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收集并整理有关OCR的数据集并统一标注格式,以便实验需要

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Todo

  • 提供数据集百度云链接
  • 数据集转换为统一格式(检测和识别)
    • icdar2015
    • MLT2019
    • COCO-Text_v2
    • ReCTS
    • SROIE
    • ArT
    • LSVT
    • Synth800k
    • icdar2017rctw
    • Synth800k
    • MTWI 2018
    • 百度中文场景文字识别
    • mjsynth
    • Synthetic Chinese String Dataset
  • 提供读取脚本

数据集

数据集 主页 适用情况 数据情况 标注形式 说明
ICDAR2015 https://rrc.cvc.uab.es/?ch=4 检测&识别 语言: 英文 train:1,000 test:500 x1, y1, x2, y2, x3, y3, x4, y4, transcription 坐标: x1, y1, x2, y2, x3, y3, x4, y4 transcription : 框内的文字信息
MLT2019 https://rrc.cvc.uab.es/?ch=15 检测&识别 语言: 混合 train:10,000 test:10,000 x1,y1,x2,y2,x3,y3,x4,y4,script,transcription 坐标: x1, y1, x2, y2, x3, y3, x4, y4 script: 文字所属语言 transcription : 框内的文字信息
COCO-Text_v2 https://bgshih.github.io/cocotext/ 检测&识别 语言: 混合 train:43,686 validation:10,000 test:10,000 json
ReCTS https://rrc.cvc.uab.es/?ch=12&com=introduction 检测&识别 语言: 混合 train:20,000 test:5,000 { “chars”: [ {“points”: [x1,y1,x2,y2,x3,y3,x4,y4], “transcription” : “trans1”, "ignore":0 }, {“points”: [x1,y1,x2,y2,x3,y3,x4,y4], “transcription” : “trans2”, " ignore ":0 }], “lines”: [ {“points”: [x1,y1,x2,y2,x3,y3,x4,y4] , “transcription” : “trans3”, "ignore ":0 }], } points: x1,y1,x2,y2,x3,y3,x4,y4 chars: 字符级别的标注 lines: 行级别的标注. transcription : 框内的文字信息 ignore: 0:不忽略,1:忽略
SROIE https://rrc.cvc.uab.es/?ch=13 检测&识别 语言: 英文 train:699 test:400 x1, y1, x2, y2, x3, y3, x4, y4, transcription 坐标: x1, y1, x2, y2, x3, y3, x4, y4 transcription : 框内的文字信息
ArT(已包含Total-Text和SCUT-CTW1500) https://rrc.cvc.uab.es/?ch=14 检测&识别 语言: 混合 train: 5,603 test: 4,563 { “gt_1”: [ {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans1”, “language” : “Latin”, "illegibility": false }, {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans2”, “language” : “Chinese”, "illegibility": false }], } points: x1,y1,x2,y2,x3,y3,x4,y4…xn,yn transcription : 框内的文字信息 language: 语言信息 illegibility: 是否模糊
LSVT https://rrc.cvc.uab.es/?ch=16 检测&识别 语言: 混合 全标注 train: 30,000 test: 20,000 只标注文本 400,000 { “gt_1”: [ {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans1”, "illegibility": false }, {“points”: [[x1, y1], [x2, y2], …, [xn, yn]], “transcription” : “trans2”, "illegibility": false }], } points: x1,y1,x2,y2,x3,y3,x4,y4…xn,yn transcription : 框内的文字信息 illegibility: 是否模糊
Synth800k http://www.robots.ox.ac.uk/~vgg/data/scenetext/ 检测&识别 语言: 英文 800,000 imnames: wordBB: charBB: txt: imnames: 文件名称 wordBB: 24n,每张图像内的文本框 charBB: 24n,每张图像内的字符框 txt: 每张图形内的字符串
icdar2017rctw https://blog.csdn.net/wl1710582732/article/details/89761818 检测&识别 语言: 混合 train:8,034 test:4,229 x1,y1,x2,y2,x3,y3,x4,y4,<识别难易程度>,transcription 坐标: x1, y1, x2, y2, x3, y3, x4, y4 transcription : 框内的文字信息
MTWI 2018 识别: https://tianchi.aliyun.com/competition/entrance/231684/introduction 检测: https://tianchi.aliyun.com/competition/entrance/231685/introduction 检测&识别 语言: 混合 train:10,000 test:10,000 x1, y1, x2, y2, x3, y3, x4, y4, transcription 坐标: x1, y1, x2, y2, x3, y3, x4, y4 transcription : 框内的文字信息
百度中文场景文字识别 https://aistudio.baidu.com/aistudio/competition/detail/20 识别 语言: 混合 train:未统计 test:未统计 h,w,name,value h: 图片高度 w: 图片宽度 name: 图片名 value: 图片上文字
mjsynth http://www.robots.ox.ac.uk/~vgg/data/text/ 识别 语言: 英文 9,000,000 - -
Synthetic Chinese String Dataset 链接:https://pan.baidu.com/s/1jefn4Jh4jHjQdiWoanjKpQ 提取码:spyi 识别 语言: 混合 300k - -

数据生成工具

https://github.com/TianzhongSong/awesome-SynthText

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