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align=\"center\"\u003e\n \u003cimg src=\"https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/main/images/logo.png\" width=\"735\" height =\"200\" alt=\"PaddleX\" align=\"middle\" /\u003e\n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n \u003ca href=\"./LICENSE\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-Apache%202-red.svg\"\u003e\u003c/a\u003e\n \u003ca href=\"\"\u003e\u003cimg src=\"https://img.shields.io/badge/Python-3.8~3.13-blue.svg\"\u003e\u003c/a\u003e\n \u003ca href=\"\"\u003e\u003cimg src=\"https://img.shields.io/badge/OS-Linux%2C%20Windows%2C%20Mac-orange.svg\"\u003e\u003c/a\u003e\n \u003ca href=\"\"\u003e\u003cimg src=\"https://img.shields.io/badge/Hardware-CPU%2C%20GPU%2C%20XPU%2C%20NPU%2C%20MLU%2C%20DCU-yellow.svg\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\u003ch4 align=\"center\"\u003e\n \u003ca href=#-特性\u003e🌟 特性\u003c/a\u003e | \u003ca href=https://aistudio.baidu.com/application/center/app?tag=%E5%85%A8%E9%83%A8\u0026flod=86503\u003e🌐 在线体验\u003c/a\u003e｜\u003ca href=#️-快速开始\u003e🚀 快速开始\u003c/a\u003e | \u003ca href=https://paddlepaddle.github.io/PaddleX/latest/index.html\u003e 📖 文档\u003c/a\u003e | \u003ca href=#-能力支持\u003e 🔥能力支持\u003c/a\u003e | \u003ca href=https://paddlepaddle.github.io/PaddleX/latest/support_list/models_list.html\u003e 📋 模型列表\u003c/a\u003e\n\n\u003c/h4\u003e\n\n\u003ch5 align=\"center\"\u003e\n \u003ca href=\"README.md\"\u003e🇨🇳 简体中文\u003c/a\u003e | \u003ca href=\"README_en.md\"\u003e🇬🇧 English\u003c/a\u003e\u003c/a\u003e\n\u003c/h5\u003e\n\n## 🔍 简介\n\nPaddleX 3.0 是基于飞桨框架构建的低代码开发工具，它集成了众多**开箱即用的预训练模型**，可以实现模型从训练到推理的**全流程开发**，支持国内外**多款主流硬件**，助力AI 开发者进行产业实践。\n\n![PaddleX](https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/main/images/PaddleX_ch.png)\n\n## 🌟 特性\n 🎨 **模型丰富一键调用**：将覆盖文本图像智能分析、OCR、目标检测、时序预测等多个关键领域的 **200+ 飞桨模型**整合为 **33 条模型产线**，通过极简的 Python API 一键调用，快速体验模型效果。同时支持 **39 种单功能模块**，方便开发者进行模型组合使用。\n\n 🚀 **提高效率降低门槛**：实现基于统一命令和图形界面的模型**全流程开发**，打造大小模型结合、大模型半监督学习和多模型融合的[**8 条特色模型产线**](https://aistudio.baidu.com/intro/paddlex)，大幅度降低迭代模型的成本。\n\n 🌐 **多种场景灵活部署**：支持**高性能推理**、**服务化部署**和**端侧部署**等多种部署方式，确保不同应用场景下模型的高效运行和快速响应。\n\n 🔧 **主流硬件高效支持**：支持英伟达 GPU、昆仑芯、昇腾和寒武纪等**多种主流硬件**的无缝切换，确保高效运行。\n\n## 📣 近期更新\n\n🔥🔥 **2025.10.16，发布 PaddleX v3.3.0**，新增能力如下：\n\n- **支持PaddleOCR-VL、PP-OCRv5多语种模型的推理部署能力。**\n\n🔥🔥 **2025.8.20，发布 PaddleX v3.2.0**，新增能力如下：\n\n- **部署能力升级：**\n - **全面支持飞桨框架 3.1.0 和 3.1.1 版本。**\n - **高性能推理支持 CUDA 12，可使用 Paddle Inference、ONNX Runtime 后端推理。**\n - **高稳定性服务化部署方案全面开源，支持用户根据需求对 Docker 镜像和 SDK 进行定制化修改。**\n - 高稳定性服务化部署方案支持通过手动构造HTTP请求的方式调用，该方式允许客户端代码使用任意编程语言编写。\n\n- **重要模型新增：**\n - 新增 PP-OCRv5 英文、泰文、希腊文识别模型的训练、推理、部署。**其中 PP-OCRv5 英文模型较 PP-OCRv5 主模型在英文场景提升 11%，泰文识别模型精度 82.68%，希腊文识别模型精度 89.28%。**\n\n- **Benchmark升级：**\n - **全部产线支持产线细粒度 benchmark，能够测量产线端到端推理时间以及逐层、逐模块的耗时数据，可用于辅助产线性能分析。**\n - **在文档中补充各产线常用配置在主流硬件上的关键指标，包括推理耗时和内存占用等，为用户部署提供参考。**\n\n- **Bug修复：**\n - 修复了当输入图片文件格式不合法时，导致递归调用的问题。\n - 修复了 PP-DocTranslation 和 PP-StructureV3 产线配置文件中图表识别、印章识别、文档预处理参数设置不生效的问题。\n - 修复 PDF 文件在推理结束后未正确关闭的问题。\n\n- **其他升级：**\n - **支持 Windows 用户使用英伟达 50 系显卡，可根据安装文档安装对应版本的 paddle 框架。**\n - **PP-OCR 系列模型支持返回单文字坐标。**\n - 将 `PaddlePredictorOption` 中的 `model_name` 参数移至 `PaddleInfer` 中，改善了用户易用性。\n - 重构了官方模型下载逻辑，新增了 AIStudio、ModelScope 等多模型托管平台。\n\n\n🔥🔥 **2025.6.28，发布 PaddleX v3.1.0**，新增能力如下：\n\n- **重要模型：**\n - **新增PP-OCRv5多语种文本识别模型**，支持法语、西班牙语、葡萄牙语、俄语、韩语等37种语言的文字识别模型的训推流程。**平均精度涨幅超30%。**\n - 升级PP-StructureV3中的**PP-Chart2Table模型**，图表转表能力进一步升级，在内部自建测评集合上指标（RMS-F1）**提升9.36个百分点（71.24% -\u003e 80.60%）**\n- **重要产线：**\n - 新增基于PP-StructureV3和ERNIE 4.5 Turbo的**文档翻译产线PP-DocTranslation，支持翻译Markdown文档、各种复杂版式的PDF文档和文档图像，结果保存为Markdown格式文档。**\n\n\n🔥🔥 **2025.5.20，发布 PaddleX v3.0.0**，相比PaddleX v2.x，核心升级如下：\n\n**丰富的模型库：**\n- **模型丰富：** PaddleX3.0 包含270+模型，涵盖了图像（视频）分类/检测/分割、OCR、语音识别、时序等多种场景。\n- **方案成熟：** PaddleX3.0 基于丰富的模型库，**提供了通用文档解析、关键信息抽取、文档理解、表格识别、通用图像识别等多种重要且成熟的AI解决方案。**\n\n**统一推理接口，重构部署能力：**\n- **推理接口标准化**，降低不同种类模型带来的API接口差异，减少用户学习成本，提升企业落地效率。\n- **提供多模型组合能力**，复杂任务可以通过不同的模型方便地进行组合使用，实现1+1\u003e2 的能力。\n- **部署能力升级，多种模型部署可以使用统一的命令管理，支持多卡推理，支持多卡多实例服务化部署。**\n\n**全面适配飞桨框架3.0：**\n- **全面适配飞桨框架3.0新特性：** 支持编译器训练，训练命令通过追加 `-o Global.dy2st=True` 即可开启编译器训练，在 GPU 上，多数模型训练速度可提升 10% 以上，少部分模型训练速度可以提升 30% 以上。推理方面，模型整体适配飞桨 3.0 中间表示技术（PIR），拥有更加灵活的扩展能力和兼容性，静态图模型存储文件名由 `xxx.pdmodel` 改为 `xxx.json`。\n- **全面支持 ONNX 格式模型：** 支持通过Paddle2ONNX插件转换模型格式。\n\n**重磅能力支撑：**\n- **支撑PP-OCRv5的串联逻辑和多硬件推理、多后端推理、服务化部署能力。**\n- **支撑PP-StructureV3的复杂模型串联和并联的逻辑，首次串联并联共15个模型，实现多模型协同的复杂pipeline。精度在 OmniDocBench 榜单上达到 SOTA 水平。**\n- **支撑PP-ChatOCRv4的大模型串联逻辑，结合文心大模型4.5Turbo，结合新增的PP-DocBee2，关键信息抽取精度相比上一代提升15.7个百分点。**\n\n**多硬件支持：**\n- **整体支持英伟达、英特尔、苹果M系列、昆仑芯、昇腾、寒武纪、海光、燧原等芯片的训练和推理。**\n- **在昇腾上，全面适配的模型达到200个，** 支持OM高性能推理的模型达到21个。此外支持PP-OCRv5、PP-StructureV3等重要模型方案。\n- 在昆仑芯上支持重要分类、检测、OCR类模型（含PP-OCRv5）。\n\n ## 🔠 模型产线说明\n\n **PaddleX 致力于实现产线级别的模型训练、推理与部署。模型产线是指一系列预定义好的、针对特定AI任务的开发流程，其中包含能够独立完成某类任务的单模型（单功能模块）组合。**\n\n\n ## 📊 能力支持\n\n\nPaddleX的各个产线均支持本地**快速推理**，部分模型支持在[AI Studio星河社区](https://aistudio.baidu.com/overview)上进行**在线体验**，您可以快速体验各个产线的预训练模型效果，如果您对产线的预训练模型效果满意，可以直接对产线进行[高性能推理](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/high_performance_inference.html)/[服务化部署](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/serving.html)/[端侧部署](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/on_device_deployment.html)，如果不满意，您也可以使用产线的**二次开发**能力，提升效果。完整的产线开发流程请参考[PaddleX产线使用概览](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/pipeline_develop_guide.html)或各产线使用[教程](#-文档)。\n\n\n此外，PaddleX在[AI Studio星河社区](https://aistudio.baidu.com/overview)为开发者提供了基于[云端图形化开发界面](https://aistudio.baidu.com/pipeline/mine)的全流程开发工具, 点击【创建产线】，选择对应的任务场景和模型产线，就可以开启全流程开发。详细请参考[教程《零门槛开发产业级AI模型》](https://aistudio.baidu.com/practical/introduce/546656605663301)\n\n\u003ctable \u003e\n \u003ctr\u003e\n \u003cth\u003e模型产线\u003c/th\u003e\n \u003cth\u003e在线体验\u003c/th\u003e\n \u003cth\u003e快速推理\u003c/th\u003e\n \u003cth\u003e高性能推理\u003c/th\u003e\n \u003cth\u003e服务化部署\u003c/th\u003e\n \u003cth\u003e端侧部署\u003c/th\u003e\n \u003cth\u003e二次开发\u003c/th\u003e\n \u003cth\u003e\u003ca href = \"https://aistudio.baidu.com/pipeline/mine\"\u003e星河零代码产线\u003c/a\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/OCR.html\"\u003e通用OCR\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/91660/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v3.html\"\u003e文档场景信息抽取v3\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/182491/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v4.html\"\u003e文档场景信息抽取v4\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/518493/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition.html\"\u003e通用表格识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/91661?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/object_detection.html\"\u003e通用目标检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/70230/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/instance_segmentation.html\"\u003e通用实例分割\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/100063/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_classification.html\"\u003e通用图像分类\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/100061/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/semantic_segmentation.html\"\u003e通用语义分割\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/100062/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_forecasting.html\"\u003e时序预测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/105706/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_anomaly_detection.html\"\u003e时序异常检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/105708/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_classification.html\"\u003e时序分类\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/105707/webUI?source=appMineRecent\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/small_object_detection.html\"\u003e小目标检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387975/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_multi_label_classification.html\"\u003e图像多标签分类\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387974/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/formula_recognition.html\"\u003e公式识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387976/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.html\"\u003e印章文本识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387977/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/pedestrian_attribute_recognition.html\"\u003e行人属性识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387978/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/vehicle_attribute_recognition.html\"\u003e车辆属性识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/387979/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_anomaly_detection.html\"\u003e图像异常检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/human_keypoint_detection.html\"\u003e人体关键点检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_detection.html\"\u003e开放词汇检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_segmentation.html\"\u003e开放词汇分割\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/rotated_object_detection.html\"\u003e旋转目标检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/3d_bev_detection.html\"\u003e3D多模态融合检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition_v2.html\"\u003e通用表格识别v2\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/518495/webUI?source=appCenter\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.html\"\u003e通用版面解析\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/PP-StructureV3.html\"\u003e通用版面解析v3\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e\u003ca href = \"https://aistudio.baidu.com/community/app/518494/webUI?source=appCente\"\u003e链接\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/doc_preprocessor.html\"\u003e文档图像预处理\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/general_image_recognition.html\"\u003e通用图像识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/face_recognition.html\"\u003e人脸识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/speech_pipelines/multilingual_speech_recognition.html\"\u003e多语种语音识别\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/video_pipelines/video_classification.html\"\u003e通用视频分类\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/video_pipelines/video_detection.html\"\u003e通用视频检测\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003ca href=\"https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/vlm_pipelines/doc_understanding.html\"\u003e文档理解\u003c/a\u003e\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n\n\n\u003c/table\u003e\n\n\u003e ❗注：以上功能均基于 GPU/CPU 实现。PaddleX 还可在昆仑芯、昇腾、寒武纪和海光等主流硬件上进行快速推理和二次开发。下表详细列出了模型产线的支持情况，具体支持的模型列表请参阅[模型列表(昆仑芯XPU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_xpu.html)/[模型列表(昇腾NPU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_npu.html)/[模型列表(寒武纪MLU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_mlu.html)/[模型列表(海光DCU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_dcu.html)。我们正在适配更多的模型，并在主流硬件上推动高性能和服务化部署的实施。\n\n🔥🔥 **国产化硬件能力支持**\n\n\u003ctable\u003e\n \u003ctr\u003e\n \u003cth\u003e模型产线\u003c/th\u003e\n \u003cth\u003e昇腾 910B\u003c/th\u003e\n \u003cth\u003e昆仑芯 R200/R300\u003c/th\u003e\n \u003cth\u003e寒武纪 MLU370X8\u003c/th\u003e\n \u003cth\u003e海光 Z100/K100AI\u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用OCR\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用表格识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用目标检测\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用实例分割\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用图像分类\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用语义分割\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e时序预测\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e时序异常检测\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e时序分类\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e图像多标签分类\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e行人属性识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e车辆属性识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e通用图像识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e印章文本识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003ctd\u003e🚧\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e图像异常检测\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e人脸识别\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003ctd\u003e✅\u003c/td\u003e\n \u003c/tr\u003e\n\u003c/table\u003e\n\n## ⏭️ 快速开始\n\n### 🛠️ 安装\n\n\u003e ❗在安装 PaddleX 之前，请确保您已具备基本的 **Python 运行环境**（注：目前支持 Python 3.8 至 Python 3.13）。PaddleX 3.0.x 版本依赖的 PaddlePaddle 版本为 3.0.0 及以上版本，请在使用前务必保证版本的对应关系。\n\n* **安装 PaddlePaddle**\n```bash\n# CPU 版本\npython -m pip install paddlepaddle==3.3.0 -i https://www.paddlepaddle.org.cn/packages/stable/cpu/\n\n# GPU 版本，需显卡驱动程序版本 ≥450.80.02（Linux）或 ≥452.39（Windows）\n python -m pip install paddlepaddle-gpu==3.3.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/\n\n# GPU 版本，需显卡驱动程序版本 ≥550.54.14（Linux）或 ≥550.54.14（Windows）\n python -m pip install paddlepaddle-gpu==3.3.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/\n```\n\u003e ❗无需关注物理机上的 CUDA 版本，只需关注显卡驱动程序版本。更多飞桨 Wheel 版本信息，请参考[飞桨官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation./docs/zh/install/pip/linux-pip.html)。\n\n* **安装PaddleX**\n\n```bash\npip install \"paddlex[base]\"\n```\n\n\u003e ❗ 更多安装方式参考 [PaddleX 安装教程](https://paddlepaddle.github.io/PaddleX/latest/installation/installation.html)\n\n### 💻 命令行使用\n\n一行命令即可快速体验产线效果，统一的命令行格式为：\n\n```bash\npaddlex --pipeline [产线名称] --input [输入图片] --device [运行设备]\n```\n\nPaddleX的每一条产线对应特定的参数，您可以在各自的产线文档中查看具体的参数说明。每条产线需指定必要的三个参数：\n* `pipeline`：产线名称或产线配置文件\n* `input`：待处理的输入文件（如图片）的本地路径、目录或 URL\n* `device`：使用的硬件设备及序号（例如`gpu:0`表示使用第 0 块 GPU），也可选择使用 NPU(`npu:0`)、 XPU(`xpu:0`)、CPU(`cpu`)等。\n\n\n以通用 OCR 产线为例：\n```bash\npaddlex --pipeline OCR \\\n --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_002.png \\\n --use_doc_orientation_classify False \\\n --use_doc_unwarping False \\\n --use_textline_orientation False \\\n --save_path ./output \\\n --device gpu:0\n```\n\u003cdetails\u003e\n \u003csummary\u003e\u003cb\u003e👉 点击查看运行结果 \u003c/b\u003e\u003c/summary\u003e\n\n```bash\n{'res': {'input_path': 'general_ocr_002.png', 'page_index': None, 'model_settings': {'use_doc_preprocessor': False, 'use_textline_orientation': False}, 'doc_preprocessor_res': {'input_path': None, 'model_settings': {'use_doc_orientation_classify': True, 'use_doc_unwarping': False}, 'angle': 0},'dt_polys': [array([[ 3, 10],\n [82, 10],\n [82, 33],\n [ 3, 33]], dtype=int16), ...], 'text_det_params': {'limit_side_len': 960, 'limit_type': 'max', 'thresh': 0.3, 'box_thresh': 0.6, 'unclip_ratio': 2.0}, 'text_type': 'general', 'textline_orientation_angles': [-1, ...], 'text_rec_score_thresh': 0.0, 'rec_texts': ['www.99*', ...], 'rec_scores': [0.8980069160461426, ...], 'rec_polys': [array([[ 3, 10],\n [82, 10],\n [82, 33],\n [ 3, 33]], dtype=int16), ...], 'rec_boxes': array([[ 3, 10, 82, 33], ...], dtype=int16)}}\n```\n\n可视化结果如下：\n\n![alt text](https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/main/images/boardingpass.png)\n\n\u003c/details\u003e\n\n其他产线的命令行使用，只需将 `pipeline` 参数调整为相应产线的名称，参数调整为对应的产线的参数即可。下面列出了每个产线对应的命令：\n\n\u003cdetails\u003e\n \u003csummary\u003e\u003cb\u003e👉 更多产线的命令行使用\u003c/b\u003e\u003c/summary\u003e\n\n| 产线名称 | 使用命令 |\n|--------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| 通用图像分类 | `paddlex --pipeline image_classification --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_image_classification_001.jpg --device gpu:0 --save_path ./output/` |\n| 通用目标检测 | `paddlex --pipeline object_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_object_detection_002.png --threshold 0.5 --save_path ./output/ --device gpu:0` |\n| 通用实例分割 | `paddlex --pipeline instance_segmentation --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_instance_segmentation_004.png --threshold 0.5 --save_path ./output --device gpu:0` |\n| 通用语义分割 | `paddlex --pipeline semantic_segmentation --input https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/application/semantic_segmentation/makassaridn-road_demo.png --target_size -1 --save_path ./output --device gpu:0` |\n| 图像多标签分类 | `paddlex --pipeline image_multilabel_classification --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_image_classification_001.jpg --save_path ./output --device gpu:0` |\n| 小目标检测 | `paddlex --pipeline small_object_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/small_object_detection.jpg --threshold 0.5 --save_path ./output --device gpu:0` |\n| 图像异常检测 | `paddlex --pipeline anomaly_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/uad_grid.png --save_path ./output --device gpu:0` |\n| 行人属性识别 | `paddlex --pipeline pedestrian_attribute_recognition --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/pedestrian_attribute_002.jpg --save_path ./output/ --device gpu:0` |\n| 车辆属性识别 | `paddlex --pipeline vehicle_attribute_recognition --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/vehicle_attribute_002.jpg --save_path ./output/ --device gpu:0` |\n| 3D多模态融合检测 | `paddlex --pipeline 3d_bev_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/det_3d/demo_det_3d/nuscenes_demo_infer.tar --device gpu:0 --save_path ./output/` |\n| 人体关键点检测 | `paddlex --pipeline human_keypoint_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/keypoint_detection_001.jpg --det_threshold 0.5 --save_path ./output/ --device gpu:0` |\n| 开放词汇检测 | `paddlex --pipeline open_vocabulary_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/open_vocabulary_detection.jpg --prompt \"bus . walking man . rearview mirror .\" --thresholds \"{'text_threshold': 0.25, 'box_threshold': 0.3}\" --save_path ./output --device gpu:0` |\n| 开放词汇分割 | `paddlex --pipeline open_vocabulary_segmentation --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/open_vocabulary_segmentation.jpg --prompt_type box --prompt \"[[112.9,118.4,513.8,382.1],[4.6,263.6,92.2,336.6],[592.4,260.9,607.2,294.2]]\" --save_path ./output --device gpu:0` |\n| 旋转目标检测 | `paddlex --pipeline rotated_object_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/rotated_object_detection_001.png --threshold 0.5 --save_path ./output --device gpu:0` |\n| 通用OCR | `paddlex --pipeline OCR --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_ocr_002.png --use_doc_orientation_classify False --use_doc_unwarping False --use_textline_orientation False --save_path ./output --device gpu:0` |\n| 文档图像预处理 | `paddlex --pipeline doc_preprocessor --input https://paddle-model-ecology.bj.bcebos.com/paddlex/demo_image/doc_test_rotated.jpg --use_doc_orientation_classify True --use_doc_unwarping True --save_path ./output --device gpu:0` |\n| 通用表格识别 | `paddlex --pipeline table_recognition --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/table_recognition.jpg --save_path ./output --device gpu:0` |\n| 通用表格识别v2 | `paddlex --pipeline table_recognition_v2 --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/table_recognition.jpg --save_path ./output --device gpu:0` |\n| 通用版面解析 | `paddlex --pipeline layout_parsing --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/demo_paper.png --use_doc_orientation_classify False --use_doc_unwarping False --use_textline_orientation False --save_path ./output --device gpu:0` |\n| 通用版面解析v3 | `paddlex --pipeline PP-StructureV3 --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/pp_structure_v3_demo.png --use_doc_orientation_classify False --use_doc_unwarping False --use_textline_orientation False --save_path ./output --device gpu:0` |\n| 公式识别 | `paddlex --pipeline formula_recognition --input https://paddle-model-ecology.bj.bcebos.com/paddlex/demo_image/general_formula_recognition.png --use_layout_detection True --use_doc_orientation_classify False --use_doc_unwarping False --layout_threshold 0.5 --layout_nms True --layout_unclip_ratio 1.0 --layout_merge_bboxes_mode large --save_path ./output --device gpu:0` |\n| 印章文本识别 | `paddlex --pipeline seal_recognition --input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/seal_text_det.png --use_doc_orientation_classify False --use_doc_unwarping False --device gpu:0 --save_path ./output` |\n| 时序预测 | `paddlex --pipeline ts_forecast --input https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_fc.csv --device gpu:0 --save_path ./output` |\n| 时序异常检测 | `paddlex --pipeline ts_anomaly_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_ad.csv --device gpu:0 --save_path ./output` |\n| 时序分类 | `paddlex --pipeline ts_classification --input https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_cls.csv --device gpu:0 --save_path ./output` |\n| 多语种语音识别 | `paddlex --pipeline multilingual_speech_recognition --input https://paddlespeech.bj.bcebos.com/PaddleAudio/zh.wav --save_path ./output --device gpu:0` |\n| 通用视频分类 | `paddlex --pipeline video_classification --input https://paddle-model-ecology.bj.bcebos.com/paddlex/videos/demo_video/general_video_classification_001.mp4 --topk 5 --save_path ./output --device gpu:0` |\n| 通用视频检测 | `paddlex --pipeline video_detection --input https://paddle-model-ecology.bj.bcebos.com/paddlex/videos/demo_video/HorseRiding.avi --device gpu:0 --save_path ./output` |\n\n\n\u003c/details\u003e\n\n### 📝 Python 脚本使用\n\n几行代码即可完成产线的快速推理，统一的 Python 脚本格式如下：\n```python\nfrom paddlex import create_pipeline\n\npipeline = create_pipeline(pipeline=[产线名称])\noutput = pipeline.predict([输入图片名称])\nfor res in output:\n res.print()\n res.save_to_img(\"./output/\")\n res.save_to_json(\"./output/\")\n```\n执行了如下几个步骤：\n\n* `create_pipeline()` 实例化产线对象\n* 传入图片并调用产线对象的 `predict()` 方法进行推理预测\n* 对预测结果进行处理\n\n其他产线的 Python 脚本使用，只需将 `create_pipeline()` 方法的 `pipeline` 参数调整为相应产线的名称，参数调整为对应的产线的参数即可。下面列出了每个产线对应的参数名称及详细的使用解释：\n\u003cdetails\u003e\n \u003csummary\u003e\u003cb\u003e👉 更多产线的Python脚本使用\u003c/b\u003e\u003c/summary\u003e\n\n| 产线名称 | 对应参数 | 详细说明 |\n|--------------------|------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| 文档场景信息抽取v4 | `PP-ChatOCRv4-doc` | [文档场景信息抽取v4产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v4.html#22-本地体验) |\n| 文档场景信息抽取v3 | `PP-ChatOCRv3-doc` | [文档场景信息抽取v3产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v3.html#22-本地体验) |\n| 通用图像分类 | `image_classification` | [通用图像分类产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_classification.html#222-python脚本方式集成) |\n| 通用目标检测 | `object_detection` | [通用目标检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/object_detection.html#222-python脚本方式集成) |\n| 通用实例分割 | `instance_segmentation` | [通用实例分割产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/instance_segmentation.html#222-python脚本方式集成) |\n| 通用语义分割 | `semantic_segmentation` | [通用语义分割产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/semantic_segmentation.html#222-python脚本方式集成) |\n| 图像多标签分类 | `multi_label_image_classification` | [图像多标签分类产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_multi_label_classification.html#22-python脚本方式集成) |\n| 小目标检测 | `small_object_detection` | [小目标检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/small_object_detection.html#22-python脚本方式集成) |\n| 图像异常检测 | `anomaly_detection` | [图像异常检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_anomaly_detection.html#22-python脚本方式集成) |\n| 通用图像识别 | `PP-ShiTuV2` | [通用图像识别Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/general_image_recognition.html#22-python脚本方式集成) |\n| 人脸识别 | `face_recognition` | [人脸识别Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/face_recognition.html#22-python脚本方式集成) |\n| 车辆属性识别 | `vehicle_attribute_recognition` | [车辆属性识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/vehicle_attribute_recognition.html#22-python脚本方式集成) |\n| 行人属性识别 | `pedestrian_attribute_recognition` | [行人属性识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/pedestrian_attribute_recognition.html#22-python脚本方式集成) |\n| 3D多模态融合检测 | `3d_bev_detection` | [3D多模态融合检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/3d_bev_detection.html#222-python脚本方式集成) |\n| 人体关键点检测 | `human_keypoint_detection` | [人体关键点检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/human_keypoint_detection.html#222-python脚本方式集成) |\n| 开放词汇检测 | `open_vocabulary_detection` | [开放词汇检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_detection.html#212-python脚本方式集成) |\n| 开放词汇分割 | `open_vocabulary_segmentation` | [开放词汇分割产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_segmentation.html#212-python脚本方式集成) |\n| 旋转目标检测 | `rotated_object_detection` | [旋转目标检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/rotated_object_detection.html#212-python脚本方式集成) |\n| 通用OCR | `OCR` | [通用OCR产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/OCR.html#222-python脚本方式集成) |\n| 文档图像预处理 | `doc_preprocessor` | [文档图像预处理产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/doc_preprocessor.html#212-python脚本方式集成) |\n| 通用表格识别 | `table_recognition` | [通用表格识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition.html#22-python脚本方式集成) |\n| 通用表格识别v2 | `table_recognition_v2` | [通用表格识别v2产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition_v2.html#22-python脚本方式集成) |\n| 通用版面解析 | `layout_parsing` | [通用版面解析产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.html#22-python脚本方式集成) |\n| 通用版面解析v3 | `PP-StructureV3` | [通用版面解析v3产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/PP-StructureV3.html#22-python脚本方式集成) |\n| 公式识别 | `formula_recognition` | [公式识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/formula_recognition.html#22-python脚本方式集成) |\n| 印章文本识别 | `seal_recognition` | [印章文本识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.html#22-python脚本方式集成) |\n| 时序预测 | `ts_forecast` | [时序预测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_forecasting.html#222-python脚本方式集成) |\n| 时序异常检测 | `ts_anomaly_detection` | [时序异常检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_anomaly_detection.html#222-python脚本方式集成) |\n| 时序分类 | `ts_classification` | [时序分类产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_classification.html#222-python脚本方式集成) |\n| 多语种语音识别 | `multilingual_speech_recognition` | [多语种语音识别产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/multilingual_speech_recognition.html#212-python脚本方式集成) |\n| 通用视频分类 | `video_classification` | [通用视频分类产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/video_classification.html#22-python脚本方式集成) |\n| 通用视频检测 | `video_detection` | [通用视频检测产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/video_detection.html#212-python脚本方式集成) |\n| 文档理解 | `doc_understanding` | [文档理解产线Python脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/vlm_pipelines/doc_understanding.html#211-python脚本方式集成) |\n\n\u003c/details\u003e\n\n\n## 📖 文档\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e ⬇️ 安装 \u003c/b\u003e\u003c/summary\u003e\n\n * [📦 PaddlePaddle 安装教程](https://paddlepaddle.github.io/PaddleX/latest/installation/paddlepaddle_install.html)\n * [📦 PaddleX 安装教程](https://paddlepaddle.github.io/PaddleX/latest/installation/installation.html)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003e \u003cb\u003e 🔥 产线使用 \u003c/b\u003e\u003c/summary\u003e\n\n* [📑 PaddleX 产线使用概览](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/pipeline_develop_guide.html)\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📝 文本图像智能分析 \u003c/b\u003e\u003c/summary\u003e\n\n * [📄 文档场景信息抽取v3产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v3.html)\n\n * [📄 文档场景信息抽取v4产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/information_extraction_pipelines/document_scene_information_extraction_v4.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🔍 OCR \u003c/b\u003e\u003c/summary\u003e\n\n * [📜 通用 OCR 产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/OCR.html )\n\n * [📊 通用表格识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition.html )\n\n * [🗂️ 通用表格识别v2产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/table_recognition_v2.html)\n\n * [📰 通用版面解析产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.html)\n\n * [🗞️ 通用版面解析产线v3使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/PP-StructureV3.html)\n * [📐 公式识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/formula_recognition.html)\n * [📝 印章文本识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.html)\n * [🖌️ 文档图像预处理产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/ocr_pipelines/doc_preprocessor.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🎥 计算机视觉 \u003c/b\u003e\u003c/summary\u003e\n\n * [🖼️ 通用图像分类产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_classification.html)\n\n * [🎯 通用目标检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/object_detection.html)\n\n * [📋 通用实例分割产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/instance_segmentation.html)\n\n * [🗣️ 通用语义分割产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/semantic_segmentation.html)\n\n * [🏷️ 图像多标签分类产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_multi_label_classification.html)\n\n * [🔍 小目标检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/small_object_detection.html)\n\n * [🖼️ 图像异常检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/image_anomaly_detection.html)\n\n * [🌐 3D多模态融合检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/3d_bev_detection.html)\n\n * [🔍 人体关键点检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/human_keypoint_detection.html)\n\n * [📚 开放词汇检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_detection.html)\n\n * [🎨 开放词汇分割产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/open_vocabulary_segmentation.html)\n\n * [🔄 旋转目标检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/rotated_object_detection.html)\n\n * [🖼️ 通用图像识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/general_image_recognition.html)\n\n * [🚶‍♀️ 行人属性识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/pedestrian_attribute_recognition.html)\n\n * [🚗 车辆属性识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/vehicle_attribute_recognition.html)\n\n * [🆔人脸识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/cv_pipelines/face_recognition.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e ⏱️ 时序分析\u003c/b\u003e \u003c/summary\u003e\n\n * [📈 时序预测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_forecasting.html)\n\n * [📉 时序异常检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_anomaly_detection.html)\n\n * [🕒 时序分类产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/time_series_pipelines/time_series_classification.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🎤 语音识别\u003c/b\u003e \u003c/summary\u003e\n\n * [🌐 多语种语音识别产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/speech_pipelines/multilingual_speech_recognition.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🎥 视频识别\u003c/b\u003e \u003c/summary\u003e\n\n * [📈 通用视频分类产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/video_pipelines/video_classification.html)\n\n * [🔍 通用视频检测产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/video_pipelines/video_detection.html)\n\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🌐 多模态视觉语言模型\u003c/b\u003e \u003c/summary\u003e\n\n * [📝 文档理解产线使用教程](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/tutorials/vlm_pipelines/doc_understanding.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e🔧 相关说明文件\u003c/b\u003e \u003c/summary\u003e\n\n * [🖥️ PaddleX 产线命令行使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/instructions/pipeline_CLI_usage.html)\n\n * [📝 PaddleX 产线 Python 脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/instructions/pipeline_python_API.html)\n\n * [🔎 产线并行推理](https://paddlepaddle.github.io/PaddleX/latest/pipeline_usage/instructions/parallel_inference.html)\n\n\u003c/details\u003e\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003e \u003cb\u003e ⚙️ 单功能模块使用 \u003c/b\u003e\u003c/summary\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🔍 OCR \u003c/b\u003e\u003c/summary\u003e\n\n * [📝 文本检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/text_detection.html)\n\n * [🔖 印章文本检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/seal_text_detection.html)\n\n * [🔠 文本识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/text_recognition.html)\n\n * [🗺️ 版面区域检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/layout_detection.html)\n\n * [📊 表格结构识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/table_structure_recognition.html)\n\n * [📊 表格单元格检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/table_cells_detection.html)\n\n * [📈 表格分类模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/table_classification.html)\n\n * [📄 文档图像方向分类使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.html)\n\n * [🔧 文本图像矫正模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/text_image_unwarping.html)\n\n * [📝 文本行方向分类模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/textline_orientation_classification.html)\n\n * [📐 公式识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/ocr_modules/formula_recognition.html)\n\n\n\u003c/details\u003e\n\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🖼️ 图像分类 \u003c/b\u003e\u003c/summary\u003e\n\n * [📂 图像分类模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/image_classification.html)\n\n * [🏷️ 图像多标签分类模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/image_multilabel_classification.html)\n\n * [👤 行人属性识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/pedestrian_attribute_recognition.html)\n\n * [🚗 车辆属性识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/vehicle_attribute_recognition.html)\n\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🏞️ 图像特征 \u003c/b\u003e\u003c/summary\u003e\n\n * [🔗 图像特征模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/image_feature.html)\n\n * [😁 人脸特征模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/face_feature.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🎯 目标检测 \u003c/b\u003e\u003c/summary\u003e\n\n * [🎯 目标检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/object_detection.html)\n\n * [📏 小目标检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/small_object_detection.html)\n\n * [🧑‍🤝‍🧑 人脸检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/face_detection.html)\n\n * [🔍 主体检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/mainbody_detection.html)\n\n * [🚶 行人检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/human_detection.html)\n\n * [🚶‍♂️ 人体关键点检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/human_keypoint_detection.html)\n\n * [🌐 开放词汇目标检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/open_vocabulary_detection.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🖼️ 图像分割 \u003c/b\u003e\u003c/summary\u003e\n\n * [🗺️ 语义分割模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/semantic_segmentation.html)\n\n * [🔍 实例分割模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/instance_segmentation.html)\n\n * [🚨 图像异常检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/anomaly_detection.html)\n\n * [🌐 开放词汇分割模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/open_vocabulary_segmentation.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e ⏱️ 时序分析 \u003c/b\u003e\u003c/summary\u003e\n\n * [📈 时序预测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/time_series_modules/time_series_forecasting.html)\n\n * [🚨 时序异常检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/time_series_modules/time_series_anomaly_detection.html)\n\n * [🕒 时序分类模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/time_series_modules/time_series_classification.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🎤 语音识别 \u003c/b\u003e\u003c/summary\u003e\n\n * [🌐 多语种语音识别模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/speech_modules/multilingual_speech_recognition.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📦 3D \u003c/b\u003e\u003c/summary\u003e\n\n * [📦 3D多模态融合检测模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/cv_modules/3d_bev_detection.html)\n\n\u003c/details\u003e\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🌐 多模态视觉语言模型 \u003c/b\u003e\u003c/summary\u003e\n\n * [📝 文档类视觉语言模型模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/vlm_modules/doc_vlm.html)\n\n * [📈 图表解析模块使用教程](https://paddlepaddle.github.io/PaddleX/latest/module_usage/tutorials/vlm_modules/chart_parsing.html)\n\n\u003c/details\u003e\n\n\n* \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📄 相关说明文件 \u003c/b\u003e\u003c/summary\u003e\n\n * [📝 PaddleX 单模型 Python 脚本使用说明](https://paddlepaddle.github.io/PaddleX/latest/module_usage/instructions/model_python_API.html)\n\n * [📝 PaddleX 通用模型配置文件参数说明](https://paddlepaddle.github.io/PaddleX/latest/module_usage/instructions/config_parameters_common.html)\n\n * [📝 PaddleX 时序任务模型配置文件参数说明](https://paddlepaddle.github.io/PaddleX/latest/module_usage/instructions/config_parameters_time_series.html)\n\n * [📝 PaddleX 3d任务模型配置文件参数说明](https://paddlepaddle.github.io/PaddleX/latest/module_usage/instructions/config_parameters_3d.html)\n\n * [📝 模型推理 Benchmark](https://paddlepaddle.github.io/PaddleX/latest/module_usage/instructions/benchmark.html)\n\n\u003c/details\u003e\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🏗️ 模型产线部署 \u003c/b\u003e\u003c/summary\u003e\n\n * [🚀 PaddleX 高性能推理指南](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/high_performance_inference.html)\n * [🖥️ PaddleX 服务化部署指南](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/serving.html)\n * [📱 PaddleX 端侧部署指南](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/on_device_deployment.html)\n * [🌐 获取 ONNX 模型](https://paddlepaddle.github.io/PaddleX/latest/pipeline_deploy/paddle2onnx.html)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🖥️ 多硬件使用 \u003c/b\u003e\u003c/summary\u003e\n\n * [🔧 多硬件使用指南](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/multi_devices_use_guide.html)\n * [🖲️ 海光 DCU 飞桨安装教程](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/paddlepaddle_install_DCU.html)\n * [🔲 寒武纪 MLU 飞桨安装教程](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/paddlepaddle_install_MLU.html)\n * [💻 昇腾 NPU 飞桨安装教程](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/paddlepaddle_install_NPU.html)\n * [🔌 昆仑 XPU 飞桨安装教程](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/paddlepaddle_install_XPU.html)\n * [📱 燧原 GCU 飞桨安装教程](https://paddlepaddle.github.io/PaddleX/latest/other_devices_support/paddlepaddle_install_GCU.html)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n\u003csummary\u003e \u003cb\u003e 📊 数据标注教程 \u003c/b\u003e\u003c/summary\u003e\n\n- \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 💻 计算机视觉 \u003c/b\u003e\u003c/summary\u003e\n\n - [📂 图像分类任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/image_classification.html)\n\n - [📂 图像特征任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/image_feature.html)\n\n - [📂 实例分割任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/instance_segmentation.html)\n\n - [📂 图像多标签分类模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/ml_classification.html)\n\n - [📂 目标检测任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/object_detection.html)\n\n - [📂 语义分割任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/cv_modules/semantic_segmentation.html)\n\n\u003c/details\u003e\n\n- \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 🔍 OCR \u003c/b\u003e\u003c/summary\u003e\n\n - [📊 表格识别任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/ocr_modules/table_recognition.html)\n\n - [📰 文本检测/识别任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/ocr_modules/text_detection_recognition.html)\n\n\u003c/details\u003e\n\n- \u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📉 时序分析 \u003c/b\u003e\u003c/summary\u003e\n\n - [📈 时序异常检测任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/time_series_modules/time_series_anomaly_detection.html)\n\n - [📉时序分类任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/time_series_modules/time_series_classification.html)\n\n - [🕜 时序预测任务模块](https://paddlepaddle.github.io/PaddleX/latest/data_annotations/time_series_modules/time_series_forecasting.html)\n\n\u003c/details\u003e\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📑 产线列表 \u003c/b\u003e\u003c/summary\u003e\n\n * [🖲️ PaddleX产线列表(CPU/GPU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/pipelines_list.html)\n * [🔲 PaddleX产线列表(DCU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/pipelines_list_dcu.html)\n * [💻 PaddleX产线列表(MLU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/pipelines_list_mlu.html)\n * [🔌 PaddleX产线列表(NPU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/pipelines_list_npu.html)\n * [📱 PaddleX产线列表(XPU)](https://paddlepaddle.github.io/PaddleX/latest/support_list/pipelines_list_xpu.html)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📄 模型列表 \u003c/b\u003e\u003c/summary\u003e\n\n * [🖲️ PaddleX模型列表（CPU/GPU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/models_list.html)\n * [🔲 PaddleX模型列表（海光 DCU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_dcu.html)\n * [💻 PaddleX模型列表（寒武纪 MLU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_mlu.html)\n * [🔌 PaddleX模型列表（昇腾 NPU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_npu.html)\n * [📱 PaddleX模型列表（昆仑 XPU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_xpu.html)\n * [📺 PaddleX模型列表（燧原 GCU）](https://paddlepaddle.github.io/PaddleX/latest/support_list/model_list_gcu.html)\n\n\u003c/details\u003e\n\n\u003cdetails open\u003e\n \u003csummary\u003e \u003cb\u003e 📝 产业实践教程\u0026范例 \u003c/b\u003e\u003c/summary\u003e\n\n* [📑 文档场景信息抽取v3模型产线———论文文献信息抽取应用教程](https://paddlepaddle.github.io/PaddleX/3.0/practical_tutorials/document_scene_information_extraction%28layout_detection%29_tutorial.html)\n\n* [📑 文档场景信息抽取v3模型产线———印章信息抽取应用教程](https://paddlepaddle.github.io/PaddleX/3.0/practical_tutorials/document_scene_information_extraction%28seal_recognition%29_tutorial.html)\n\n* [📑 文档场景信息抽取v3模型产线———DeepSeek 篇](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/document_scene_information_extraction(deepseek)_tutorial.html)\n\n* [🚗 通用 OCR 模型产线———车牌识别教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/ocr_det_license_tutorial.html)\n\n* [✍️ 通用 OCR 模型产线———手写中文识别教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/ocr_rec_chinese_tutorial.html)\n\n* [🔍 公式识别模型产线实践教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/formula_recognition_tutorial.html)\n\n* [💻 版面区域检测模型使用实践教程———大模型训练数据构建教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/layout_detection.html)\n\n* [😊 人脸识别之卡通人脸识别实践教程———卡通人脸识别教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/face_recognition_tutorial.html)\n\n* [🖼️ 通用图像分类模型产线———垃圾分类教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/image_classification_garbage_tutorial.html)\n\n* [🧩 通用实例分割模型产线———遥感图像实例分割教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/instance_segmentation_remote_sensing_tutorial.html)\n\n* [👥 通用目标检测模型产线———行人跌倒检测教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/object_detection_fall_tutorial.html)\n\n* [👗 通用目标检测模型产线———服装时尚元素检测教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/object_detection_fashion_pedia_tutorial.html)\n\n* [🗣️ 通用语义分割模型产线———车道线分割教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/semantic_segmentation_road_tutorial.html)\n\n* [🛠️ 时序异常检测模型产线———设备异常检测应用教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/ts_anomaly_detection.html)\n\n* [🎢 时序分类模型产线———心跳监测时序数据分类应用教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/ts_classification.html)\n\n* [🔋 时序预测模型产线———用电量长期预测应用教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/ts_forecast.html)\n\n* [🔧 产线部署实践教程](https://paddlepaddle.github.io/PaddleX/latest/practical_tutorials/deployment_tutorial.html)\n\n\u003c/details\u003e\n\n## 🤔 FAQ\n\n关于我们项目的一些常见问题解答，请参考[FAQ](https://paddlepaddle.github.io/PaddleX/latest/FAQ.html)。如果您的问题没有得到解答，请随时在 [Issues](https://github.com/PaddlePaddle/PaddleX/issues) 中提出\n## 💬 Discussion\n\n我们非常欢迎并鼓励社区成员在 [Discussions](https://github.com/PaddlePaddle/PaddleX/discussions) 板块中提出问题、分享想法和反馈。无论您是想要报告一个 bug、讨论一个功能请求、寻求帮助还是仅仅想要了解项目的最新动态，这里都是一个绝佳的平台。\n\n\n## 📄 许可证书\n\n本项目的发布受 [Apache 2.0 license](./LICENSE) 许可认证。\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaddlepaddle%2Fpaddlex","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpaddlepaddle%2Fpaddlex","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpaddlepaddle%2Fpaddlex/lists"}