paddlepaddle / paddleocr Goto Github PK

请问超轻量模型的训练数据（中英文数字）是公开的数据集么，还是私有数据集，可以共享么，谢谢

你好，请问如何将paddleOCR设置为http server服务？

python tools/export_model.py -c configs/det/det_db_mv3.yml -o Global.checkpoints="./output/best_accuracy" Global.save_inference_dir="./inference/det/"

paddlepaddle-gpu只能用这个版本1.7.2.post97吗？
目前是paddlepaddle-gpu 1.8.0.post107

我更改了rec_chinese_lite_train.yml配置文件的内容，如下：

Global:
  algorithm: CRNN
  use_gpu: true
  epoch_num: 300
  log_smooth_window: 20
  print_batch_step: 10
  save_model_dir: ./output/rec_CRNN
  save_epoch_step: 3
  eval_batch_step: 2000
  train_batch_size_per_card: 160
  test_batch_size_per_card: 160
  image_shape: [3, 32, 320]
  max_text_length: 25
  character_type: ch
  character_dict_path: ./ppocr/utils/18548.txt
  loss_type: ctc
  reader_yml: ./configs/rec/rec_chinese_reader_csv.yml
  pretrain_weights: ./pretrain_models/rec_mv3_none_bilstm_ctc/best_accuracy
  checkpoints:
  save_inference_dir:
Architecture:
  function: ppocr.modeling.architectures.rec_model,RecModel

Backbone:
  function: ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3
  scale: 0.5
  model_name: small

Head:
  function: ppocr.modeling.heads.rec_ctc_head,CTCPredict
  encoder_type: rnn
  SeqRNN:
    hidden_size: 48
    
Loss:
  function: ppocr.modeling.losses.rec_ctc_loss,CTCLoss

Optimizer:
  function: ppocr.optimizer,AdamDecay
  base_lr: 0.0005
  beta1: 0.9
  beta2: 0.999

其实只更改了epoch_num，batch_size，character_dict_path，reader_yml，pretrain_weights这几处，但是迭代了100轮左右，现在的train acc只有0.2左右。我的字符集有18000多个，请问这个轻量级的网络目前来看是不是欠拟合了？因为我发现如果我换成resnet50作为backbone，网络可以训练的不错

现在都是python接口版本，请问是否考虑提供c++接口版本？

如题，期待SRN的开源。

您好，follow detection.md文档进行ocr训练时，运行训练命令遇到了以下问题，特来请教。
通过FLAGS_selected_gpus 指定显卡 和 修改train.py里面的place = fluid.CUDAPlace(3) if use_gpu else fluid.CPUPlace()运行训练都会出现这个问题。
运行use_gpu=False也出现了下面的问题。
FLAGS_selected_gpus=3 && python3 tools/train.py -c configs/det/det_mv3_db.yml -o Optimizer.base_lr=0.0001
grep: warning: GREP_OPTIONS is deprecated; please use an alias or script
2020-05-18 09:29:29,797-INFO: {'Architecture': {'function': 'ppocr.modeling.architectures.det_model,DetModel'}, 'TestReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'single_img_path': None, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280], 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'do_eval': True}, 'Backbone': {'function': 'ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3', 'model_name': 'large', 'scale': 0.5}, 'Head': {'k': 50, 'function': 'ppocr.modeling.heads.det_db_head,DBHead', 'inner_channels': 96, 'model_name': 'large', 'out_channels': 2}, 'Optimizer': {'beta1': 0.9, 'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 0.0001, 'beta2': 0.999}, 'EvalReader': {'test_image_shape': [736, 1280], 'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'img_set_dir': './train_data/icdar2015/text_localization/', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt'}, 'Loss': {'function': 'ppocr.modeling.losses.det_db_loss,DBLoss', 'balance_loss': True, 'beta': 10, 'alpha': 5, 'ohem_ratio': 3, 'main_loss_type': 'DiceLoss'}, 'TrainReader': {'reader_function': 'ppocr.data.det.dataset_traversal,TrainReader', 'num_workers': 8, 'img_set_dir': './train_data/icdar2015/text_localization/', 'process_function': 'ppocr.data.det.db_process,DBProcessTrain', 'label_file_path': './train_data/icdar2015/text_localization/train_icdar2015_label.txt'}, 'PostProcess': {'unclip_ratio': 1.5, 'max_candidates': 1000, 'function': 'ppocr.postprocess.db_postprocess,DBPostProcess', 'thresh': 0.3, 'box_thresh': 0.7}, 'Global': {'save_epoch_step': 200, 'save_inference_dir': None, 'eval_batch_step': 5000, 'log_smooth_window': 20, 'algorithm': 'DB', 'epoch_num': 1200, 'use_gpu': True, 'train_batch_size_per_card': 16, 'image_shape': [3, 640, 640], 'save_model_dir': './output/det_db/', 'save_res_path': './output/det_db/predicts_db.txt', 'checkpoints': None, 'pretrain_weights': './pretrain_models/MobileNetV3_large_x0_5_pretrained/', 'test_batch_size_per_card': 16, 'reader_yml': './configs/det/det_db_icdar15_reader.yml', 'print_batch_step': 2}}
3 640 640
3 640 640
import ujson error: No module named 'ujson' use json
2020-05-18 09:29:33,067-INFO: places would be ommited when DataLoader is not iterable
W0518 09:29:33.928460 5607 device_context.cc:237] Please NOTE: device: 3, CUDA Capability: 75, Driver API Version: 10.2, Runtime API Version: 10.0
W0518 09:29:33.932370 5607 device_context.cc:245] device: 3, cuDNN Version: 7.5.
W0518 09:29:33.932396 5607 device_context.cc:271] WARNING: device: 3. The installed Paddle is compiled with CUDNN 7.6, but CUDNN version in your machine is 7.5, which may cause serious incompatible bug. Please recompile or reinstall Paddle with compatible CUDNN version.
2020-05-18 09:29:35,015-INFO: Loading parameters from ./pretrain_models/MobileNetV3_large_x0_5_pretrained/...
2020-05-18 09:29:35,015-WARNING: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ]
2020-05-18 09:29:35,015-WARNING: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ]
2020-05-18 09:29:35,206-INFO: Finish initing model from ./pretrain_models/MobileNetV3_large_x0_5_pretrained/
I0518 09:29:35.251972 5607 parallel_executor.cc:440] The Program will be executed on CUDA using ParallelExecutor, 8 cards are used, so 8 programs are executed in parallel.
W0518 09:29:48.223284 5607 init.cc:209] Warning: PaddlePaddle catches a failure signal, it may not work properly
W0518 09:29:48.223331 5607 init.cc:211] You could check whether you killed PaddlePaddle thread/process accidentally or report the case to PaddlePaddle
W0518 09:29:48.223345 5607 init.cc:214] The detail failure signal is:

Traceback (most recent call last):
File "/projects/python/PaddleOCR/tools/infer/predict_system.py", line 115, in
dt_boxes, rec_res = text_sys(img)
File "/projects/python/PaddleOCR/tools/infer/predict_system.py", line 67, in call
dt_boxes, elapse = self.text_detector(img)
File "/projects/python/PaddleOCR/tools/infer/predict_det.py", line 143, in call
outs_dict['f_geo'] = outputs[1]
IndexError: list index out of range

Traceback (most recent call last):
File "tools/infer/predict_system.py", line 15, in
import utility
File "PaddleOCR/tools/infer/utility.py", line 17, in
from ppocr.utils.utility import initial_logger
ModuleNotFoundError: No module named 'ppocr'

paddlepaddle-gpu 1.7.2.post107
PaddleOCR 3b40c32

python tools/export_model.py -c configs/rec/rec_r34_vd_tps_bilstm_attn.yml -o Global.checkpoints="./output/rec/rec_r34_vd_tps_bilstm_attn/best_accuracy" Global.save_inference_dir="./inference/rec/rec_r34_vd_tps_bilstm_attn"

python tools/export_model.py -c configs/rec/rec_mv3_tps_bilstm_attn.yml -o Global.checkpoints="./output/rec/rec_mv3_tps_bilstm_attn/best_accuracy" Global.save_inference_dir="./inference/rec/rec_mv3_tps_bilstm_attn"

Traceback (most recent call last):
  File "tools/export_model.py", line 94, in <module>
    main()
  File "tools/export_model.py", line 68, in main
    config, eval_program, startup_prog)
  File "PaddleOCR\tools\program.py", line 193, in build_export
    image, outputs = model(mode='export')
  File "PaddleOCR\ppocr\modeling\architectures\rec_model.py", line 112
, in __call__
    predict = predicts['predict']
KeyError: 'predict'

运行命令：
python3 tools/export_model.py -c configs/rec/rec_r34_vd_tps_bilstm_attn.yml -o Global.checkpoints=./ch_lite/rec_r34_vd_tps_bilstm_attn/best_accuracy Global.save_inference_dir=./inference_model/rec_r34/

出现报错：
Traceback (most recent call last):
File "tools/export_model.py", line 93, in
main()
File "tools/export_model.py", line 67, in main
config, eval_program, startup_prog)
File "/root/PaddleOCR-develop/tools/program.py", line 193, in build_export
image, outputs = model(mode='export')
File "/root/PaddleOCR-develop/ppocr/modeling/architectures/rec_model.py", line 112, in call
predict = predicts['predict']
KeyError: 'predict'

请问有没有考虑过移动端部署呢？具体是什么流程呢？

图像中文字不多的情况下，实际使用需要240ms左右的时间

(PaddlePaddle) xx@MacBook-Pro PaddleOCR % python3 tools/train.py -c configs/det/det_mv3_db.yml
2020-05-17 10:05:23,320-INFO: {'Global': {'algorithm': 'DB', 'use_gpu': False, 'epoch_num': 1200, 'log_smooth_window': 20, 'print_batch_step': 2, 'save_model_dir': './output/det_db/', 'save_epoch_step': 200, 'eval_batch_step': 5000, 'train_batch_size_per_card': 16, 'test_batch_size_per_card': 16, 'image_shape': [3, 640, 640], 'reader_yml': './configs/det/det_db_icdar15_reader.yml', 'pretrain_weights': './pretrain_models/MobileNetV3_large_x0_5_pretrained/', 'checkpoints': None, 'save_res_path': './output/det_db/predicts_db.txt', 'save_inference_dir': None}, 'Architecture': {'function': 'ppocr.modeling.architectures.det_model,DetModel'}, 'Backbone': {'function': 'ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3', 'scale': 0.5, 'model_name': 'large'}, 'Head': {'function': 'ppocr.modeling.heads.det_db_head,DBHead', 'model_name': 'large', 'k': 50, 'inner_channels': 96, 'out_channels': 2}, 'Loss': {'function': 'ppocr.modeling.losses.det_db_loss,DBLoss', 'balance_loss': True, 'main_loss_type': 'DiceLoss', 'alpha': 5, 'beta': 10, 'ohem_ratio': 3}, 'Optimizer': {'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 0.001, 'beta1': 0.9, 'beta2': 0.999}, 'PostProcess': {'function': 'ppocr.postprocess.db_postprocess,DBPostProcess', 'thresh': 0.3, 'box_thresh': 0.7, 'max_candidates': 1000, 'unclip_ratio': 1.5}, 'TrainReader': {'reader_function': 'ppocr.data.det.dataset_traversal,TrainReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTrain', 'num_workers': 8, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/train_icdar2015_label.txt'}, 'EvalReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280]}, 'TestReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'single_img_path': None, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280], 'do_eval': True}}
2020-05-17 10:05:23,321-ERROR: Config use_gpu cannot be set as true while you are using paddlepaddle cpu version !
Please try:
1. Install paddlepaddle-gpu to run model on GPU
2. Set use_gpu as false in config file to run model on CPU

开发环境：
win10，conda安装paddlepaddle=1.8。
已经成功生成model和params文件，只是部署预测的时候出了错。

运行predict_system的时候报错如下：
Traceback (most recent call last):
File "E:/jiajun LUO/OCR/PaddleOCR-develop/tools/infer/predict_system.py", line 121, in
dt_boxes, rec_res = text_sys(img)
File "E:/jiajun LUO/OCR/PaddleOCR-develop/tools/infer/predict_system.py", line 81, in call
rec_res, elapse = self.text_recognizer(img_crop_list)
File "E:\jiajun LUO\OCR\PaddleOCR-develop\tools\infer\predict_rec.py", line 81, in call
self.predictor.zero_copy_run()
paddle.fluid.core_avx.EnforceNotMet:

C++ Call Stacks (More useful to developers):

Windows not support stack backtrace yet.

Python Call Stacks (More useful to users):

File "F:\Anaconda3\envs\paddle\lib\site-packages\paddle\fluid\framework.py", line 2610, in append_op
attrs=kwargs.get("attrs", None))
File "F:\Anaconda3\envs\paddle\lib\site-packages\paddle\fluid\layer_helper.py", line 43, in append_op
return self.main_program.current_block().append_op(*args, **kwargs)
File "F:\Anaconda3\envs\paddle\lib\site-packages\paddle\fluid\layers\nn.py", line 13779, in grid_sampler
helper.append_op(type='grid_sampler', inputs=ipts, outputs={'Output': out})
File "E:\jiajun LUO\OCR\PaddleOCR-develop\ppocr\modeling\stns\tps.py", line 259, in call
batch_I_r = layers.grid_sampler(x=image, grid=batch_P_prime)
File "E:\jiajun LUO\OCR\PaddleOCR-develop\ppocr\modeling\architectures\rec_model.py", line 98, in call
inputs = self.tps(image)
File "E:\jiajun LUO\OCR\PaddleOCR-develop\tools\program.py", line 198, in build_export
image, outputs = model(mode='export')
File "E:/jiajun LUO/OCR/PaddleOCR-develop/tools/export_model.py", line 68, in main
config, eval_program, startup_prog)
File "E:/jiajun LUO/OCR/PaddleOCR-develop/tools/export_model.py", line 94, in
main()

Error Message Summary:

InvalidArgumentError: Input(X) dims[3] and Input(Grid) dims[2] should be equal, but received X dimension3 != Grid dimension2
[Hint: Expected grid_dims[2] == x_dims[3], but received grid_dims[2]:100 != x_dims[3]:382.] at (D:\1.8.0cpu2\paddle\paddle\fluid\operators\grid_sampler_op.cc:72)
[operator < grid_sampler > error]

你好，在检测模型转inference模型时，已修改det_mv3_db.yml 中'use_gpu': False，但仍然报错，如下所示：
python tools/export_model.py -c configs/det/det_mv3_db.yml -o Global.checkpoints=./ch_lite/det_mv3_db/best_accuracy Global.save_inference_dir=./inference_model/det_db/
2020-05-19 10:29:59,237-INFO: {'Global': {'algorithm': 'DB', 'use_gpu': False, 'epoch_num': 1200, 'log_smooth_window': 20, 'print_batch_step': 2, 'save_model_dir': './output/det_db/', 'save_epoch_step': 200, 'eval_batch_step': 5000, 'train_batch_size_per_card': 16, 'test_batch_size_per_card': 16, 'image_shape': [3, 640, 640], 'reader_yml': './configs/det/det_db_icdar15_reader.yml', 'pretrain_weights': './pretrain_models/MobileNetV3_large_x0_5_pretrained/', 'checkpoints': './ch_lite/det_mv3_db/best_accuracy', 'save_res_path': './output/det_db/predicts_db.txt', 'save_inference_dir': './inference_model/det_db/'}, 'Architecture': {'function': 'ppocr.modeling.architectures.det_model,DetModel'}, 'Backbone': {'function': 'ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3', 'scale': 0.5, 'model_name': 'large'}, 'Head': {'function': 'ppocr.modeling.heads.det_db_head,DBHead', 'model_name': 'large', 'k': 50, 'inner_channels': 96, 'out_channels': 2}, 'Loss': {'function': 'ppocr.modeling.losses.det_db_loss,DBLoss', 'balance_loss': True, 'main_loss_type': 'DiceLoss', 'alpha': 5, 'beta': 10, 'ohem_ratio': 3}, 'Optimizer': {'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 0.001, 'beta1': 0.9, 'beta2': 0.999}, 'PostProcess': {'function': 'ppocr.postprocess.db_postprocess,DBPostProcess', 'thresh': 0.3, 'box_thresh': 0.7, 'max_candidates': 1000, 'unclip_ratio': 1.5}, 'TrainReader': {'reader_function': 'ppocr.data.det.dataset_traversal,TrainReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTrain', 'num_workers': 8, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/train_icdar2015_label.txt'}, 'EvalReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280]}, 'TestReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'single_img_path': None, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280], 'do_eval': True}}
2020-05-19 10:29:59,238-ERROR: Config use_gpu cannot be set as true while you are using paddlepaddle cpu version !
Please try:
1. Install paddlepaddle-gpu to run model on GPU
2. Set use_gpu as false in config file to run model on CPU

运行　python3 tools/eval.py 出现如下错误
2020-05-21 09:38:02,350-INFO: Finish initing model from ./output/det_db/iter_epoch_1600
2020-05-21 09:38:04,318-INFO: test tackling num:8
Traceback (most recent call last):
File "tools/eval.py", line 101, in
main()
File "tools/eval.py", line 80, in main
metrics = eval_det_run(exe, config, eval_info_dict, "eval")
File "/paddle/PaddleOCR/tools/eval_utils/eval_det_utils.py", line 126, in eval_det_run
cal_det_res(exe, config, eval_info_dict)
File "/paddle/PaddleOCR/tools/eval_utils/eval_det_utils.py", line 59, in cal_det_res
img_list = np.concatenate(img_list, axis=0)
ValueError: all the input array dimensions except for the concatenation axis must match exactly

想问下SRN什么时候能开源？

感谢大佬分享，太强了
请问现在提供的中文模型只有inference.md中的两种吗？

您好，按照文档操作出现如下错误
运行环境 docker-ubuntu 18.04 + cuda10.0 + python3.6.9 + paddle-gpu(1.7.2.post97)
运行命令 export PYTHONPATH=. && python3 tools/infer/predict_system.py --image_dir="./doc/imgs/11.jpg" --det_model_dir="./inference/det/" --rec_model_dir="./inference/rec/"

出现如下错误
Error: Failed to find dynamic library: libcublas.so ( libcublas.so: cannot open shared object file: No such file or directory )
Please specify its path correctly using following ways:
Method. set environment variable LD_LIBRARY_PATH on Linux or DYLD_LIBRARY_PATH on Mac OS.
For instance, issue command: export LD_LIBRARY_PATH=...
Note: After Mac OS 10.11, using the DYLD_LIBRARY_PATH is impossible unless System Integrity Protection (SIP) is disabled. at (/paddle/paddle/fluid/platform/dynload/dynamic_loader.cc:177)

您好，感谢您分享这么好的工作。想请教一下，因为CRNN这种只能处理水平的文字，PaddleOCR是如何处理竖排文字的呢？多谢！

你好, 非常感谢您的项目, 很棒! 我先后跑了检测和识别模型, 当识别模型训练完毕之后, 打算进行单张图片的预测, 因此执行提供的命令, python3 tools/infer_rec.py -c configs/rec/rec_chinese_lite_train.yml -o Global.checkpoints=./output/rec_CRNN/best_accuracy TestReader.infer_img=./doc/imgs_word/word_1.jpg, 但是发生了下面的报错, 可以麻烦帮我看一下原因吗?感谢

2020-05-15 23:06:04,952-INFO: {'Global': {'algorithm': 'CRNN', 'use_gpu': True, 'epoch_num': 3000, 'log_smooth_window': 20, 'print_batch_step': 10, 'save_model_dir': './output/rec_CRNN', 'save_epoch_step': 3, 'eval_batch_step': 2000, 'train_batch_size_per_card': 256, 'test_batch_size_per_card': 256, 'image_shape': [3, 32, 100], 'max_text_length': 25, 'character_type': 'ch', 'character_dict_path': './ppocr/utils/ppocr_keys_v1.txt', 'loss_type': 'ctc', 'reader_yml': './configs/rec/rec_chinese_reader.yml', 'pretrain_weights': './pretrain_models/CRNN/best_accuracy', 'checkpoints': './output/rec_CRNN/best_accuracy', 'save_inference_dir': None}, 'Architecture': {'function': 'ppocr.modeling.architectures.rec_model,RecModel'}, 'Backbone': {'function': 'ppocr.modeling.backbones.rec_mobilenet_v3,MobileNetV3', 'scale': 0.5, 'model_name': 'small'}, 'Head': {'function': 'ppocr.modeling.heads.rec_ctc_head,CTCPredict', 'encoder_type': 'rnn', 'SeqRNN': {'hidden_size': 48}}, 'Loss': {'function': 'ppocr.modeling.losses.rec_ctc_loss,CTCLoss'}, 'Optimizer': {'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 0.0005, 'beta1': 0.9, 'beta2': 0.999}, 'TrainReader': {'reader_function': 'ppocr.data.rec.dataset_traversal,SimpleReader', 'num_workers': 8, 'img_set_dir': './train_data', 'label_file_path': './train_data/rec_gt_train.txt'}, 'EvalReader': {'reader_function': 'ppocr.data.rec.dataset_traversal,SimpleReader', 'img_set_dir': './train_data', 'label_file_path': './train_data/rec_gt_test.txt'}, 'TestReader': {'reader_function': 'ppocr.data.rec.dataset_traversal,SimpleReader', 'infer_img': './doc/imgs_word/word_1.jpg'}} W0515 23:06:05.985396 31885 device_context.cc:237] Please NOTE: device: 0, CUDA Capability: 70, Driver API Version: 10.1, Runtime API Version: 9.0 W0515 23:06:05.989531 31885 device_context.cc:245] device: 0, cuDNN Version: 7.3. Traceback (most recent call last): File "tools/infer_rec.py", line 130, in <module> main() File "tools/infer_rec.py", line 79, in main init_model(config, eval_prog, exe) File "/home/aistudio/ppocr/utils/save_load.py", line 114, in init_model fluid.load(program, path, exe) File "/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/io.py", line 1740, in load v.name, parameter_file_name) AssertionError: Can not find [conv11_se_1_offset] in model file [./output/rec_CRNN/best_accuracy.pdparams]

python3 tools/export_model.py -c configs/det/det_mv3_db.yml -o Global.checkpoints=./ch_lite/det_mv3_db/best_accuracy Global.save_inference_dir=./inference_model/det_db/

will you realease training code?

会有动态图版本吗

可以使用paddlehub运行的PaddleOCR 模块包

det_r50_vd_east.tar    det_east_r50_vd.yml
det_mv3_east.tar    det_east_mv3.yml
det_r50_vd_db.tar    det_db_r50_vd.yml
det_mv3_db.tar    det_db_mv3.yml

您好，能否在推理后，不生成图片至./inference_results/文件夹？

如果说是动态调整，跑了一天一夜，LR还是0.0005，没看到有变化的log

训练crnn，应该在哪里设置lr decay呢

Traceback (most recent call last):
File "train.py", line 112, in
FLAGS = parser.parse_args()
File "/paddle/paddle/program.py", line 49, in parse_args
args.opt = self._parse_opt(args.opt)
File "/paddle/paddle/program.py", line 58, in _parse_opt
k, v = s.split('=')
ValueError: need more than 1 value to unpack

请教一个问题，对于文字检测阶段，在对图片进行标注的时候，有的文字区域离得比较远，语义上也属于两个部分；但是也有排版离得远但是语义上属于同一部分的，在标注的时候应该怎么标注呢？是不管离得远近语义一直就框在一起还是，只以距离衡量？
如果用人的思维考虑语义的话，可能会引入噪声，模型难收敛、或者预测结果不稳定；
如果只是以距离作为指标的话，在下游任务对相同语义的两个或者几个部分，合并起来比较困难。如果只是用规则来合并的话，那就对检测和识别（也可能加入纠错）阶段的准确率要求很高。
请教一下，有什么好的思路呢？

windows使用超轻量模型预测结果不正确，调试代码发现字典解析错误，在character.py文件line 37 中line = line.decode('utf-8').strip("\n")，由于没有删除“/r”在windows中使用时字典解析错误，

谢改db_postprocess.py 131行后入下图132行所示：

运行后，报错信息如下：

谢改db_postprocess.py 47行后入下图48行所示：

再次运行后，报错信息如下：

模型的具体实现代码会开源吗，这个项目大概什么时候release

您好，运行训练命令遇到了以下问题，特来请教。
通过FLAGS_selected_gpus 指定显卡 和 修改train.py里面的place = fluid.CUDAPlace(3) if use_gpu else fluid.CPUPlace()运行训练都会出现这个问题。
运行use_gpu=False也出现了下面的问题。
FLAGS_selected_gpus=3 && python3 tools/train.py -c configs/det/det_mv3_db.yml -o Optimizer.base_lr=0.0001
grep: warning: GREP_OPTIONS is deprecated; please use an alias or script
2020-05-18 09:29:29,797-INFO: {'Architecture': {'function': 'ppocr.modeling.architectures.det_model,DetModel'}, 'TestReader': {'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'single_img_path': None, 'img_set_dir': './train_data/icdar2015/text_localization/', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt', 'test_image_shape': [736, 1280], 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'do_eval': True}, 'Backbone': {'function': 'ppocr.modeling.backbones.det_mobilenet_v3,MobileNetV3', 'model_name': 'large', 'scale': 0.5}, 'Head': {'k': 50, 'function': 'ppocr.modeling.heads.det_db_head,DBHead', 'inner_channels': 96, 'model_name': 'large', 'out_channels': 2}, 'Optimizer': {'beta1': 0.9, 'function': 'ppocr.optimizer,AdamDecay', 'base_lr': 0.0001, 'beta2': 0.999}, 'EvalReader': {'test_image_shape': [736, 1280], 'reader_function': 'ppocr.data.det.dataset_traversal,EvalTestReader', 'img_set_dir': './train_data/icdar2015/text_localization/', 'process_function': 'ppocr.data.det.db_process,DBProcessTest', 'label_file_path': './train_data/icdar2015/text_localization/test_icdar2015_label.txt'}, 'Loss': {'function': 'ppocr.modeling.losses.det_db_loss,DBLoss', 'balance_loss': True, 'beta': 10, 'alpha': 5, 'ohem_ratio': 3, 'main_loss_type': 'DiceLoss'}, 'TrainReader': {'reader_function': 'ppocr.data.det.dataset_traversal,TrainReader', 'num_workers': 8, 'img_set_dir': './train_data/icdar2015/text_localization/', 'process_function': 'ppocr.data.det.db_process,DBProcessTrain', 'label_file_path': './train_data/icdar2015/text_localization/train_icdar2015_label.txt'}, 'PostProcess': {'unclip_ratio': 1.5, 'max_candidates': 1000, 'function': 'ppocr.postprocess.db_postprocess,DBPostProcess', 'thresh': 0.3, 'box_thresh': 0.7}, 'Global': {'save_epoch_step': 200, 'save_inference_dir': None, 'eval_batch_step': 5000, 'log_smooth_window': 20, 'algorithm': 'DB', 'epoch_num': 1200, 'use_gpu': True, 'train_batch_size_per_card': 16, 'image_shape': [3, 640, 640], 'save_model_dir': './output/det_db/', 'save_res_path': './output/det_db/predicts_db.txt', 'checkpoints': None, 'pretrain_weights': './pretrain_models/MobileNetV3_large_x0_5_pretrained/', 'test_batch_size_per_card': 16, 'reader_yml': './configs/det/det_db_icdar15_reader.yml', 'print_batch_step': 2}}
3 640 640
3 640 640
import ujson error: No module named 'ujson' use json
2020-05-18 09:29:33,067-INFO: places would be ommited when DataLoader is not iterable
W0518 09:29:33.928460 5607 device_context.cc:237] Please NOTE: device: 3, CUDA Capability: 75, Driver API Version: 10.2, Runtime API Version: 10.0
W0518 09:29:33.932370 5607 device_context.cc:245] device: 3, cuDNN Version: 7.5.
W0518 09:29:33.932396 5607 device_context.cc:271] WARNING: device: 3. The installed Paddle is compiled with CUDNN 7.6, but CUDNN version in your machine is 7.5, which may cause serious incompatible bug. Please recompile or reinstall Paddle with compatible CUDNN version.
2020-05-18 09:29:35,015-INFO: Loading parameters from ./pretrain_models/MobileNetV3_large_x0_5_pretrained/...
2020-05-18 09:29:35,015-WARNING: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ]
2020-05-18 09:29:35,015-WARNING: ./pretrain_models/MobileNetV3_large_x0_5_pretrained/.pdparams not found, try to load model file saved with [ save_params, save_persistables, save_vars ]
2020-05-18 09:29:35,206-INFO: Finish initing model from ./pretrain_models/MobileNetV3_large_x0_5_pretrained/
I0518 09:29:35.251972 5607 parallel_executor.cc:440] The Program will be executed on CUDA using ParallelExecutor, 8 cards are used, so 8 programs are executed in parallel.
W0518 09:29:48.223284 5607 init.cc:209] Warning: PaddlePaddle catches a failure signal, it may not work properly
W0518 09:29:48.223331 5607 init.cc:211] You could check whether you killed PaddlePaddle thread/process accidentally or report the case to PaddlePaddle
W0518 09:29:48.223345 5607 init.cc:214] The detail failure signal is:

有多少人因为pull不下来而放弃了呢，docker 如何提速呢，有没有非docker使用
PaddleOCR 的方式呢

平台：AI-studio
GPU：v100
被推理的图片大小：150k、1920*1080

使用GPU：约6秒
使用CPU：约8秒

请教：如何提升推理速度？

inference里的是model和params
其他模型下载下来是best_accuracy.pdmodel这种格式，改名报错
Error: Getting 'tensor_desc' is not supported by the type of var double_buffer_0. at (D:\1.7.2\paddle\paddle\fluid\framework\var_desc.cc:209)

在学习过程中，我注意到train.py中判断了一下算法参数algorithm是否在已有范围内，之后就找不到哪里使用了这个参数
我想知道代码是怎么实现选择不同的算法的，求大佬们指点

我安装了 paddlepaddle-gpu==1.7.2.post97，但是运行时报错：
Traceback (most recent call last):
File "tools/infer/predict_system.py", line 116, in
dt_boxes, rec_res = text_sys(img)
File "tools/infer/predict_system.py", line 67, in call
dt_boxes, elapse = self.text_detector(img)
File "/home/import/gh/project/PaddleOCR-develop/tools/infer/predict_det.py", line 109, in call
self.predictor.zero_copy_run()
paddle.fluid.core_avx.EnforceNotMet:

C++ Call Stacks (More useful to developers):

0 std::string paddle::platform::GetTraceBackString<char const*>(char const*&&, char const*, int)
1 paddle::platform::EnforceNotMet::EnforceNotMet(std::__exception_ptr::exception_ptr, char const*, int)
2 cudnnActivationStruct* paddle::platform::ScopedActivationDescriptor::descriptor(std::string const&, double)
3 paddle::operators::CUDNNConvFusionOpKernel::Compute(paddle::framework::ExecutionContext const&) const
4 std::_Function_handler<void (paddle::framework::ExecutionContext const&), paddle::framework::OpKernelRegistrarFunctor<paddle::platform::CUDAPlace, false, 0ul, paddle::operators::CUDNNConvFusionOpKernel, paddle::operators::CUDNNConvFusionOpKernel >::operator()(char const*, char const*, int) const::{lambda(paddle::framework::ExecutionContext const&)#1}>::_M_invoke(std::_Any_data const&, paddle::framework::ExecutionContext const&)
5 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&, paddle::framework::RuntimeContext*) const
6 paddle::framework::OperatorWithKernel::RunImpl(paddle::framework::Scope const&, paddle::platform::Place const&) const
7 paddle::framework::OperatorBase::Run(paddle::framework::Scope const&, paddle::platform::Place const&)
8 paddle::framework::NaiveExecutor::Run()
9 paddle::AnalysisPredictor::ZeroCopyRun()

Python Call Stacks (More useful to users):

File "/root/miniconda3/envs/ocrpy36/lib/python3.6/site-packages/paddle/fluid/framework.py", line 2525, in append_op
attrs=kwargs.get("attrs", None))
File "/root/miniconda3/envs/ocrpy36/lib/python3.6/site-packages/paddle/fluid/layer_helper.py", line 43, in append_op
return self.main_program.current_block().append_op(*args, **kwargs)
File "/root/miniconda3/envs/ocrpy36/lib/python3.6/site-packages/paddle/fluid/layers/nn.py", line 1405, in conv2d
"data_format": data_format,
File "/paddle/PaddleOCR/github/PaddleOCR/ppocr/modeling/backbones/det_mobilenet_v3.py", line 153, in conv_bn_layer
bias_attr=False)
File "/paddle/PaddleOCR/github/PaddleOCR/ppocr/modeling/backbones/det_mobilenet_v3.py", line 98, in call
name='conv1')
File "/paddle/PaddleOCR/github/PaddleOCR/ppocr/modeling/architectures/det_model.py", line 111, in call
conv_feas = self.backbone(image)
File "/paddle/PaddleOCR/github/PaddleOCR/tools/program.py", line 193, in build_export
image, outputs = model(mode='export')
File "tools/export_model.py", line 67, in main
config, eval_program, startup_prog)
File "tools/export_model.py", line 93, in
main()

Error Message Summary:

Error: An error occurred here. There is no accurate error hint for this error yet. We are continuously in the process of increasing hint for this kind of error check. It would be helpful if you could inform us of how this conversion went by opening a github issue. And we will resolve it with high priority.

• New issue link: https://github.com/PaddlePaddle/Paddle/issues/new
• Recommended issue content: all error stack information
  [Hint: CUDNN_STATUS_BAD_PARAM] at (/paddle/paddle/fluid/platform/cudnn_helper.h:463)
  [operator < conv2d_fusion > error]