update common pre-commit configs and commit the results of running pr…

…e-commit run -a

.gitignore

@@ -31,4 +31,4 @@ paddleocr.egg-info/
 /deploy/android_demo/app/.cxx/
 /deploy/android_demo/app/cache/
 test_tipc/web/models/
-test_tipc/web/node_modules/
+test_tipc/web/node_modules/

.pre-commit-config.yaml

@@ -1,26 +1,22 @@
 repos:
 -   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: a11d9314b22d8f8c7556443875b731ef05965464
+    rev: v4.6.0
     hooks:
+    -   id: check-added-large-files
+        args: ['--maxkb=512']
+    -   id: check-case-conflict
     -   id: check-merge-conflict
     -   id: check-symlinks
     -   id: detect-private-key
-        files: (?!.*paddle)^.*$
     -   id: end-of-file-fixer
-        files: \.md$
     -   id: trailing-whitespace
-        files: \.md$
+        files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|py|md)$
 -   repo: https://github.com/Lucas-C/pre-commit-hooks
-    rev: v1.0.1
+    rev: v1.5.1
     hooks:
-    -   id: forbid-crlf
-        files: \.md$
     -   id: remove-crlf
-        files: \.md$
-    -   id: forbid-tabs
-        files: \.md$
     -   id: remove-tabs
-        files: \.md$
+        files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|py|md)$
 -   repo: local
     hooks:
     -   id: clang-format
@@ -31,7 +27,7 @@ repos:
         files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|cuh|proto)$
 # For Python files
 -   repo: https://github.com/psf/black.git
-    rev: 23.3.0
+    rev: 24.4.2
     hooks:
     -   id: black
         files: (.*\.(py|pyi|bzl)|BUILD|.*\.BUILD|WORKSPACE)$
@@ -47,4 +43,3 @@ repos:
             - --show-source
             - --statistics
         exclude: ^benchmark/|^test_tipc/
-

MANIFEST.in

@@ -7,4 +7,4 @@ recursive-include ppocr/postprocess *.py
 recursive-include tools/infer *.py
 recursive-include tools __init__.py
 recursive-include ppocr/utils/e2e_utils *.py
-recursive-include ppstructure *.py
+recursive-include ppstructure *.py

README.md

@@ -207,12 +207,12 @@ PaddleOCR is being oversight by a [PMC](https://github.com/PaddlePaddle/PaddleOC
 <details open>
 <summary>PP-Structure 文档分析</summary>
 
-- 版面分析+表格识别  
+- 版面分析+表格识别
 <div align="center">
     <img src="./ppstructure/docs/table/ppstructure.GIF" width="800">
 </div>
 
-- SER（语义实体识别）  
+- SER（语义实体识别）
 <div align="center">
     <img src="https://user-images.githubusercontent.com/14270174/185310636-6ce02f7c-790d-479f-b163-ea97a5a04808.jpg" width="600">
 </div>

README_en.md

@@ -119,11 +119,11 @@ PaddleOCR support a variety of cutting-edge algorithms related to OCR, and devel
         - [Mobile](./deploy/lite/readme.md)
         - [Paddle2ONNX](./deploy/paddle2onnx/readme.md)
         - [PaddleCloud](./deploy/paddlecloud/README.md)
-        - [Benchmark](./doc/doc_en/benchmark_en.md)  
+        - [Benchmark](./doc/doc_en/benchmark_en.md)
 - [PP-Structure 🔥](./ppstructure/README.md)
     - [Quick Start](./ppstructure/docs/quickstart_en.md)
     - [Model Zoo](./ppstructure/docs/models_list_en.md)
-    - [Model training](./doc/doc_en/training_en.md)  
+    - [Model training](./doc/doc_en/training_en.md)
         - [Layout Analysis](./ppstructure/layout/README.md)
         - [Table Recognition](./ppstructure/table/README.md)
         - [Key Information Extraction](./ppstructure/kie/README.md)
@@ -136,7 +136,7 @@ PaddleOCR support a variety of cutting-edge algorithms related to OCR, and devel
     - [Text recognition](./doc/doc_en/algorithm_overview_en.md)
     - [End-to-end OCR](./doc/doc_en/algorithm_overview_en.md)
     - [Table Recognition](./doc/doc_en/algorithm_overview_en.md)
-    - [Key Information Extraction](./doc/doc_en/algorithm_overview_en.md)  
+    - [Key Information Extraction](./doc/doc_en/algorithm_overview_en.md)
     - [Add New Algorithms to PaddleOCR](./doc/doc_en/add_new_algorithm_en.md)
 - Data Annotation and Synthesis
     - [Semi-automatic Annotation Tool: PPOCRLabel](https://github.com/PFCCLab/PPOCRLabel/blob/main/README.md)
@@ -188,7 +188,7 @@ PaddleOCR support a variety of cutting-edge algorithms related to OCR, and devel
 <details open>
 <summary>PP-StructureV2</summary>
 
-- layout analysis + table recognition  
+- layout analysis + table recognition
 <div align="center">
     <img src="./ppstructure/docs/table/ppstructure.GIF" width="800">
 </div>
@@ -209,7 +209,7 @@ PaddleOCR support a variety of cutting-edge algorithms related to OCR, and devel
 - RE (Relation Extraction)
 <div align="center">
     <img src="https://user-images.githubusercontent.com/25809855/186094813-3a8e16cc-42e5-4982-b9f4-0134dfb5688d.png" width="600">
-</div>  
+</div>
 
 <div align="center">
     <img src="https://user-images.githubusercontent.com/14270174/185393805-c67ff571-cf7e-4217-a4b0-8b396c4f22bb.jpg" width="600">

applications/PCB字符识别/PCB字符识别.md

@@ -546,7 +546,7 @@ python3 tools/infer/predict_system.py  \
     --use_gpu=True
 ```
 
-得到保存结果，文本检测识别可视化图保存在`det_rec_infer/`目录下，预测结果保存在`det_rec_infer/system_results.txt`中，格式如下：`0018.jpg	[{"transcription": "E295", "points": [[88, 33], [137, 33], [137, 40], [88, 40]]}]`
+得到保存结果，文本检测识别可视化图保存在`det_rec_infer/`目录下，预测结果保存在`det_rec_infer/system_results.txt`中，格式如下：`0018.jpg   [{"transcription": "E295", "points": [[88, 33], [137, 33], [137, 40], [88, 40]]}]`
 
 2）然后将步骤一保存的数据转换为端对端评测需要的数据格式： 修改 `tools/end2end/convert_ppocr_label.py`中的代码，convert_label函数中设置输入标签路径，Mode，保存标签路径等，对预测数据的GTlabel和预测结果的label格式进行转换。
 ```

applications/PCB字符识别/gen_data/corpus/text.txt

@@ -27,4 +27,4 @@ K06
 KIEY
 NZQJ
 UN1B
-6X4
+6X4

applications/中文表格识别.md

@@ -456,7 +456,7 @@ display(HTML('<html><body><table><tr><td colspan="5">alleadersh</td><td rowspan=
 
 预测结果如下：
 ```
-val_9.jpg:	 {'attributes': ['Scanned', 'Little', 'Black-and-White', 'Clear', 'Without-Obstacles', 'Horizontal'], 'output': [1, 1, 1, 1, 1, 1]}
+val_9.jpg:   {'attributes': ['Scanned', 'Little', 'Black-and-White', 'Clear', 'Without-Obstacles', 'Horizontal'], 'output': [1, 1, 1, 1, 1, 1]}
 ```
 
 
@@ -466,7 +466,7 @@ val_9.jpg:	 {'attributes': ['Scanned', 'Little', 'Black-and-White', 'Clear', 'Wi
 
 预测结果如下：
 ```
-val_3253.jpg:	 {'attributes': ['Photo', 'Little', 'Black-and-White', 'Blurry', 'Without-Obstacles', 'Tilted'], 'output': [0, 1, 1, 0, 1, 0]}
+val_3253.jpg:    {'attributes': ['Photo', 'Little', 'Black-and-White', 'Blurry', 'Without-Obstacles', 'Tilted'], 'output': [0, 1, 1, 0, 1, 0]}
 ```
 
 对比两张图片可以发现，第一张图片比较清晰，表格属性的结果也偏向于比较容易识别，我们可以更相信表格识别的结果，第二张图片比较模糊，且存在倾斜现象，表格识别可能存在错误，需要我们人工进一步校验。通过表格的属性识别能力，可以进一步将“人工”和“智能”很好的结合起来，为表格识别能力的落地的精度提供保障。

applications/光功率计数码管字符识别/光功率计数码管字符识别.md

@@ -434,16 +434,16 @@ python3 -m paddle.distributed.launch --gpus '0' tools/eval.py -c configs/rec/PP-
 
 ```
 output/rec/
-├── best_accuracy.pdopt  
-├── best_accuracy.pdparams  
-├── best_accuracy.states  
-├── config.yml  
-├── iter_epoch_3.pdopt  
-├── iter_epoch_3.pdparams  
-├── iter_epoch_3.states  
-├── latest.pdopt  
-├── latest.pdparams  
-├── latest.states  
+├── best_accuracy.pdopt
+├── best_accuracy.pdparams
+├── best_accuracy.states
+├── config.yml
+├── iter_epoch_3.pdopt
+├── iter_epoch_3.pdparams
+├── iter_epoch_3.states
+├── latest.pdopt
+├── latest.pdparams
+├── latest.states
 └── train.log
 ```
 

applications/包装生产日期识别.md

@@ -243,7 +243,7 @@ def get_cropus(f):
     elif 0.7 < rad < 0.8:
         f.write('20{:02d}-{:02d}-{:02d}'.format(year, month, day))
     elif 0.8 < rad < 0.9:
-        f.write('20{:02d}.{:02d}.{:02d}'.format(year, month, day))  
+        f.write('20{:02d}.{:02d}.{:02d}'.format(year, month, day))
     else:
         f.write('{:02d}:{:02d}:{:02d} {:02d}'.format(hours, minute, second, file_id2))
 

applications/印章弯曲文字识别.md

@@ -409,7 +409,7 @@ def crop_seal_from_img(label_file, data_dir, save_dir, save_gt_path):
 
 
 
-if __name__ == "__main__":  
+if __name__ == "__main__":
 
     # 数据处理
     gen_extract_label("./seal_labeled_datas", "./seal_labeled_datas/Label.txt", "./seal_ppocr_gt/seal_det_img.txt", "./seal_ppocr_gt/seal_ppocr_img.txt")
@@ -523,7 +523,7 @@ def gen_xml_label(mode='train'):
         xml_file = open(("./seal_VOC/Annotations" + '/' + i_name + '.xml'), 'w')
         xml_file.write('<annotation>\n')
         xml_file.write('    <folder>seal_VOC</folder>\n')
-        xml_file.write('    <filename>' + str(img_name) + '</filename>\n')  
+        xml_file.write('    <filename>' + str(img_name) + '</filename>\n')
         xml_file.write('    <path>' + 'Annotations/' + str(img_name) + '</path>\n')
         xml_file.write('    <size>\n')
         xml_file.write('        <width>' + str(width) + '</width>\n')
@@ -553,7 +553,7 @@ def gen_xml_label(mode='train'):
             xml_file.write('            <ymax>'+str(ymax)+'</ymax>\n')
             xml_file.write('        </bndbox>\n')
             xml_file.write('    </object>\n')
-        xml_file.write('</annotation>')  
+        xml_file.write('</annotation>')
         xml_file.close()
     print(f'{mode} xml save done!')
 

applications/多模态表单识别.md

@@ -110,12 +110,12 @@ tar -xf XFUND.tar
 
 ```bash
 /home/aistudio/PaddleOCR/ppstructure/vqa/XFUND
-  └─ zh_train/        		 	训练集
-      ├── image/				图片存放文件夹
-      ├── xfun_normalize_train.json 	标注信息
-  └─ zh_val/        		 	验证集
-      ├── image/			图片存放文件夹
-      ├── xfun_normalize_val.json 	标注信息
+  └─ zh_train/                  训练集
+      ├── image/              图片存放文件夹
+      ├── xfun_normalize_train.json   标注信息
+  └─ zh_val/                    验证集
+      ├── image/          图片存放文件夹
+      ├── xfun_normalize_val.json     标注信息
 
 ```
 
@@ -805,7 +805,7 @@ CUDA_VISIBLE_DEVICES=0 python3 tools/infer_vqa_token_ser_re.py \
 最终会在config.Global.save_res_path字段所配置的目录下保存预测结果可视化图像以及预测结果文本文件，预测结果文本文件名为infer_results.txt, 每一行表示一张图片的结果，每张图片的结果如下所示，前面表示测试图片路径，后面为测试结果：key字段及对应的value字段。
 
 ```
-test_imgs/t131.jpg	{"政治面税": "群众", "性别": "男", "籍贯": "河北省邯郸市", "婚姻状况": "亏末婚口已婚口已娇", "通讯地址": "邯郸市阳光苑7号楼003", "民族": "汉族", "毕业院校": "河南工业大学", "户口性质": "口农村城镇", "户口地址": "河北省邯郸市", "联系电话": "13288888888", "健康状况": "健康", "姓名": "小六", "好高cm": "180", "出生年月": "1996年8月9日", "文化程度": "本科", "身份证号码": "458933777777777777"}
+test_imgs/t131.jpg  {"政治面税": "群众", "性别": "男", "籍贯": "河北省邯郸市", "婚姻状况": "亏末婚口已婚口已娇", "通讯地址": "邯郸市阳光苑7号楼003", "民族": "汉族", "毕业院校": "河南工业大学", "户口性质": "口农村城镇", "户口地址": "河北省邯郸市", "联系电话": "13288888888", "健康状况": "健康", "姓名": "小六", "好高cm": "180", "出生年月": "1996年8月9日", "文化程度": "本科", "身份证号码": "458933777777777777"}
 ````
 
 展示预测结果