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  3. PaddleOCR 算法模型挑战赛 - 赛题一:OCR 端到端识别任务

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Baidu AI StudioComputer VisionIntermediateRegistration unverifiedRegistration unverified

PaddleOCR 算法模型挑战赛 - 赛题一:OCR 端到端识别任务

适合已做过通用场景 OCR、能同时处理文本检测和文本识别的开发者或团队。需要能使用 PaddlePaddle/PaddleOCR 训练模型,并能将检测框坐标和对应文本按规定格式输出;若目标是进入决赛,还应能完成 AtomGit 代码开源和线下答辩。

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Suggested next step

Decide whether this contest fits your current stage before you sink time into the leaderboard.

Beginner score

55/100

Higher means a safer real starting point for your current stage.

Learning value

58/100

Measures whether the competition teaches habits you can transfer elsewhere.

Estimated effort

10-30 hours

Use this to check whether the task fits your current time budget.

Metric

Official scoring is published on the Ba…

If you cannot explain this metric clearly yet, you probably still need a bit of prep.

Who this competition fits

适合已做过通用场景 OCR、能同时处理文本检测和文本识别的开发者或团队。需要能使用 PaddlePaddle/PaddleOCR 训练模型,并能将检测框坐标和对应文本按规定格式输出;若目标是进入决赛,还应能完成 AtomGit 代码开源和线下答辩。

Official blurb (unedited)
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。作为飞桨开源社区最热门的套件开源项目,PaddleOCR 拥有业界领先的 PP-OCR 模型和多场景通用的表格识别模型,广受众多开发者和用户的认可和使用。本次算法模型挑战赛聚焦通用 OCR 模型,要求开发者以当前飞桨开源模型为基线,不断突破技术瓶颈,研发出更加高效准确的新模型。 Official tags: 通用 OCR 模型. Sign-ups: 426.

Prep before joining

If the items below still feel unfamiliar, you usually get a better result by preparing first instead of rushing in.

PaddlePaddle 训练与推理

OCR 文本检测与识别

文本行四点坐标预测

PaddleOCR 模型部署

Python 3.7 兼容开发

JSONL 结果文件生成

Where the real difficulty shows up

The real friction is usually not library usage. It is validation, time allocation, and task framing.

难点不只是提升端到端识别效果,还要在与官方基线速度差距合理的条件下完成模型优化。B 榜还要求提交可在指定 PaddlePaddle 与 Python 环境中运行的模型包;若改动后处理,则必须提供能自动生成 result.txt 的 predict.py 和依赖配置。

Read this first

This guide is the best pre-read if you want a cleaner start instead of trial-and-error.

A pre-flight checklist for image competitions when you only have free cloud GPU access.

Your First CV Baseline Checklist

Your decision

Use these fields to make a quick decision before you dive deeper.

Status
Registration unverified
Registration
Registration unverified
Eligibility
Needs official confirmation
Reward
¥200,000
Compute
Single GPU
Official metric
Official scoring is published on the Baidu AI Studio competition page.
Verification
Source page verified

Registration is unverified; confirm availability on the official page before investing.

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Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win — report anything that looks wrong.

Source page verifiedMetric confirmedReviewed
Published on this site
Jul 21, 2026

Official metric is not published on the Baidu AI Studio competition listing; verify scoring on the competition page.