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产线文档: 更新PP-DocTranslation等产线文档的参数描述格式 #17063
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| <td><code>seal_text_recognition_model_dir</code></td> | ||
| <td>印章文本识别模型的目录路径。如果不设置,将会下载官方模型。</td> | ||
| <td>印章文本识别模型的目录路径。 |
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这里不太对,重复了
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| <td><code>formula_recognition_model_name</code></td> | ||
| <td>公式识别模型的名称。如果不设置,将会使用产线默认模型。</td> | ||
| <td>公式识别模型的名称。 |
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这里不太对,重复了
| <tr> | ||
| <td><code>formula_recognition_model_dir</code></td> | ||
| <td>公式识别模型的目录路径。如果不设置,将会下载官方模型。</td> | ||
| <td>公式识别模型的目录路径。 |
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这里不太对,重复了
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| <td><code>formula_recognition_batch_size</code></td> | ||
| <td>公式识别模型的batch size。如果不设置,将默认设置batch size为<code>1</code>。</td> | ||
| <td>公式识别模型的batch size。 |
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这里不太对,重复了
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| <td><code>use_doc_orientation_classify</code></td> | ||
| <td>是否加载并使用文档方向分类模块。如果不设置,将使用产线初始化的该参数值,默认初始化为<code>False</code>。</td> | ||
| <td>是否加载并使用文档方向分类模块。 |
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这里不太对,重复了
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| <td><code>use_table_recognition</code></td> | ||
| <td>是否加载并使用表格识别子产线。如果不设置,将使用产线初始化的该参数值,默认初始化为<code>True</code>。</td> | ||
| <td>是否加载并使用表格识别子产线。 |
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这里不太对,重复了
| <tr> | ||
| <td><code>use_formula_recognition</code></td> | ||
| <td>是否加载并使用公式识别子产线。如果不设置,将使用产线初始化的该参数值,默认初始化为<code>True</code>。</td> | ||
| <td>是否加载并使用公式识别子产线。 |
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这里不太对,重复了
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| <td><code>use_chart_recognition</code></td> | ||
| <td>是否加载并使用文档区域检测模块。如果不设置,将使用产线初始化的该参数值,默认初始化为<code>False</code>。</td> | ||
| <td>是否加载并使用文档区域检测模块。 |
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这里不太对,重复了
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| <td><code>use_region_detection</code></td> | ||
| <td>是否加载并使用文档区域检测模块。如果不设置,将使用产线初始化的该参数值,默认初始化为<code>True</code>。</td> | ||
| <td>是否加载并使用文档区域检测模块。 |
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这里不太对,重复了
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| (2)调用 doc_preprocessor 产线对象的 `predict()` 方法进行推理预测,该方法会返回一个结果列表。 | ||
| (2)调用 doc_preprocessor 产线对象的 <code>predict()</code> 方法进行推理预测,该方法会返回一个结果列表。 | ||
| 另外,产线还提供了 <code>predict_iter()</code> 方法。两者在参数接受和结果返回方面是完全一致的,区别在于 <code>predict_iter()</code> 返回的是一个 <code>generator</code>,能够逐步处理和获取预测结果,适合处理大型数据集或希望节省内存的场景。可以根据实际需求选择使用这两种方法中的任意一种。 |
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这块的可视化会不会有问题?
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多余部分已删除,可视化部分看起来没问题
Removed redundant explanation about predict_iter() method and clarified the usage of predict() method.
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@cuicheng01 已修改 |
@cuicheng01