From 11f5faf44b8ddfde118137538e53e4e82c769550 Mon Sep 17 00:00:00 2001 From: JetHong <1147925384@qq.com> Date: Sat, 24 Apr 2021 16:18:30 +0800 Subject: [PATCH] add total text (#2608) Co-authored-by: MissPenguin Co-authored-by: littletomatodonkey <2120160898@bit.edu.cn> --- configs/e2e/e2e_r50_vd_pg.yml | 4 ++-- doc/doc_ch/pgnet.md | 8 ++++---- doc/doc_en/pgnet_en.md | 8 ++++---- 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/configs/e2e/e2e_r50_vd_pg.yml b/configs/e2e/e2e_r50_vd_pg.yml index 31960955..8128bde1 100644 --- a/configs/e2e/e2e_r50_vd_pg.yml +++ b/configs/e2e/e2e_r50_vd_pg.yml @@ -72,7 +72,7 @@ Train: dataset: name: PGDataSet data_dir: ./train_data/total_text/train - label_file_list: [./train_data/total_text/train/total_text.txt] + label_file_list: [./train_data/total_text/train/train.txt] ratio_list: [1.0] transforms: - DecodeImage: # load image @@ -96,7 +96,7 @@ Eval: dataset: name: PGDataSet data_dir: ./train_data/total_text/test - label_file_list: [./train_data/total_text/test/total_text.txt] + label_file_list: [./train_data/total_text/test/test.txt] transforms: - DecodeImage: # load image img_mode: RGB diff --git a/doc/doc_ch/pgnet.md b/doc/doc_ch/pgnet.md index 26585386..e79c2388 100644 --- a/doc/doc_ch/pgnet.md +++ b/doc/doc_ch/pgnet.md @@ -83,19 +83,19 @@ python3 tools/infer/predict_e2e.py --e2e_algorithm="PGNet" --image_dir="./doc/im 本节以totaltext数据集为例，介绍PaddleOCR中端到端模型的训练、评估与测试。 ### 准备数据 -下载解压[totaltext](https://github.com/cs-chan/Total-Text-Dataset/blob/master/Dataset/README.md) 数据集到PaddleOCR/train_data/目录，数据集组织结构： +下载解压[totaltext](https://paddleocr.bj.bcebos.com/dataset/total_text.tar) 数据集到PaddleOCR/train_data/目录，数据集组织结构： ``` /PaddleOCR/train_data/total_text/train/ |- rgb/ # total_text数据集的训练数据 - |- gt_0.png + |- img11.jpg | ... - |- total_text.txt # total_text数据集的训练标注 + |- train.txt # total_text数据集的训练标注 ``` total_text.txt标注文件格式如下，文件名和标注信息中间用"\t"分隔： ``` " 图像文件名 json.dumps编码的图像标注信息" -rgb/gt_0.png [{"transcription": "EST", "points": [[1004.0,689.0],[1019.0,698.0],[1034.0,708.0],[1049.0,718.0],[1064.0,728.0],[1079.0,738.0],[1095.0,748.0],[1094.0,774.0],[1079.0,765.0],[1065.0,756.0],[1050.0,747.0],[1036.0,738.0],[1021.0,729.0],[1007.0,721.0]]}, {...}] +rgb/img11.jpg [{"transcription": "ASRAMA", "points": [[214.0, 325.0], [235.0, 308.0], [259.0, 296.0], [286.0, 291.0], [313.0, 295.0], [338.0, 305.0], [362.0, 320.0], [349.0, 347.0], [330.0, 337.0], [310.0, 329.0], [290.0, 324.0], [269.0, 328.0], [249.0, 336.0], [231.0, 346.0]]}, {...}] ``` json.dumps编码前的图像标注信息是包含多个字典的list，字典中的 `points` 表示文本框的四个点的坐标(x, y)，从左上角的点开始顺时针排列。 `transcription` 表示当前文本框的文字，**当其内容为“###”时，表示该文本框无效，在训练时会跳过。** diff --git a/doc/doc_en/pgnet_en.md b/doc/doc_en/pgnet_en.md index 2ab1116c..9c46802b 100644 --- a/doc/doc_en/pgnet_en.md +++ b/doc/doc_en/pgnet_en.md @@ -76,19 +76,19 @@ The visualized end-to-end results are saved to the `./inference_results` folder This section takes the totaltext dataset as an example to introduce the training, evaluation and testing of the end-to-end model in PaddleOCR. ### Data Preparation -Download and unzip [totaltext](https://github.com/cs-chan/Total-Text-Dataset/blob/master/Dataset/README.md) dataset to PaddleOCR/train_data/, dataset organization structure is as follow： +Download and unzip [totaltext](https://paddleocr.bj.bcebos.com/dataset/total_text.tar) dataset to PaddleOCR/train_data/, dataset organization structure is as follow： ``` /PaddleOCR/train_data/total_text/train/ |- rgb/ # total_text training data of dataset - |- gt_0.png + |- img11.png | ... - |- total_text.txt # total_text training annotation of dataset + |- train.txt # total_text training annotation of dataset ``` total_text.txt: the format of dimension file is as follows，the file name and annotation information are separated by "\t"： ``` " Image file name Image annotation information encoded by json.dumps" -rgb/gt_0.png [{"transcription": "EST", "points": [[1004.0,689.0],[1019.0,698.0],[1034.0,708.0],[1049.0,718.0],[1064.0,728.0],[1079.0,738.0],[1095.0,748.0],[1094.0,774.0],[1079.0,765.0],[1065.0,756.0],[1050.0,747.0],[1036.0,738.0],[1021.0,729.0],[1007.0,721.0]]}, {...}] +rgb/img11.jpg [{"transcription": "ASRAMA", "points": [[214.0, 325.0], [235.0, 308.0], [259.0, 296.0], [286.0, 291.0], [313.0, 295.0], [338.0, 305.0], [362.0, 320.0], [349.0, 347.0], [330.0, 337.0], [310.0, 329.0], [290.0, 324.0], [269.0, 328.0], [249.0, 336.0], [231.0, 346.0]]}, {...}] ``` The image annotation after **json.dumps()** encoding is a list containing multiple dictionaries. -- GitLab