mean: [127.0, 127.0, 127.0]
std: [127.0, 127.0, 127.0]
- ToCHWImage:
output_columns: ["image", "text_seq"]
net_input_column_index: [0]
label_column_index: [1]
loader:
shuffle: True
batch_size: *batch_size
drop_remainder: True
max_rowsize: 12
num_workers: 1
eval:
ckpt_load_path: ./tmp_rec/best.ckpt
dataset_sink_mode: False
dataset:
type: LMDBDataset
dataset_root: path/to/data_lmdb_release/
data_dir: validation/
label_file: null
sample_ratio: 1.0
shuffle: False
transform_pipeline:
- DecodeImage:
img_mode: BGR
to_float32: False
- RecCTCLabelEncode:
max_text_len: *max_text_len
character_dict_path: *character_dict_path
use_space_char: *use_space_char
lower: False
- Rotate90IfVertical:
threshold: 2.0
direction: counterclockwise
- SVTRRecResizeImg:
image_shape: [32, 320] # H, W
padding: True
- NormalizeImage:
bgr_to_rgb: True
is_hwc: True
mean: [127.0, 127.0, 127.0]
std: [127.0, 127.0, 127.0]
- ToCHWImage:
output_columns: ["image", "text_padded", "text_length"]
net_input_column_index: [0]
label_column_index: [1, 2]
loader:
shuffle: False
batch_size: 64
drop_remainder: False
max_rowsize: 12
num_workers: 1