add result example
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@ -57,8 +57,28 @@ im_show = draw_result(image, result,font_path=font_path)
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im_show = Image.fromarray(im_show)
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im_show.save('result.jpg')
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```
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#### 1.2.3 返回结果说明
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The return result of PaddleStructure is a list composed of a dict, an example is as follows
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#### 1.2.3 Parameter Description:
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```shell
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[
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{ 'type': 'Text',
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'bbox': [34, 432, 345, 462],
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'res': ([[36.0, 437.0, 341.0, 437.0, 341.0, 446.0, 36.0, 447.0], [41.0, 454.0, 125.0, 453.0, 125.0, 459.0, 41.0, 460.0]],
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[('Tigure-6. The performance of CNN and IPT models using difforen', 0.90060663), ('Tent ', 0.465441)])
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}
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]
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```
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The description of each field in dict is as follows
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| Parameter | Description |
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| --------------- | -------------|
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|type|Type of image area|
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|bbox|The coordinates of the image area in the original image, respectively [left upper x, left upper y, right bottom x, right bottom y]|
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|res|OCR or table recognition result of image area。<br> Table: HTML string of the table; <br> OCR: A tuple containing the detection coordinates and recognition results of each single line of text|
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#### 1.2.4 Parameter Description:
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| Parameter | Description | Default value |
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| --------------- | ---------------------------------------- | ------------------------------------------- |
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@ -58,8 +58,28 @@ im_show = Image.fromarray(im_show)
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im_show.save('result.jpg')
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```
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#### 1.2.3 返回结果说明
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PaddleStructure 的返回结果为一个dict组成的list,示例如下
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#### 1.2.3 参数说明
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```shell
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[
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{ 'type': 'Text',
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'bbox': [34, 432, 345, 462],
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'res': ([[36.0, 437.0, 341.0, 437.0, 341.0, 446.0, 36.0, 447.0], [41.0, 454.0, 125.0, 453.0, 125.0, 459.0, 41.0, 460.0]],
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[('Tigure-6. The performance of CNN and IPT models using difforen', 0.90060663), ('Tent ', 0.465441)])
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}
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]
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```
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dict 里各个字段说明如下
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| 字段 | 说明 |
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| --------------- | -------------|
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|type|图片区域的类型|
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|bbox|图片区域的在原图的坐标,分别[左上角x,左上角y,右下角x,右下角y]|
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|res|图片区域的OCR或表格识别结果。<br> 表格: 表格的HTML字符串; <br> OCR: 一个包含各个单行文字的检测坐标和识别结果的元组|
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#### 1.2.4 参数说明
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| 字段 | 说明 | 默认值 |
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| --------------- | ---------------------------------------- | ------------------------------------------- |
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