nikooooooooooooooooooo
commented
6 months ago 数据集：https://aistudio.baidu.com/datasetdetail/107509
用PPOCRLabel标记了24张图片，如下
1.划分数据集
python PPOCRLabel/gen_ocr_train_val_test.py --trainValTestRatio 6:2:2 --datasetRootPath ./train_data --detRootPath ./train_data/det --recRootPath ./train_data/recLabel.txt
ocr/0000.jpg [{"transcription": "吴运", "points": [[94, 55], [139, 55], [139, 80], [94, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[42, 84], [218, 84], [218, 111], [42, 111]], "difficult": false, "key_cls": "sex"}, {"transcription": "2006年9月11日", "points": [[88, 116], [245, 116], [245, 140], [88, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "广东省广州某某666号—白制数据集", "points": [[91, 150], [279, 150], [279, 193], [91, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "213984748281422633", "points": [[144, 240], [311, 240], [311, 260], [144, 260]], "difficult": false, "key_cls": "card"}] ocr/0001.jpg [{"transcription": "何汊", "points": [[95, 55], [136, 55], [136, 78], [95, 78]], "difficult": false, "key_cls": "name"}, {"transcription": "性别女民族汉", "points": [[47, 88], [205, 88], [205, 108], [47, 108]], "difficult": false, "key_cls": "sex"}, {"transcription": "1998年5月6日", "points": [[91, 118], [237, 118], [237, 139], [91, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "湖南省长沙某某666号—自制数据集", "points": [[90, 153], [280, 153], [280, 197], [90, 197]], "difficult": false, "key_cls": "adress"}, {"transcription": "081494794611860592", "points": [[145, 235], [310, 235], [310, 260], [145, 260]], "difficult": false, "key_cls": "card"}] ocr/0002.jpg [{"transcription": "雷专鼢", "points": [[94, 54], [157, 54], [157, 81], [94, 81]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[45, 88], [207, 88], [207, 107], [45, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "2018年11月24日", "points": [[90, 117], [239, 117], [239, 141], [90, 141]], "difficult": false, "key_cls": "birth"}, {"transcription": "安徽省合肥某某666号—自制数据集", "points": [[91, 151], [278, 151], [278, 192], [91, 192]], "difficult": false, "key_cls": "adress"}, {"transcription": "965073295312179882", "points": [[145, 238], [310, 238], [310, 258], [145, 258]], "difficult": false, "key_cls": "card"}] ocr/0003.jpg [{"transcription": "卫肮", "points": [[92, 55], [145, 55], [145, 81], [92, 81]], "difficult": false, "key_cls": "name"}, {"transcription": "性别女民族汉", "points": [[45, 88], [207, 88], [207, 106], [45, 106]], "difficult": false, "key_cls": "sex"}, {"transcription": "2019年12月17日", "points": [[88, 116], [238, 116], [238, 137], [88, 137]], "difficult": false, "key_cls": "birth"}, {"transcription": "河南省郑州某某666号—自制数据集", "points": [[90, 153], [277, 153], [277, 192], [90, 192]], "difficult": false, "key_cls": "adress"}, {"transcription": "163878699991251580", "points": [[144, 238], [314, 238], [314, 258], [144, 258]], "difficult": false, "key_cls": "card"}] ocr/0004.jpg [{"transcription": "郝颁", "points": [[93, 56], [144, 56], [144, 81], [93, 81]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[46, 88], [207, 88], [207, 107], [46, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "1984年9月19日", "points": [[90, 115], [237, 115], [237, 139], [90, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "浙江省杭州某某666号—自制数据集", "points": [[90, 154], [278, 154], [278, 193], [90, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "803226740643271224", "points": [[144, 236], [315, 236], [315, 262], [144, 262]], "difficult": false, "key_cls": "card"}] ocr/0005.jpg [{"transcription": "郝嫖", "points": [[93, 54], [144, 54], [144, 82], [93, 82]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[46, 86], [208, 86], [208, 111], [46, 111]], "difficult": false, "key_cls": "sex"}, {"transcription": "1979年7月17日", "points": [[90, 118], [239, 118], [239, 137], [90, 137]], "difficult": false, "key_cls": "birth"}, {"transcription": "湖北省武汉某某666号一自制数据集", "points": [[91, 152], [277, 152], [277, 193], [91, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "974132654656644874", "points": [[144, 237], [311, 237], [311, 260], [144, 260]], "difficult": false, "key_cls": "card"}] ocr/0006.jpg [{"transcription": "茅钇鲅", "points": [[93, 56], [156, 56], [156, 77], [93, 77]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[46, 88], [207, 88], [207, 107], [46, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "1978年2月26日", "points": [[89, 118], [241, 118], [241, 139], [89, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州某某666号—自制数据集", "points": [[89, 152], [279, 152], [279, 196], [89, 196]], "difficult": false, "key_cls": "adress"}, {"transcription": "267124840234334444", "points": [[145, 237], [310, 237], [310, 257], [145, 257]], "difficult": false, "key_cls": "card"}] ocr/0007.jpg [{"transcription": "薛氅沂", "points": [[92, 55], [155, 55], [155, 78], [92, 78]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[45, 87], [207, 87], [207, 106], [45, 106]], "difficult": false, "key_cls": "sex"}, {"transcription": "1995年7月14日", "points": [[88, 118], [236, 118], [236, 138], [88, 138]], "difficult": false, "key_cls": "birth"}, {"transcription": "黑龙江省哈尔滨某某666号自制数据集", "points": [[90, 151], [280, 151], [280, 196], [90, 196]], "difficult": false, "key_cls": "adress"}, {"transcription": "556010053044157446", "points": [[143, 237], [315, 237], [315, 262], [143, 262]], "difficult": false, "key_cls": "card"}] ocr/0008.jpg [{"transcription": "殷蓊", "points": [[93, 53], [144, 53], [144, 82], [93, 82]], "difficult": false, "key_cls": "name"}, {"transcription": "性别女民族汉", "points": [[46, 88], [207, 88], [207, 107], [46, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "2017年8月6日", "points": [[89, 116], [237, 116], [237, 139], [89, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "河北省石家庄某某666号一自制数据集", "points": [[91, 151], [279, 151], [279, 194], [91, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "20190257831503175X", "points": [[145, 237], [314, 237], [314, 260], [145, 260]], "difficult": false, "key_cls": "card"}] ocr/0009.jpg [{"transcription": "熊杼", "points": [[95, 55], [139, 55], [139, 80], [95, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[45, 88], [215, 88], [215, 109], [45, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "2013年4月5日", "points": [[89, 116], [237, 116], [237, 139], [89, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "广东省广州某某666号—自制数据集", "points": [[91, 151], [278, 151], [278, 192], [91, 192]], "difficult": false, "key_cls": "adress"}, {"transcription": "661546442301175555", "points": [[145, 236], [312, 236], [312, 258], [145, 258]], "difficult": false, "key_cls": "card"}] ocr/0010.jpg [{"transcription": "计疆怏", "points": [[97, 56], [160, 56], [160, 80], [97, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[46, 87], [207, 87], [207, 107], [46, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "1985年10月17日", "points": [[89, 117], [240, 117], [240, 142], [89, 142]], "difficult": false, "key_cls": "birth"}, {"transcription": "浙江省杭州某某666号—自制数据集", "points": [[91, 151], [278, 151], [278, 195], [91, 195]], "difficult": false, "key_cls": "adress"}, {"transcription": "449688818089602352", "points": [[145, 235], [313, 235], [313, 261], [145, 261]], "difficult": false, "key_cls": "card"}] ocr/0011.jpg [{"transcription": "萧杀鼬", "points": [[94, 55], [155, 55], [155, 78], [94, 78]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[46, 86], [214, 86], [214, 111], [46, 111]], "difficult": false, "key_cls": "sex"}, {"transcription": "1986年9月3日", "points": [[90, 117], [240, 117], [240, 139], [90, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州某某666号——自制数据集", "points": [[93, 149], [278, 149], [278, 192], [93, 192]], "difficult": true, "key_cls": "adress"}, {"transcription": "984445587021926237", "points": [[146, 236], [311, 236], [311, 259], [146, 259]], "difficult": false, "key_cls": "card"}] ocr/0012.jpg [{"transcription": "乐骶脲", "points": [[95, 55], [158, 55], [158, 79], [95, 79]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[43, 84], [207, 84], [207, 107], [43, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "2014年6月2日", "points": [[90, 117], [228, 117], [228, 135], [90, 135]], "difficult": false, "key_cls": "birth"}, {"transcription": "安徽省合肥某某666号—自制数据集", "points": [[89, 149], [279, 149], [279, 194], [89, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "294336746086848019", "points": [[145, 237], [310, 237], [310, 260], [145, 260]], "difficult": false, "key_cls": "card"}] ocr/0013.jpg [{"transcription": "金桂羔", "points": [[94, 55], [160, 55], [160, 83], [94, 83]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[45, 87], [207, 87], [207, 108], [45, 108]], "difficult": false, "key_cls": "sex"}, {"transcription": "2019年6月9日", "points": [[89, 117], [237, 117], [237, 140], [89, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州某某666号——自制数据集", "points": [[90, 151], [279, 151], [279, 194], [90, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "770140527439237475", "points": [[144, 237], [314, 237], [314, 260], [144, 260]], "difficult": false, "key_cls": "card"}] ocr/0014.jpg [{"transcription": "苗停", "points": [[92, 55], [136, 55], [136, 80], [92, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[42, 85], [207, 85], [207, 107], [42, 107]], "difficult": false, "key_cls": "sex"}, {"transcription": "2004年2月25日", "points": [[89, 115], [229, 115], [229, 135], [89, 135]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州某某666号—自制数据集", "points": [[91, 151], [277, 151], [277, 193], [91, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "352678939043916255", "points": [[144, 238], [311, 238], [311, 262], [144, 262]], "difficult": false, "key_cls": "card"}] ocr/0015.jpg [{"transcription": "安狲", "points": [[93, 54], [141, 54], [141, 78], [93, 78]], "difficult": false, "key_cls": "name"}, {"transcription": "性别机器人民族汉", "points": [[44, 86], [213, 86], [213, 112], [44, 112]], "difficult": false, "key_cls": "sex"}, {"transcription": "1985年9月12日", "points": [[90, 116], [241, 116], [241, 141], [90, 141]], "difficult": false, "key_cls": "birth"}, {"transcription": "山东省济南某某666号——自制数据集", "points": [[90, 151], [279, 151], [279, 193], [90, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "78953491053071603X", "points": [[145, 238], [312, 238], [312, 261], [145, 261]], "difficult": false, "key_cls": "card"}] ocr/0016.jpg [{"transcription": "成最", "points": [[93, 55], [139, 55], [139, 80], [93, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[47, 88], [212, 88], [212, 109], [47, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "2004年10月16日", "points": [[91, 118], [238, 118], [238, 139], [91, 139]], "difficult": false, "key_cls": "birth"}, {"transcription": "潮北省武汉某某666号——自制数据集", "points": [[92, 153], [279, 153], [279, 195], [92, 195]], "difficult": false, "key_cls": "adress"}, {"transcription": "585127964734198547", "points": [[145, 238], [311, 238], [311, 260], [145, 260]], "difficult": false, "key_cls": "card"}] ocr/0017.jpg [{"transcription": "凤靓", "points": [[94, 56], [141, 56], [141, 80], [94, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[47, 88], [211, 88], [211, 109], [47, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "1995年6月27日", "points": [[91, 117], [245, 117], [245, 142], [91, 142]], "difficult": false, "key_cls": "birth"}, {"transcription": "山西省太原某某666号—自制数据集", "points": [[92, 153], [279, 153], [279, 193], [92, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "925371718911532719", "points": [[145, 238], [311, 238], [311, 260], [145, 260]], "difficult": false, "key_cls": "card"}] ocr/0018.jpg [{"transcription": "张辉", "points": [[93, 55], [139, 55], [139, 79], [93, 79]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[45, 87], [214, 87], [214, 109], [45, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "2009年12月6日", "points": [[88, 117], [237, 117], [237, 140], [88, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "潮北省武汉某某666号—自制数据集", "points": [[93, 152], [278, 152], [278, 194], [93, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "898135533101984568", "points": [[145, 238], [310, 238], [310, 258], [145, 258]], "difficult": false, "key_cls": "card"}] ocr/0019.jpg [{"transcription": "吕课", "points": [[95, 57], [137, 57], [137, 79], [95, 79]], "difficult": false, "key_cls": "name"}, {"transcription": "性别未知民族汉", "points": [[46, 87], [210, 87], [210, 110], [46, 110]], "difficult": false, "key_cls": "sex"}, {"transcription": "2014年1月16日", "points": [[91, 116], [240, 116], [240, 140], [91, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "山东省济南某某666号—自制数据集", "points": [[92, 151], [280, 151], [280, 194], [92, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "418547080384305138", "points": [[146, 235], [310, 235], [310, 260], [146, 260]], "difficult": false, "key_cls": "card"}] ocr/0020.jpg [{"transcription": "祁峁", "points": [[94, 55], [135, 55], [135, 79], [94, 79]], "difficult": false, "key_cls": "name"}, {"transcription": "性别女民族汉", "points": [[46, 88], [209, 88], [209, 111], [46, 111]], "difficult": false, "key_cls": "sex"}, {"transcription": "2002年3月20日", "points": [[90, 116], [238, 116], [238, 140], [90, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "河南省郑州某某666号——自制数据集", "points": [[92, 151], [277, 151], [277, 193], [92, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "081155252519463497", "points": [[144, 237], [312, 237], [312, 260], [144, 260]], "difficult": false, "key_cls": "card"}] ocr/0021.jpg [{"transcription": "魏喜糨", "points": [[96, 55], [154, 55], [154, 77], [96, 77]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[49, 89], [209, 89], [209, 109], [49, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "2005年7月15日", "points": [[91, 117], [237, 117], [237, 140], [91, 140]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州某某666号—自制数据集", "points": [[93, 152], [279, 152], [279, 195], [93, 195]], "difficult": false, "key_cls": "adress"}, {"transcription": "885898805473809799", "points": [[145, 238], [310, 238], [310, 257], [145, 257]], "difficult": false, "key_cls": "card"}] ocr/0022.jpg [{"transcription": "425763470037534625", "points": [[146, 239], [310, 239], [310, 258], [146, 258]], "difficult": false, "key_cls": "card"}, {"transcription": "吉林省长春某某666号——自制数据集", "points": [[93, 153], [280, 153], [280, 194], [93, 194]], "difficult": false, "key_cls": "adress"}, {"transcription": "1986年2月13日", "points": [[93, 117], [237, 117], [237, 138], [93, 138]], "difficult": false, "key_cls": "birth"}, {"transcription": "性别男民族汉", "points": [[47, 88], [207, 88], [207, 109], [47, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "傅嘁馐", "points": [[95, 57], [155, 57], [155, 78], [95, 78]], "difficult": false, "key_cls": "name"}] ocr/0023.jpg [{"transcription": "孔操肆", "points": [[97, 57], [155, 57], [155, 80], [97, 80]], "difficult": false, "key_cls": "name"}, {"transcription": "性别男民族汉", "points": [[45, 85], [207, 85], [207, 109], [45, 109]], "difficult": false, "key_cls": "sex"}, {"transcription": "2006年2月21日", "points": [[90, 116], [232, 116], [232, 136], [90, 136]], "difficult": false, "key_cls": "birth"}, {"transcription": "福建省福州号——自制数据集", "points": [[93, 152], [278, 152], [278, 193], [93, 193]], "difficult": false, "key_cls": "adress"}, {"transcription": "760297342529942985", "points": [[146, 239], [309, 239], [309, 257], [146, 257]], "difficult": false, "key_cls": "card"}]
2.训练det模型
python tools/train.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_cml.ymlcal_metric_during_train改成false，Train.loader.batch_size_per_card改成10，Global.pretrained_model改成本地模型
Global:
debug: false
use_gpu: true
epoch_num: 500
log_smooth_window: 20
print_batch_step: 20
save_model_dir: ./output/ch_PP-OCRv4_det
save_epoch_step: 50
eval_batch_step:
- 0
- 1000
cal_metric_during_train: false
checkpoints: null
pretrained_model: ./train/model/ch_PP-OCRv4_det_train/best_accuracy.pdparams
save_inference_dir: null
use_visualdl: false
infer_img: doc/imgs_en/img_10.jpg
save_res_path: ./checkpoints/det_db/predicts_db.txt
distributed: true
Architecture:
name: DistillationModel
algorithm: Distillation
model_type: det
Models:
Student:
model_type: det
algorithm: DB
Transform: null
Backbone:
name: PPLCNetV3
scale: 0.75
pretrained: false
det: true
Neck:
name: RSEFPN
out_channels: 96
shortcut: true
Head:
name: DBHead
k: 50
Student2:
pretrained: null
model_type: det
algorithm: DB
Transform: null
Backbone:
name: PPLCNetV3
scale: 0.75
pretrained: true
det: true
Neck:
name: RSEFPN
out_channels: 96
shortcut: true
Head:
name: DBHead
k: 50
Teacher:
pretrained: https://paddleocr.bj.bcebos.com/PP-OCRv4/chinese/ch_PP-OCRv4_det_cml_teacher_pretrained/teacher.pdparams
freeze_params: true
return_all_feats: false
model_type: det
algorithm: DB
Backbone:
name: ResNet_vd
in_channels: 3
layers: 50
Neck:
name: LKPAN
out_channels: 256
Head:
name: DBHead
kernel_list:
- 7
- 2
- 2
k: 50
Loss:
name: CombinedLoss
loss_config_list:
- DistillationDilaDBLoss:
weight: 1.0
model_name_pairs:
- - Student
- Teacher
- - Student2
- Teacher
key: maps
balance_loss: true
main_loss_type: DiceLoss
alpha: 5
beta: 10
ohem_ratio: 3
- DistillationDMLLoss:
model_name_pairs:
- Student
- Student2
maps_name: thrink_maps
weight: 1.0
key: maps
- DistillationDBLoss:
weight: 1.0
model_name_list:
- Student
- Student2
balance_loss: true
main_loss_type: DiceLoss
alpha: 5
beta: 10
ohem_ratio: 3
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: Cosine
learning_rate: 0.001
warmup_epoch: 2
regularizer:
name: L2
factor: 5.0e-05
PostProcess:
name: DistillationDBPostProcess
model_name:
- Student
key: head_out
thresh: 0.3
box_thresh: 0.6
max_candidates: 1000
unclip_ratio: 1.5
Metric:
name: DistillationMetric
base_metric_name: DetMetric
main_indicator: hmean
key: Student
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
label_file_list:
- ./train_data/det/train.txt
ratio_list: [1.0]
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- DetLabelEncode: null
- IaaAugment:
augmenter_args:
- type: Fliplr
args:
p: 0.5
- type: Affine
args:
rotate:
- -10
- 10
- type: Resize
args:
size:
- 0.5
- 3
- EastRandomCropData:
size:
- 640
- 640
max_tries: 50
keep_ratio: true
- MakeBorderMap:
shrink_ratio: 0.4
thresh_min: 0.3
thresh_max: 0.7
total_epoch: 500
- MakeShrinkMap:
shrink_ratio: 0.4
min_text_size: 8
total_epoch: 500
- NormalizeImage:
scale: 1./255.
mean:
- 0.485
- 0.456
- 0.406
std:
- 0.229
- 0.224
- 0.225
order: hwc
- ToCHWImage: null
- KeepKeys:
keep_keys:
- image
- threshold_map
- threshold_mask
- shrink_map
- shrink_mask
loader:
shuffle: true
drop_last: false
# batch_size_per_card: 16
batch_size_per_card: 10
num_workers: 8
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/
label_file_list:
- ./train_data/det/val.txt
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- DetLabelEncode: null
- DetResizeForTest:
limit_side_len: 960
limit_type: max
- NormalizeImage:
scale: 1./255.
mean:
- 0.485
- 0.456
- 0.406
std:
- 0.229
- 0.224
- 0.225
order: hwc
- ToCHWImage: null
- KeepKeys:
keep_keys:
- image
- shape
- polys
- ignore_tags
loader:
shuffle: false
drop_last: false
batch_size_per_card: 1
num_workers: 2
profiler_options: null3.训练rec模型
python tools/train.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec.ymlGlobal.pretrained_model改成本地模型
Global:
debug: false
use_gpu: true
epoch_num: 200
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/ch_PP-OCRv4_rec
save_epoch_step: 10
eval_batch_step: [0, 2000]
cal_metric_during_train: true
pretrained_model: ./train/model/ch_PP-OCRv4_rec_train/student.pdparams
checkpoints:
save_inference_dir:
use_visualdl: false
infer_img: doc/imgs_words/ch/word_1.jpg
character_dict_path: ppocr/utils/ppocr_keys_v1.txt
max_text_length: &max_text_length 25
infer_mode: false
use_space_char: true
distributed: true
save_res_path: ./output/rec/predicts_ppocrv3.txt
Optimizer:
name: Adam
beta1: 0.9
beta2: 0.999
lr:
name: Cosine
learning_rate: 0.001
warmup_epoch: 5
regularizer:
name: L2
factor: 3.0e-05
Architecture:
model_type: rec
algorithm: SVTR_LCNet
Transform:
Backbone:
name: PPLCNetV3
scale: 0.95
Head:
name: MultiHead
head_list:
- CTCHead:
Neck:
name: svtr
dims: 120
depth: 2
hidden_dims: 120
kernel_size: [1, 3]
use_guide: True
Head:
fc_decay: 0.00001
- NRTRHead:
nrtr_dim: 384
max_text_length: *max_text_length
Loss:
name: MultiLoss
loss_config_list:
- CTCLoss:
- NRTRLoss:
PostProcess:
name: CTCLabelDecode
Metric:
name: RecMetric
main_indicator: acc
Train:
dataset:
name: MultiScaleDataSet
ds_width: false
data_dir: ./train_data/
ext_op_transform_idx: 1
label_file_list:
- ./train_data/rec/train.txt
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- RecConAug:
prob: 0.5
ext_data_num: 2
image_shape: [48, 320, 3]
max_text_length: *max_text_length
- RecAug:
- MultiLabelEncode:
gtc_encode: NRTRLabelEncode
- KeepKeys:
keep_keys:
- image
- label_ctc
- label_gtc
- length
- valid_ratio
sampler:
name: MultiScaleSampler
scales: [[320, 32], [320, 48], [320, 64]]
first_bs: &bs 192
fix_bs: false
divided_factor: [8, 16] # w, h
is_training: True
loader:
shuffle: true
batch_size_per_card: *bs
drop_last: true
num_workers: 8
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data
label_file_list:
- ./train_data/rec/val.txt
transforms:
- DecodeImage:
img_mode: BGR
channel_first: false
- MultiLabelEncode:
gtc_encode: NRTRLabelEncode
- RecResizeImg:
image_shape: [3, 48, 320]
- KeepKeys:
keep_keys:
- image
- label_ctc
- label_gtc
- length
- valid_ratio
loader:
shuffle: false
drop_last: false
batch_size_per_card: 128
num_workers: 44.导出推理模型
python tools/export_model.py -c configs/det/ch_PP-OCRv4/ch_PP-OCRv4_det_cml.yml -o Global.pretrained_model=output/ch_PP-OCRv4_det/best_model/model.pdparams Global.save_inference_dir=inference_model/det/python tools/export_model.py -c configs/rec/PP-OCRv4/ch_PP-OCRv4_rec.yml -o Global.pretrained_model="./output/ch_PP-OCRv4_rec/latest.pdparams" Global.save_inference_dir="./inference_model/rec/"5.执行脚本
import cv2
from paddleocr import PaddleOCR
paddleocr = PaddleOCR(lang='ch', show_log=False, enable_mkldnn=True,
det_model_dir='./inference_model/det/Teacher',
rec_model_dir='./inference_model/rec'
)
img = cv2.imread('./train_data/0000.jpg')
result = paddleocr.ocr(img)
for i in range(len(result[0])):
print(result[0][i][1][0])
UserWangZz
xiaowen0407
Sensorjang
请提供下述完整信息以便快速定位问题/Please provide the following information to quickly locate the problem
稍等附上训练过程