diff --git a/doc/doc_ch/FAQ.md b/doc/doc_ch/FAQ.md index 752a4adbf09e41fc19a892e6f491f5d09cc938d3..648cf23859dd075206a30322c1ee643391f1e9fd 100644 --- a/doc/doc_ch/FAQ.md +++ b/doc/doc_ch/FAQ.md @@ -40,7 +40,7 @@ PaddleOCR已完成Windows和Mac系统适配，运行时注意两点：1、在[ 英文数据集，MJSynth和SynthText合成数据，数据量上千万。 中文数据集，LSVT街景数据集根据真值将图crop出来，并进行位置校准，总共30w张图像。此外基于LSVT的语料，合成数据500w。 - 其中，公开数据集都是开源的，用户可自行搜索下载，也可参考[中文数据集](./datasets.md)，合成数据暂不开源，用户可使用开源合成工具自行合成，可参考的合成工具包括[text_renderer](https://github.com/Sanster/text_renderer)、[SynthText](https://github.com/ankush-me/SynthText)、[TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator)等。 + 其中，公开数据集都是开源的，用户可自行搜索下载，也可参考[中文数据集](./datasets.md)，合成数据暂不开源，用户可使用开源合成工具自行合成，可参考的合成工具包括[text_renderer](https://github.com/oh-my-ocr/text_renderer)、[SynthText](https://github.com/ankush-me/SynthText)、[TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator)等。 10. **使用带TPS的识别模型预测报错** 报错信息：Input(X) dims[3] and Input(Grid) dims[2] should be equal, but received X dimension[3](320) != Grid dimension[2](100) diff --git a/doc/doc_ch/data_synthesis.md b/doc/doc_ch/data_synthesis.md index a5b9c4aca0bd5a0795b297c31161717aff2c298b..5cda3f3565138e67c48c60e9519756ace6d78252 100644 --- a/doc/doc_ch/data_synthesis.md +++ b/doc/doc_ch/data_synthesis.md @@ -1,6 +1,6 @@ ## 数据合成工具 除了开源数据，用户还可使用合成工具自行合成。这里整理了常用的数据合成工具，持续更新中，欢迎各位小伙伴贡献工具～ -- [text_renderer](https://github.com/Sanster/text_renderer) +- [text_renderer](https://github.com/oh-my-ocr/text_renderer) - [SynthText](https://github.com/ankush-me/SynthText) - [SynthText_Chinese_version](https://github.com/JarveeLee/SynthText_Chinese_version) - [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator) diff --git a/doc/doc_en/FAQ_en.md b/doc/doc_en/FAQ_en.md index a89567f7d912c815d802f021bf8b751f7d94e25c..25ec3147723d0cbce8ccb49f36bd51688f5bb97f 100644 --- a/doc/doc_en/FAQ_en.md +++ b/doc/doc_en/FAQ_en.md @@ -42,7 +42,7 @@ At present, the open source model, dataset and magnitude are as follows: English dataset: MJSynth and SynthText synthetic dataset, the amount of data is tens of millions. Chinese dataset: LSVT street view dataset with cropped text area, a total of 30w images. In addition, the synthesized data based on LSVT corpus is 500w. - Among them, the public datasets are opensourced, users can search and download by themselves, or refer to [Chinese data set](./datasets_en.md), synthetic data is not opensourced, users can use open-source synthesis tools to synthesize data themselves. Current available synthesis tools include [text_renderer](https://github.com/Sanster/text_renderer), [SynthText](https://github.com/ankush-me/SynthText), [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator), etc. + Among them, the public datasets are opensourced, users can search and download by themselves, or refer to [Chinese data set](./datasets_en.md), synthetic data is not opensourced, users can use open-source synthesis tools to synthesize data themselves. Current available synthesis tools include [text_renderer](https://github.com/oh-my-ocr/text_renderer), [SynthText](https://github.com/ankush-me/SynthText), [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator), etc. 10. **Error in using the model with TPS module for prediction** Error message: Input(X) dims[3] and Input(Grid) dims[2] should be equal, but received X dimension[3](108) != Grid dimension[2](100) diff --git a/doc/doc_en/data_synthesis_en.md b/doc/doc_en/data_synthesis_en.md index 81b19d538d7c680ff0a73d7bff204ca667fdc552..6dff484b01b4ee331e9716675364791f9585468d 100644 --- a/doc/doc_en/data_synthesis_en.md +++ b/doc/doc_en/data_synthesis_en.md @@ -3,7 +3,7 @@ In addition to open source data, users can also use synthesis tools to synthesize data. There are the commonly used data synthesis tools, which will be continuously updated. Welcome to contribute tools~ -* [Text_renderer](https://github.com/Sanster/text_renderer) +* [Text_renderer](https://github.com/oh-my-ocr/text_renderer) * [SynthText](https://github.com/ankush-me/SynthText) * [SynthText_Chinese_version](https://github.com/JarveeLee/SynthText_Chinese_version) * [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator) diff --git a/doc/doc_en/datasets_en.md b/doc/doc_en/datasets_en.md index 61d2033b4fe8f0077ad66fb9ae2cd559ce29fd65..7ec73b3d8b014f4b1594542039237d6648039f81 100644 --- a/doc/doc_en/datasets_en.md +++ b/doc/doc_en/datasets_en.md @@ -6,7 +6,7 @@ This is a collection of commonly used Chinese datasets, which is being updated c - [Chinese Document Text Recognition](#中文文档文字识别) - [ICDAR2019-ArT](#ICDAR2019-ArT) -In addition to opensource data, users can also use synthesis tools to synthesize data themselves. Current available synthesis tools include [text_renderer](https://github.com/Sanster/text_renderer), [SynthText](https://github.com/ankush-me/SynthText), [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator), etc. +In addition to opensource data, users can also use synthesis tools to synthesize data themselves. Current available synthesis tools include [text_renderer](https://github.com/oh-my-ocr/text_renderer), [SynthText](https://github.com/ankush-me/SynthText), [TextRecognitionDataGenerator](https://github.com/Belval/TextRecognitionDataGenerator), etc. #### 1. ICDAR2019-LSVT