PaddleOCR
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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 de...
Team, please help to fix the issue below...I am getting when running the custom detection training: [2022/08/10 21:34:29] ppocr INFO: train with paddle 2.3.1 and device Place(cpu) [2022/08/10 21:34:29] ppocr...
我在开发一个小应用,需要识别出来的每个字符在文本行中的像素位置,请问paddleocr推理的结果中有这个信息吗?
然后acc就会远远低于之前训练好的模型
Hi. Is it possible to load the previously-annotated labels by PPOCRLabelv2 and modify them?
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 - 系统环境/System Environment: Intel CPU Ubuntu 20.04 - 版本号/Version:Paddle: PaddleOCR: 问题相关组件/Related components: paddleOCR 2.5.0.3 First of all, thank you very...
Fixed Loggers related functions in program.py In addition the old script break when running and inference incase the config had wandb enabled since it was using save_model_dir parameter which is...
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 - 系统环境/System Environment: - 版本号/Version:Paddle: PaddleOCR: 问题相关组件/Related components: - 运行指令/Command Code: - 完整报错/Complete Error Message:
通过预定义文件(docvqa_predefine.py)为Label.txt 增加关系抽取(RE),直观地就是增加id、linking属性,并修改key_cls为question、answer或other。以PPLabelOCRLabel V3的Label.txt新格式要求实现RE( 移除xfund格式、移除切分文本)。
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 - 系统环境/System Environment:Windows 11 x64 with Python 3.10.5 - 运行指令/Command Code:pip install opencv-contrib-python==4.4.0.46 使用 pip 安装 paddleocr 时一直报错,发现是 4.4.0.46 版本的...
训练OCR的图片的大小基本是小于50K左右的图片,分辨率大概是200多×200多,使用ResNet50_vd_ssld_pretrained对数据进行训练,训练的图片数据是1385张,训练的次数是1200次 test文件夹的图片是277张,train文件夹的图片是1108张,训练的是det的模型 - 系统环境/System Environment:windows10 - 版本号/Version:Paddle: PaddleOCR: release/2.5 训练结束时的显示的训练结果 [2022/08/04 15:14:42] ppocr INFO: epoch: [1200/1200], global_step: 265160, lr: 0.001000, loss: 0.139509, loss_shrink_maps: 0.065475, loss_threshold_maps: 0.063840, loss_binary_maps: 0.013063, avg_reader_cost: 0.26215...