paddlepaddle / paddleocr Goto Github PK

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

License: Apache License 2.0

Python 78.88% Makefile 0.20% C++ 12.09% Shell 4.93% CMake 0.40% Dockerfile 0.07% Java 2.46% Cython 0.05% C 0.33% Cuda 0.34% HTML 0.01% JavaScript 0.14% C# 0.07%

ocr crnn ocrlite db chineseocr

paddleocr's Introduction

简介

PaddleOCR旨在打造一套丰富、领先、且实用的OCR工具库，助力开发者训练出更好的模型，并应用落地。

📣 近期更新

🔥PaddleOCR 算法模型挑战赛 火热开启！报名时间1/15-3/31，30万元奖金池！快来一展身手吧😎！
🔨2023.11 发布 PP-ChatOCRv2: 一个SDK，覆盖20+高频应用场景，支持5种文本图像智能分析能力和部署，包括通用场景关键信息抽取（快递单、营业执照和机动车行驶证等）、复杂文档场景关键信息抽取（解决生僻字、特殊标点、多页pdf、表格等难点问题）、通用OCR、文档场景专用OCR、通用表格识别。针对垂类业务场景，也支持模型训练、微调和Prompt优化。
🔥2023.8.7 发布 PaddleOCR release/2.7
- 发布PP-OCRv4，提供mobile和server两种模型
  - PP-OCRv4-mobile：速度可比情况下，中文场景效果相比于PP-OCRv3再提升4.5%，英文场景提升10%，80语种多语言模型平均识别准确率提升8%以上
  - PP-OCRv4-server：发布了目前精度最高的OCR模型，中英文场景上检测模型精度提升4.9%，识别模型精度提升2% 可参考快速开始一行命令快速使用，同时也可在飞桨AI套件(PaddleX)中的通用OCR产业方案中低代码完成模型训练、推理、高性能部署全流程
- 发布PP-ChatOCR ,使用融合PP-OCR模型和文心大模型的通用场景关键信息抽取全新方案
🔨2022.11 新增实现4种前沿算法：文本检测 DRRG, 文本识别 RFL, 文本超分Text Telescope，公式识别CAN
2022.10 优化JS版PP-OCRv3模型：模型大小仅4.3M，预测速度提升8倍，配套web demo开箱即用
💥 直播回放：PaddleOCR研发团队详解PP-StructureV2优化策略。微信扫描下方二维码，关注公众号并填写问卷后进入官方交流群，获取直播回放链接与20G重磅OCR学习大礼包（内含PDF转Word应用程序、10种垂类模型、《动手学OCR》电子书等）
🔥2022.8.24 发布 PaddleOCR release/2.6
- 发布PP-StructureV2，系统功能性能全面升级，适配中文场景，新增支持版面复原，支持一行命令完成PDF转Word；
- 版面分析模型优化：模型存储减少95%，速度提升11倍，平均CPU耗时仅需41ms；
- 表格识别模型优化：设计3大优化策略，预测耗时不变情况下，模型精度提升6%；
- 关键信息抽取模型优化：设计视觉无关模型结构，语义实体识别精度提升2.8%，关系抽取精度提升9.1%。
🔥2022.8 发布 OCR场景应用集合：包含数码管、液晶屏、车牌、高精度SVTR模型、手写体识别等9个垂类模型，覆盖通用，制造、金融、交通行业的主要OCR垂类应用。

更多

🌟 特性

支持多种OCR相关前沿算法，在此基础上打造产业级特色模型PP-OCR、PP-Structure和PP-ChatOCRv2，并打通数据生产、模型训练、压缩、预测部署全流程。

上述内容的使用方法建议从文档教程中的快速开始体验

⚡ 快速开始

在线免费体验：
- PP-OCRv4 在线体验地址：https://aistudio.baidu.com/application/detail/7658
- PP-ChatOCRv2 在线体验地址：https://aistudio.baidu.com/application/detail/10368
一行命令快速使用：快速开始（中英文/多语言/文档分析）
移动端demo体验：安装包DEMO下载地址(基于EasyEdge和Paddle-Lite, 支持iOS和Android系统)

📖 技术交流合作

飞桨AI套件(PaddleX)提供了飞桨模型训压推一站式全流程高效率开发平台，其使命是助力AI技术快速落地，愿景是使人人成为AI Developer！
- PaddleX 目前覆盖图像分类、目标检测、图像分割、3D、OCR和时序预测等领域方向，已内置了36种基础单模型，例如RT-DETR、PP-YOLOE、PP-HGNet、PP-LCNet、PP-LiteSeg等；集成了12种实用的产业方案，例如PP-OCRv4、PP-ChatOCR、PP-ShiTu、PP-TS、车载路面垃圾检测、野生动物违禁制品识别等。
- PaddleX 提供了“工具箱”和“开发者”两种AI开发模式。工具箱模式可以无代码调优关键超参，开发者模式可以低代码进行单模型训压推和多模型串联推理，同时支持云端和本地端。
- PaddleX 还支持联创开发，利润分成！目前 PaddleX 正在快速迭代，欢迎广大的个人开发者和企业开发者参与进来，共创繁荣的 AI 技术生态！
PaddleX官网地址：https://aistudio.baidu.com/intro/paddlex
PaddleX官方交流频道：https://aistudio.baidu.com/community/channel/610

📚《动手学OCR》电子书

《动手学OCR》电子书

🚀 开源共建

👫 加入社区：感谢大家长久以来对 PaddleOCR 的支持和关注，与广大开发者共同构建一个专业、和谐、相互帮助的开源社区是 PaddleOCR 的目标。我们非常欢迎各位开发者参与到飞桨社区的开源建设中，加入开源、共建飞桨。为感谢社区开发者在 PaddleOCR release2.7 中做出的代码贡献，我们将为贡献者制作与邮寄开源贡献证书，烦请填写问卷提供必要的邮寄信息。
🤩 社区活动：飞桨开源社区长期运营与发布各类丰富的活动与开发任务，在 PaddleOCR 社区，你可以关注以下社区活动，并选择自己感兴趣的内容参与开源共建：
- 🎁 飞桨套件快乐开源常规赛 | 传送门：OCR 社区常规赛升级版，以建设更好用的 OCR 套件为目标，包括但不限于学术前沿模型训练与推理、打磨优化 OCR 工具与应用项目开发等，任何有利于社区意见流动和问题解决的行为都热切希望大家的参与。让我们共同成长为飞桨套件的重要 Contributor 🎉🎉🎉。
- 💡 新需求征集 | 传送门：你在日常研究和实践深度学习过程中，有哪些你期望的 feature 亟待实现？请按照格式描述你想实现的 feature 和你提出的初步实现思路，我们会定期沟通与讨论这些需求，并将其纳入未来的版本规划中。
- 💬 PP-SIG 技术研讨会 | 传送门：PP-SIG 是飞桨社区开发者由于相同的兴趣汇聚在一起形成的虚拟组织，通过定期召开技术研讨会的方式，分享行业前沿动态、探讨社区需求与技术开发细节、发起社区联合贡献任务。PaddleOCR 希望可以通过 AI 的力量助力任何一位有梦想的开发者实现自己的想法，享受创造价值带来的愉悦。
📑 项目合作：如果你有企业中明确的 OCR 垂类应用需求，我们推荐你使用训压推一站式全流程高效率开发平台 PaddleX，助力 AI 技术快速落地。PaddleX 还支持联创开发，利润分成！欢迎广大的个人开发者和企业开发者参与进来，共创繁荣的 AI 技术生态！

🛠️ PP-OCR系列模型列表（更新中）

模型简介	模型名称	推荐场景	检测模型	方向分类器	识别模型
中英文超轻量PP-OCRv4模型（15.8M）	ch_PP-OCRv4_xx	移动端&服务器端	推理模型 / 训练模型	推理模型 / 训练模型	推理模型 / 训练模型
中英文超轻量PP-OCRv3模型（16.2M）	ch_PP-OCRv3_xx	移动端&服务器端	推理模型 / 训练模型	推理模型 / 训练模型	推理模型 / 训练模型
英文超轻量PP-OCRv3模型（13.4M）	en_PP-OCRv3_xx	移动端&服务器端	推理模型 / 训练模型	推理模型 / 训练模型	推理模型 / 训练模型

超轻量OCR系列更多模型下载（包括多语言），可以参考PP-OCR系列模型下载，文档分析相关模型参考PP-Structure系列模型下载

PaddleOCR场景应用模型

行业	类别	亮点	文档说明	模型下载
制造	数码管识别	数码管数据合成、漏识别调优	光功率计数码管字符识别	下载链接
金融	通用表单识别	多模态通用表单结构化提取	多模态表单识别	下载链接
交通	车牌识别	多角度图像处理、轻量模型、端侧部署	轻量级车牌识别	下载链接

更多制造、金融、交通行业的主要OCR垂类应用模型（如电表、液晶屏、高精度SVTR模型等），可参考场景应用模型下载

📖 文档教程

👀 效果展示 more

PP-OCRv3 中文模型

PP-OCRv3 英文模型

PP-OCRv3 多语言模型

PP-Structure 文档分析

版面分析+表格识别

SER（语义实体识别）

RE（关系提取）

许可证书

本项目的发布受Apache 2.0 license许可认证。

paddleocr's People

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paddleocr's Issues

TypeError: bad argument type for built-in operation

安装imgaug库一直失败，是什么原因呢？

running build_ext
building 'imagecodecs._aec' extension
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/imagecodecs
gcc -pthread -B /root/anaconda3/envs/pp/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -Iimagecodecs -I/root/anaconda3/envs/pp/include/python3.6m -I/root/anaconda3/envs/pp/lib/python3.6/site-packages/numpy/core/include -c imagecodecs/_aec.c -o build/temp.linux-x86_64-3.6/imagecodecs/_aec.o
In file included from /root/anaconda3/envs/pp/lib/python3.6/site-packages/numpy/core/include/numpy/ndarraytypes.h:1832:0,
                 from /root/anaconda3/envs/pp/lib/python3.6/site-packages/numpy/core/include/numpy/ndarrayobject.h:12,
                 from /root/anaconda3/envs/pp/lib/python3.6/site-packages/numpy/core/include/numpy/arrayobject.h:4,
                 from imagecodecs/_aec.c:598:
/root/anaconda3/envs/pp/lib/python3.6/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:17:2: warning: #warning "Using deprecated NumPy API, disable it with " "#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp]
 #warning "Using deprecated NumPy API, disable it with " \
  ^
imagecodecs/_aec.c:602:20: fatal error: libaec.h: No such file or directory
compilation terminated.
error: command 'gcc' failed with exit status 1

请教：推理后，不生成图片至./inference_results/文件夹

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

有多少人因为pull不下来而放弃了呢

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

Segmentation fault (core dumped)

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:

will you realease training code?

学习率如何调整？在yml文件中设置没有改变，一直都是0.0005

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

请问能提供官方版的paddle转pb模型的脚本吗?

期待SRN的开源

如题，期待SRN的开源。

predict_system.py --det_algorithm EAST

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

paddleOCR设置为http服务

你好，请问如何将paddleOCR设置为http server服务？

训练集标注的问题

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？

config中的algorithm参数

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

训练日志

导出识别模型时都是 KeyError: 'predict'

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'

GPU一直没用上

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]

rec_r34_vd_tps_bilstm_attn模型转inference模型失败，请问是什么问题？

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'

使用rec_chinese_lite_train.yml配置文件训练中文数据集效果不好

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

什么时候支持paddle1.8.1

got an unexpected keyword argument 'gradient_clip'

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

竖排文字的处理

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！

ValueError: all the input array dimensions except for the concatenation axis must match exactly

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

是否提供c++接口版本？

现在都是python接口版本，请问是否考虑提供c++接口版本？

中文模型

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？

PaddlePaddle CPU版本，det_mv3_db.yml中use_gpu修改为false后仍报错

(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

实际使用需要240ms左右的时间

图像中文字不多的情况下，实际使用需要240ms左右的时间

lr decay

训练crnn，应该在哪里设置lr decay呢

DB文本检测模型推理有问题

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/

自研算法预计啥时候能出啊

训练检测模型时出现以下错误

Error: Failed to find dynamic library: libcublas.so ( libcublas.so: cannot open shared object file: No such file or directory )

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)

SRN

想问下SRN什么时候能开源？

ocr从业者失业大礼包

Segmentation fault (core dumped)

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:

希望提供一个paddlehub的模型构建脚本

可以使用paddlehub运行的PaddleOCR 模块包

请问想换文档内列出的其他模型怎么换？

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)

关于paddleOCR的推理速度

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？

模型的具体实现代码会开源吗，这个项目大概什么时候release

使用训练好的识别模型进行预测, 报错

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]

动态图

会有动态图版本吗

program.py

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

使用rec_r34_vd_tps_bilstm_ctc模型预测失败，请问如何解决？

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]

报错

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'

Error: Cannot load cudnn shared library. Cannot invoke method cudnnGetVersion at (/paddle/paddle/fluid/platform/dynload/cudnn.cc:63)

检测模型转inference模型，'use_gpu': False，但仍然转换失败

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

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

ocr轻量级模型部署移动端

请问有没有考虑过移动端部署呢？具体是什么流程呢？

inference error

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：

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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。

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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。