人工智能Java SDK：文字識別（OCR）工具箱

文字識別（OCR）工具箱

文字識別（OCR）目前在多個行業(yè)中得到了廣泛應用几于，比如金融行業(yè)的單據(jù)識別輸入，餐飲行業(yè)中的發(fā)票識別，
交通領域的車票識別，企業(yè)中各種表單識別，以及日常工作生活中常用的身份證拂封，駕駛證，護照識別等等鹦蠕。
OCR（文字識別）是目前常用的一種AI能力冒签。

OCR工具箱功能:

方向檢測

0度
90度
180度
270度

detect_direction

圖片旋轉
文字識別(提供三個模型)

mobile模型
light模型
服務器端模型

版面分析（支持5個類別, 用于配合文字識別，表格識別的流水線處理）

Text
Title
List
Table
Figure

表格識別

生成html表格
生成excel文件

運行OCR識別例子

1.1 文字方向檢測：

例子代碼: OcrDetectionExample.java
運行成功后钟病，命令行應該看到下面的信息:

[INFO ] - Result image has been saved in: build/output/detect_result.png
[INFO ] - [
    class: "0", probability: 1.00000, bounds: [x=0.073, y=0.069, width=0.275, height=0.026]
    class: "0", probability: 1.00000, bounds: [x=0.652, y=0.158, width=0.222, height=0.040]
    class: "0", probability: 1.00000, bounds: [x=0.143, y=0.252, width=0.144, height=0.026]
    class: "0", probability: 1.00000, bounds: [x=0.628, y=0.328, width=0.168, height=0.026]
    class: "0", probability: 1.00000, bounds: [x=0.064, y=0.330, width=0.450, height=0.023]
]

輸出圖片效果如下：

detect_result

1.2 文字方向檢測幫助類（增加置信度信息顯示萧恕，便于調試）：

例子代碼: OcrDetectionHelperExample.java
運行成功后刚梭，命令行應該看到下面的信息:

[INFO ] - Result image has been saved in: build/output/detect_result_helper.png
[INFO ] - [
    class: "0 :1.0", probability: 1.00000, bounds: [x=0.073, y=0.069, width=0.275, height=0.026]
    class: "0 :1.0", probability: 1.00000, bounds: [x=0.652, y=0.158, width=0.222, height=0.040]
    class: "0 :1.0", probability: 1.00000, bounds: [x=0.143, y=0.252, width=0.144, height=0.026]
    class: "0 :1.0", probability: 1.00000, bounds: [x=0.628, y=0.328, width=0.168, height=0.026]
    class: "0 :1.0", probability: 1.00000, bounds: [x=0.064, y=0.330, width=0.450, height=0.023]
]

輸出圖片效果如下：

detect_result_helper

2. 圖片旋轉：

每調用一次rotateImg方法，會使圖片逆時針旋轉90度票唆。

例子代碼: RotationExample.java
旋轉前圖片:

ticket_0
旋轉后圖片效果如下：

rotate_result

3. 文字識別：

再使用本方法前朴读，請調用上述方法使圖片文字呈水平(0度)方向。

例子代碼: LightOcrRecognitionExample.java
運行成功后走趋，命令行應該看到下面的信息:

[INFO ] - [
    class: "你", probability: -1.0e+00, bounds: [x=0.319, y=0.164, width=0.050, height=0.057]
    class: "永遠都", probability: -1.0e+00, bounds: [x=0.329, y=0.349, width=0.206, height=0.044]
    class: "無法叫醒一個", probability: -1.0e+00, bounds: [x=0.328, y=0.526, width=0.461, height=0.044]
    class: "裝睡的人", probability: -1.0e+00, bounds: [x=0.330, y=0.708, width=0.294, height=0.043]
]

輸出圖片效果如下：

ocr_result

4. 版面分析：

運行成功后衅金，命令行應該看到下面的信息:

[INFO ] - [
    class: "Text", probability: 0.98750, bounds: [x=0.081, y=0.620, width=0.388, height=0.183]
    class: "Text", probability: 0.98698, bounds: [x=0.503, y=0.464, width=0.388, height=0.167]
    class: "Text", probability: 0.98333, bounds: [x=0.081, y=0.465, width=0.387, height=0.121]
    class: "Figure", probability: 0.97186, bounds: [x=0.074, y=0.091, width=0.815, height=0.304]
    class: "Table", probability: 0.96995, bounds: [x=0.506, y=0.712, width=0.382, height=0.143]
]

輸出圖片效果如下：

layout

5. 表格識別：

運行成功后，命令行應該看到下面的信息:

<html>
 <body>
  <table>
   <thead>
    <tr>
     <td>Methods</td>
     <td>R</td>
     <td>P</td>
     <td>F</td>
     <td>FPS</td>
    </tr>
   </thead>
   <tbody>
    <tr>
     <td>SegLink[26]</td>
     <td>70.0</td>
     <td>86.0</td>
     <td>770</td>
     <td>89</td>
    </tr>
    <tr>
     <td>PixelLink[4j</td>
     <td>73.2</td>
     <td>83.0</td>
     <td>77.8</td>
     <td></td>
    </tr>
...
   </tbody>
  </table> 
 </body>
</html>

輸出圖片效果如下：

table
生成excel效果如下：

excel

最后編輯于：2023.09.03 23:06:05

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