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训练文本检测模型,训练后的checkpoints模型与转换后的inference模型识别效果不一致
训练:tools/train.py -c ./configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml 评估:tools/eval.py -c ./configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy.pdparams 预测:tools/infer_det.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.infer_img=./train_data/wenbenjiance_test Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy.pdparams 预测结果正常:
转推理模型:tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy Global.save_inference_dir=./output/fapiao_putong_ch_PP-OCR_v3_det_inferer
推理模型预测:tools/infer/predict_det.py --image_dir=./train_data/wenbenjiance_test --det_model_dir=./output/fapiao_putong_ch_PP-OCR_v3_det_inferer
预测结果不正常:
配置文件ch_PP-OCRv3_det_student.yml Global: debug: false use_gpu: true epoch_num: 500 log_smooth_window: 20 print_batch_step: 10 save_model_dir: ./output/fapiao_putong_ch_PP-OCR_V3_det/ save_epoch_step: 100 eval_batch_step:
0 500 cal_metric_during_train: false pretrained_model: ./pretrained_model/ch_PP-OCRv3_det_distill_train/student.pdparams checkpoints: null save_inference_dir: null use_visualdl: false infer_img: doc/imgs_en/img_10.jpg save_res_path: ./output/fapiao_putong_checkpoints/det_db/predicts_db.txt distributed: true Architecture: model_type: det algorithm: DB Transform: Backbone: name: MobileNetV3 scale: 0.5 model_name: large disable_se: True Neck: name: RSEFPN out_channels: 96 shortcut: True Head: name: DBHead k: 50
Loss: name: DBLoss 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: 0.00005 warmup_epoch: 2 regularizer: name: L2 factor: 5.0e-05 PostProcess: name: DBPostProcess thresh: 0.3 box_thresh: 0.6 max_candidates: 1000 unclip_ratio: 1.5 Metric: name: DetMetric main_indicator: hmean Train: dataset: name: SimpleDataSet data_dir: ./train_data/wenbenjiance/imgs label_file_list:
The text was updated successfully, but these errors were encountered:
转inference模型后,会有一套默认配置,需要确保这个配置和动态图推理时一致。
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问题描述 / Problem Description
训练文本检测模型,训练后的checkpoints模型与转换后的inference模型识别效果不一致
运行环境 / Runtime Environment
复现代码 / Reproduction Code
训练:tools/train.py -c ./configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml
评估:tools/eval.py -c ./configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy.pdparams
预测:tools/infer_det.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.infer_img=./train_data/wenbenjiance_test Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy.pdparams
预测结果正常:
转推理模型:tools/export_model.py -c configs/det/ch_PP-OCRv3/ch_PP-OCRv3_det_student.yml -o Global.checkpoints=./output/1-fapiao_putong_ch_PP-OCR_V3_det/best_accuracy Global.save_inference_dir=./output/fapiao_putong_ch_PP-OCR_v3_det_inferer
推理模型预测:tools/infer/predict_det.py --image_dir=./train_data/wenbenjiance_test --det_model_dir=./output/fapiao_putong_ch_PP-OCR_v3_det_inferer
预测结果不正常:
配置文件ch_PP-OCRv3_det_student.yml
Global:
debug: false
use_gpu: true
epoch_num: 500
log_smooth_window: 20
print_batch_step: 10
save_model_dir: ./output/fapiao_putong_ch_PP-OCR_V3_det/
save_epoch_step: 100
eval_batch_step:
0
500
cal_metric_during_train: false
pretrained_model: ./pretrained_model/ch_PP-OCRv3_det_distill_train/student.pdparams
checkpoints: null
save_inference_dir: null
use_visualdl: false
infer_img: doc/imgs_en/img_10.jpg
save_res_path: ./output/fapiao_putong_checkpoints/det_db/predicts_db.txt
distributed: true
Architecture:
model_type: det
algorithm: DB
Transform:
Backbone:
name: MobileNetV3
scale: 0.5
model_name: large
disable_se: True
Neck:
name: RSEFPN
out_channels: 96
shortcut: True
Head:
name: DBHead
k: 50
Loss:
name: DBLoss
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: 0.00005
warmup_epoch: 2
regularizer:
name: L2
factor: 5.0e-05
PostProcess:
name: DBPostProcess
thresh: 0.3
box_thresh: 0.6
max_candidates: 1000
unclip_ratio: 1.5
Metric:
name: DetMetric
main_indicator: hmean
Train:
dataset:
name: SimpleDataSet
data_dir: ./train_data/wenbenjiance/imgs
label_file_list:
ratio_list: [1.0]
transforms:
img_mode: BGR
channel_first: false
augmenter_args:
args:
p: 0.5
args:
rotate:
args:
size:
size:
max_tries: 50
keep_ratio: true
shrink_ratio: 0.4
thresh_min: 0.3
thresh_max: 0.7
shrink_ratio: 0.4
min_text_size: 8
scale: 1./255.
mean:
std:
order: hwc
keep_keys:
loader:
shuffle: true
drop_last: false
batch_size_per_card: 4
num_workers: 0
Eval:
dataset:
name: SimpleDataSet
data_dir: ./train_data/wenbenjiance/imgs
label_file_list:
transforms:
img_mode: BGR
channel_first: false
scale: 1./255.
mean:
std:
order: hwc
keep_keys:
loader:
shuffle: false
drop_last: false
batch_size_per_card: 1
num_workers: 0
完整报错 / Complete Error Message
可能解决方案 / Possible solutions
附件 / Appendix
The text was updated successfully, but these errors were encountered: