diff --git a/api/README.md b/api/README.md
index 3970b5854..7cf717fd0 100644
--- a/api/README.md
+++ b/api/README.md
@@ -1,142 +1 @@
-## RapidOCR API
-
-
- 
- 
- 
- 
-
-
-- 采用`FastAPI` + `uvicorn`实现。
-- 该模块定位是一个快速搭建示例的demo，没有考虑多进程处理并发请求，如果有这需求的小伙伴，可以看看gunicorn等。
-
-### 使用步骤
-1. 安装`rapidocr_api`
- ```bash
- $ pip install rapidocr_api
-
- # 源码安装
- $ python setup.py bdist_wheel v0.0.1
- $ cd dist
- $ pip install rapidocr_*.whl
- ```
-2. 运行
- - 用法:
- ```bash
- $ rapidocr_api -h
- usage: rapidocr_api [-h] [-ip IP] [-p PORT]
-
- optional arguments:
- -h, --help show this help message and exit
- -ip IP, --ip IP IP Address
- -p PORT, --port PORT IP port
- ```
- - 示例:
- ```bash
- $ rapidocr_api -ip 0.0.0.0 -p 9003
- ```
-3. 使用
- - ⚠️：本质就是发送一个POST请求，其他语言同理
- - curl调用
- ```bash
- $ curl -F image_file=@1.png http://0.0.0.0:9003/ocr
- ```
- - python调用
- - 以文件的方式发送请求
- ```python
- import requests
-
- url = 'http://localhost:9003/ocr'
- img_path = '../python/tests/test_files/ch_en_num.jpg'
-
- with open(img_path, 'rb') as f:
- file_dict = {'image_file': (img_path, f, 'image/png')}
- response = requests.post(url, files=file_dict, timeout=60)
-
- print(response.json())
- ```
- - 以`base64`方式发送post请求
- ```python
- import base64
- import requests
-
- url = 'http://localhost:9003/ocr'
- img_path = '../python/tests/test_files/ch_en_num.jpg'
-
- with open(img_path, 'rb') as fa:
- img_str = base64.b64encode(fa.read())
-
- payload = {'image_data': img_str}
- resp = requests.post(url, data=payload)
-
- print(resp.json())
- ```
-4. API输出
- - 示例结果：
-
- 详情
-
- ```json
- {
- "0": {
- "rec_txt": "8月26日！",
- "dt_boxes": [
- [333.0, 72.0],
- [545.0, 40.0],
- [552.0, 90.0],
- [341.0, 122.0]
- ],
- "score": "0.7342076812471662"
- },
- "1": {
- "rec_txt": "澳洲名校招生信息",
- "dt_boxes": [
- [266.0, 163.0],
- [612.0, 116.0],
- [619.0, 163.0],
- [272.0, 210.0]
- ],
- "score": "0.8261737492349412"
- },
- "2": {
- "rec_txt": "解读！！",
- "dt_boxes": [
- [341.0, 187.0],
- [595.0, 179.0],
- [598.0, 288.0],
- [344.0, 296.0]
- ],
- "score": "0.6152311325073242"
- },
- "3": {
- "rec_txt": "Rules...",
- "dt_boxes": [
- [446.0, 321.0],
- [560.0, 326.0],
- [559.0, 352.0],
- [445.0, 347.0]
- ],
- "score": "0.8704230123096042"
- }
- }
- ```
-
-
- - 输出结果说明：
- - 如果图像中存在文字，则会输出字典格式，具体介绍如下：
- ```python
- {
- "0": {
- "rec_txt": "香港深圳抽血，", # 识别的文本
- "dt_boxes": [ # 依次为左上角 → 右上角 → 右下角 → 左下角
- [265, 18],
- [472, 231],
- [431, 271],
- [223, 59]
- ],
- "score": "0.8175641223788261" # 置信度
- }
- }
- ```
- - 如果没有检测到文字，则会输出空json(`{}`)。
-5. **!!说明：OCR的输出结果为最原始结果，大家可按需进一步扩展。**
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr_api/)
diff --git a/docs/doc_whl_rapidocr_api.md b/docs/doc_whl_rapidocr_api.md
index 3a9825d3e..7cf717fd0 100644
--- a/docs/doc_whl_rapidocr_api.md
+++ b/docs/doc_whl_rapidocr_api.md
@@ -1,135 +1 @@
-## rapidocr-api
-
-
-
-
-
-
-
-### Use
-1. Install`rapidocr_api`
- ```bash
- $ pip install rapidocr_api
- ```
-2. Run
- - Usage:
- ```bash
- $ rapidocr_api -h
- usage: rapidocr_api [-h] [-ip IP] [-p PORT]
-
- optional arguments:
- -h, --help show this help message and exit
- -ip IP, --ip IP IP Address
- -p PORT, --port PORT IP port
- ```
- - Example:
- ```bash
- $ rapidocr_api -ip 0.0.0.0 -p 9003
- ```
-3. Use
- - with curl
- ```bash
- $ curl -F image_file=@1.png http://0.0.0.0:9003/ocr
- ```
- - with python
- - Send image data by file format.
- ```python
- import requests
-
- url = 'http://localhost:9003/ocr'
- img_path = '../python/tests/test_files/ch_en_num.jpg'
-
- with open(img_path, 'rb') as f:
- file_dict = {'image_file': (img_path, f, 'image/png')}
- response = requests.post(url, files=file_dict, timeout=60)
-
- print(response.json())
- ```
- - Send image data by base64 format.
- ```python
- import base64
- import requests
-
- url = 'http://localhost:9003/ocr'
- img_path = '../python/tests/test_files/ch_en_num.jpg'
-
- with open(img_path, 'rb') as fa:
- img_str = base64.b64encode(fa.read())
-
- payload = {'image_data': img_str}
- resp = requests.post(url, data=payload)
-
- print(resp.json())
- ```
-4. Output
-
- Click to expand
-
- ```json
- {
- "0": {
- "rec_txt": "香港深圳抽血，",
- "dt_boxes": [
- [265, 18],
- [472, 231],
- [431, 271],
- [223, 59]
- ],
- "score": "0.8175641223788261"
- },
- "1": {
- "rec_txt": "专业查性别",
- "dt_boxes": [
- [388, 15],
- [636, 257],
- [587, 307],
- [339, 65]
- ],
- "score": "0.8293875356515249"
- },
- "2": {
- "rec_txt": "专业鉴定B超单",
- "dt_boxes": [
- [215, 84],
- [509, 413],
- [453, 463],
- [159, 134]
- ],
- "score": "0.8626169338822365"
- },
- "3": {
- "rec_txt": "b超仪器查性别",
- "dt_boxes": [
- [128, 135],
- [430, 478],
- [366, 534],
- [64, 192]
- ],
- "score": "0.8449362441897392"
- },
- "4": {
- "rec_txt": "加微信eee",
- "dt_boxes": [
- [58, 189],
- [268, 450],
- [209, 498],
- [0, 236]
- ],
- "score": "0.8176911813872201"
- },
- "5": {
- "rec_txt": "可邮寄",
- "dt_boxes": [
- [493, 261],
- [617, 384],
- [577, 423],
- [454, 300]
- ],
- "score": "0.7494261413812637"
- }
- }
- ```
-
-
-
-### See details for [RapidOCR](https://github.com/RapidAI/RapidOCR/tree/main/ocrweb).
\ No newline at end of file
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr_api/)
diff --git a/docs/doc_whl_rapidocr_ort.md b/docs/doc_whl_rapidocr_ort.md
index 2d89a6a00..5725106bc 100644
--- a/docs/doc_whl_rapidocr_ort.md
+++ b/docs/doc_whl_rapidocr_ort.md
@@ -1,8 +1 @@
-## rapidocr-onnxruntime
-
-
-
- 
-
-
-### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr/rapidocr_onnxruntime/)
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr/usage/)
diff --git a/docs/doc_whl_rapidocr_vino.md b/docs/doc_whl_rapidocr_vino.md
index 1f6121cc3..5725106bc 100644
--- a/docs/doc_whl_rapidocr_vino.md
+++ b/docs/doc_whl_rapidocr_vino.md
@@ -1,8 +1 @@
-## rapidocr-openvino
-
-
-
- 
-
-
-### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr/rapidocr_openvino/)
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr/usage/)
diff --git a/docs/doc_whl_rapidocr_web.md b/docs/doc_whl_rapidocr_web.md
index 983c7260e..e8c8a2e8b 100644
--- a/docs/doc_whl_rapidocr_web.md
+++ b/docs/doc_whl_rapidocr_web.md
@@ -1,31 +1 @@
-## rapidocr-web
-
-
-
- 
- 
-
-
-### use
-1. Install package by pypi.
- ```bash
- $ pip install rapidocr-web
- ```
-2. Run by command line.
- - Usage:
- ```bash
- $ rapidocr_web -h
- usage: rapidocr_web [-h] [-ip IP] [-p PORT]
-
- optional arguments:
- -h, --help show this help message and exit
- -ip IP, --ip IP IP Address
- -p PORT, --port PORT IP port
- ```
- - Example:
- ```bash
- $ rapidocr_web -ip "0.0.0.0" -p 9003
- ```
-3. Open `http://localhost:9003/` to view, enjoy it.
-
-### See details for [RapidOCR](https://github.com/RapidAI/RapidOCR/tree/main/ocrweb).
\ No newline at end of file
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr_web/rapidocr_web/)
diff --git a/ocrweb/README.md b/ocrweb/README.md
index e8fe23f0d..e8c8a2e8b 100755
--- a/ocrweb/README.md
+++ b/ocrweb/README.md
@@ -1,53 +1 @@
-## RapidOCR Web Demo
-
-
-
-
-
-
-
-
-
-- [RapidOCR Web Demo](#rapidocr-web-demo)
- - [简要说明](#简要说明)
- - [桌面版使用教程](#桌面版使用教程)
- - [界面版使用步骤](#界面版使用步骤)
-
-
-### 简要说明
-- 该模块依赖`rapidocr_onnxruntime`库。
-- 如果想要离线部署，可以先手动下载[`rapidocr_onnxruntime`](https://pypi.org/project/rapidocr-onnxruntime/#files) whl包，再手动安装[`rapidocr_web`](https://pypi.org/project/rapidocr-web/#files) whl包来使用。
-- 所用模型组合（最优组合）为：
- ```text
- ch_PP-OCRv3_det + ch_ppocr_mobile_v2.0_cls + ch_PP-OCRv3_rec
- ```
-- 网页上显示的推理时间具体解释如下：
-
-
-
-
-
-
-
-
-
-
-
-目录
-
-- [RapidOCR Python](#rapidocr-python)
- - [简介](#简介)
- - [说明](#说明)
- - [pip安装快速使用（推荐）](#pip安装快速使用推荐)
- - [源码使用步骤](#源码使用步骤)
-
-
-### 简介
-- 该部分为python版的OCR推理，包括基于ONNXRuntime和OpenVINO两个推理引擎的包。
-- 因为模型较小，因此将相关模型都已打到Whl包，可直接pip安装使用。
-
-### 说明
-- `rapidocr_onnxruntime`和`rapidocr_openvino`两个包除推理引擎不同之外，其余均相同，默认都是在CPU上运行。
-- 按语义版本号来讲，两个包其主版本号和次版本号同步更新，修订号可能会有区别。也就是说`x.y.z`中`x`和`y`是一样的，`z`可能不同。
-- 各个版本的对应关系：
- |版本|内置模型版本|对应PaddleOCR 分支|
- |:---:|:---:|:---:|
- |`v1.3.x`|PaddleOCR v4版| [release/2.7](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.7)|
- |`v1.2.x`
`v1.1.x`
`v1.0.x`|PaddleOCR v3版| [release/2.6](https://github.com/PaddlePaddle/PaddleOCR/tree/release/2.6)|
-- 推荐使用[PaddleOCRModelConveter](https://github.com/RapidAI/PaddleOCRModelConverter)在线转换，现用现转。推理代码都是同一个，只需更换模型即可。已转好**ONNX模型下载地址：**[百度网盘](https://pan.baidu.com/s/1PTcgXG2zEgQU6A_A3kGJ3Q?pwd=jhai) | [Google Drive](https://drive.google.com/drive/folders/1x_a9KpCo_1blxH1xFOfgKVkw1HYRVywY?usp=sharing)，大家可自行搭配使用。
-- 所有常用的参数配置都在[`config.yaml`](https://github.com/RapidAI/RapidOCR/blob/main/python/rapidocr_onnxruntime/config.yaml)下，其中每个独立的模块下均有独立的`config.yaml`配置文件，可以单独使用。
-- 关于选择哪个版本的包（`rapidocr_onnxruntime` 或者 `rapidocr_openvino`）?
- |推理引擎|推理速度更快|占用内存更少|
- |:---:|:---:|:---:|
- |`rapidocr_onnxruntime`||✓|
- |`rapidocr_openvino`|✓|⚠️ openvino存在内存不释放的问题，参见[wiki](https://github.com/RapidAI/RapidOCR/wiki/openvino%E5%85%A5%E9%97%A8)|
-
-
-### pip安装快速使用（推荐）
-1. 安装环境
- |包名|版本|安装命令|
- |:---|:---:|:---|
- |`rapidocr_onnxruntime`|
|`pip install rapidocr-onnxruntime`|
- |`rapidocr_openvino`|
|`pip install rapidocr-openvino`|
-
-2. python脚本使用
- - ⚠️注意：初始化RapidOCR可不提供`config.yaml`，默认使用安装目录下的`config.yaml`。如有自定义需求：
- - 一是可直接通过初始化参数传入。详细参数参考下面命令行部分，和`config.yaml`基本对应。
- - 二是复制`config.yaml`，自行更改，然后初始化给出。e.g. `engine = RapidOCR(config_path="custom.yaml")`
-
- - 输入：`Union[str, np.ndarray, bytes, Path]`
- - 输出：
- - 有值：`([[文本框坐标], 文本内容, 置信度], 推理时间)`，e.g. `[[左上, 右上, 右下, 左下], '小明', '0.99'], [0.02, 0.02, 0.85]`
- - 为空：`(None, None)`
- - 示例：
- ```python
- import cv2
- from rapidocr_onnxruntime import RapidOCR
- # from rapidocr_openvino import RapidOCR
-
- # RapidOCR可传入参数参考下面的命令行部分
- rapid_ocr = RapidOCR()
-
- img_path = 'tests/test_files/ch_en_num.jpg'
-
- # 输入格式一：str
- result, elapse = rapid_ocr(img_path)
-
- # 输入格式二：np.ndarray
- img = cv2.imread('tests/test_files/ch_en_num.jpg')
- result, elapse = rapid_ocr(img)
-
- # 输入格式三：bytes
- with open(img_path, 'rb') as f:
- img = f.read()
- result, elapse = rapid_ocr(img)
-
- # 输入格式四：Path
- result, elapse = rapid_ocr(Path(img_path))
- print(result)
- ```
-
-3. 命令行使用
- - 参数说明：
- ```bash
- $ rapidocr_onnxruntime -h
- usage: rapidocr_onnxruntime [-h] -img IMG_PATH [-p] [--text_score TEXT_SCORE]
- [--use_angle_cls USE_ANGLE_CLS]
- [--use_text_det USE_TEXT_DET]
- [--print_verbose PRINT_VERBOSE]
- [--min_height MIN_HEIGHT]
- [--width_height_ratio WIDTH_HEIGHT_RATIO]
- [--det_use_cuda DET_USE_CUDA]
- [--det_model_path DET_MODEL_PATH]
- [--det_limit_side_len DET_LIMIT_SIDE_LEN]
- [--det_limit_type {max,min}]
- [--det_thresh DET_THRESH]
- [--det_box_thresh DET_BOX_THRESH]
- [--det_unclip_ratio DET_UNCLIP_RATIO]
- [--det_use_dilation DET_USE_DILATION]
- [--det_score_mode {slow,fast}]
- [--cls_use_cuda CLS_USE_CUDA]
- [--cls_model_path CLS_MODEL_PATH]
- [--cls_image_shape CLS_IMAGE_SHAPE]
- [--cls_label_list CLS_LABEL_LIST]
- [--cls_batch_num CLS_BATCH_NUM]
- [--cls_thresh CLS_THRESH]
- [--rec_use_cuda REC_USE_CUDA]
- [--rec_model_path REC_MODEL_PATH]
- [--rec_img_shape REC_IMAGE_SHAPE]
- [--rec_batch_num REC_BATCH_NUM]
-
- optional arguments:
- -h, --help show this help message and exit
- -img IMG_PATH, --img_path IMG_PATH MUST
- -p, --print_cost
-
- Global:
- --text_score TEXT_SCORE
- --use_angle_cls USE_ANGLE_CLS
- --use_text_det USE_TEXT_DET
- --print_verbose PRINT_VERBOSE
- --min_height MIN_HEIGHT
- --width_height_ratio WIDTH_HEIGHT_RATIO
-
- Det:
- --det_use_cuda DET_USE_CUDA
- --det_model_path DET_MODEL_PATH
- --det_limit_side_len DET_LIMIT_SIDE_LEN
- --det_limit_type {max,min}
- --det_thresh DET_THRESH
- --det_box_thresh DET_BOX_THRESH
- --det_unclip_ratio DET_UNCLIP_RATIO
- --det_use_dilation DET_USE_DILATION
- --det_score_mode {slow,fast}
-
- Cls:
- --cls_use_cuda CLS_USE_CUDA
- --cls_model_path CLS_MODEL_PATH
- --cls_image_shape CLS_IMAGE_SHAPE
- --cls_label_list CLS_LABEL_LIST
- --cls_batch_num CLS_BATCH_NUM
- --cls_thresh CLS_THRESH
-
- Rec:
- --rec_use_cuda REC_USE_CUDA
- --rec_model_path REC_MODEL_PATH
- --rec_img_shape REC_IMAGE_SHAPE
- --rec_batch_num REC_BATCH_NUM
- ```
- - 示例：
- ```bash
- $ rapidocr_onnxruntime -img tests/test_files/ch_en_num.jpg
- ```
-
-### 源码使用步骤
-
-
-
-1. 下载整个项目到本地
- ```shell
- cd RapidOCR/python
- ```
-
-2. 下载链接下的`resources`目录（包含模型和显示的字体文件）
- - 下载链接：[百度网盘](https://pan.baidu.com/s/1PTcgXG2zEgQU6A_A3kGJ3Q?pwd=jhai) | [Google Drive](https://drive.google.com/drive/folders/1x_a9KpCo_1blxH1xFOfgKVkw1HYRVywY?usp=sharing)
- - 最终目录如下，自行比对:
- ```text
- .
- ├── README.md
- ├── demo.py
- ├── rapidocr_onnxruntime
- │ ├── __init__.py
- │ ├── ch_ppocr_v2_cls
- │ ├── ch_ppocr_v3_det
- │ ├── ch_ppocr_v3_rec
- │ ├── config.yaml
- │ ├── rapid_ocr_api.py
- │ └── models
- │ ├── ch_PP-OCRv3_det_infer.onnx
- │ ├── ch_ppocr_mobile_v2.0_cls_infer.onnx
- │ └── ch_PP-OCRv3_rec_infer.onnx
- ├── rapidocr_openvino
- │ ├── __init__.py
- │ ├── README.md
- │ ├── ch_ppocr_v2_cls
- │ ├── ch_ppocr_v3_det
- │ ├── ch_ppocr_v3_rec
- │ ├── config.yaml
- │ ├── rapid_ocr_api.py
- │ └── models
- │ ├── ch_PP-OCRv3_det_infer.onnx
- │ ├── ch_ppocr_mobile_v2.0_cls_infer.onnx
- │ └── ch_PP-OCRv3_rec_infer.onnx
- ├── requirements.txt
- └── resources
- └── fonts
- └── FZYTK.TTF
- ```
-
-3. 安装运行环境
- - 基于onnxruntime推理所需环境安装：
- ```bash
- pip install onnxruntime>=1.7.0
- pip install -r requirements.txt
- ```
- - 基于openvino推理所需环境安装：
- ```bash
- pip install openvino
- pip install -r requirements.txt
- ```
- - ⚠️: 在Windows端，Shapely库自动安装可能会有问题，解决方案参见[Q15](https://github.com/RapidAI/RapidOCR/blob/main/docs/FAQ.md#q-windows系统下装完环境之后运行示例程序之后报错oserror-winerror-126-找不到指定的模組)
-
-4. 运行示例
- - 运行单元测试
- ```bash
- pytest tests/test_*.py
- ```
- - 接口调用
- ```python
- import cv2
-
- # 基于onnxruntime引擎推理
- from rapidocr_onnxruntime import RapidOCR
-
- # 基于openvino引擎推理
- # from rapidocr_openvino import RapidOCR
-
- rapid_ocr = RapidOCR()
-
- image_path = r'test_images/det_images/ch_en_num.jpg'
- img = cv2.imread(image_path)
-
- result = rapid_ocr(img)
- print(result)
-
- # result: [[文本框坐标], 文本内容, 置信度]
- # 示例：[[左上, 右上, 右下, 左下], '小明', '0.99']
- ```
- - 直接运行`demo.py`，可直接可视化查看结果。
- ```bash
- python demo.py
- ```
-
\ No newline at end of file
+### See [Documentation](https://rapidai.github.io/RapidOCRDocs/docs/install_usage/rapidocr/install/)