CN110941947A - Document editing method and device, computer storage medium and terminal - Google Patents
Document editing method and device, computer storage medium and terminal Download PDFInfo
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- CN110941947A CN110941947A CN201811110450.0A CN201811110450A CN110941947A CN 110941947 A CN110941947 A CN 110941947A CN 201811110450 A CN201811110450 A CN 201811110450A CN 110941947 A CN110941947 A CN 110941947A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/22—Image preprocessing by selection of a specific region containing or referencing a pattern; Locating or processing of specific regions to guide the detection or recognition
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Abstract
A method, a device, a computer storage medium and a terminal for editing a document comprise: for Portable Document Format (PDF) documents with preset pages, converting each page of PDF document into a corresponding sample picture; labeling the position of each line of characters contained in each sample picture obtained by conversion; training a neural network model by taking the sample picture with the marked character position as training data; after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model; editing a PDF document according to the determined position of the character contained in the picture to be processed; the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner. The embodiment of the invention edits the PDF document after determining the distribution of characters in the PDF, avoids the influence on document editing due to typesetting conversion, and improves the document editing efficiency.
Description
Technical Field
The present disclosure relates to, but not limited to, information editing technologies, and in particular, to a method, an apparatus, a computer storage medium, and a terminal for document editing.
Background
Portable Document Format (PDF) files are widely used by related staff as carriers for recording information such as novels, test questions, magazines, comics, reports and the like; workers typically print WORD or documents edited by other office software as PDF documents, or scan printed paper documents as PDF documents.
When the PDF file is a file obtained by scanning a paper file, a user cannot edit information contained in the PDF; in the related technology, a user can realize information copying and editing after a PDF file is generally converted into a WORD file through a conversion tool; after the document is converted into the WORD file, the document typesetting may change, and the user needs to determine the position of the acquired information again to copy the information, which affects the document editing efficiency; in addition, when the PDF file obtained by scanning is converted into a WORD file, content errors are also likely to occur, and the difficulty in acquiring information is further increased in the case of layout change and content errors.
In summary, when the PDF file obtained by scanning needs to obtain the required information, the efficiency of obtaining information is reduced due to information errors in the process of typesetting and text conversion, which affects the document editing efficiency of the user.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
Embodiments of the present invention provide a method and an apparatus for document editing, a computer storage medium, and a terminal, which can avoid the influence of typesetting transformation on document editing and improve the document editing efficiency.
The embodiment of the invention provides a method for editing a document, which comprises the following steps:
for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
labeling the position of each line of characters contained in each sample picture obtained by conversion;
training a neural network model by taking the sample picture with the marked character position as training data;
after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
Optionally, the position of each line of text included in the labeled sample picture includes:
marking the following part or all information of each line of characters by taking the pixel as a marking unit:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
Optionally, the neural network model includes:
tensor Flow model.
Optionally, the performing PDF document editing includes:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
On the other hand, an embodiment of the present invention further provides a device for editing a document, including: the device comprises a conversion unit, a marking unit, a training unit, a determination unit and a processing unit; wherein the content of the first and second substances,
the conversion unit is used for: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
the marking unit is used for: labeling the position of each line of characters contained in each sample picture obtained by conversion;
the training unit is used for: training a neural network model by taking the sample picture with the marked character position as training data;
the determination unit is used for: after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
the processing unit is used for: editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
Optionally, the labeling unit is specifically configured to:
and marking the following part or all of information of each line of characters by taking the pixels as marking units for each sample picture obtained by conversion:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
Optionally, the neural network model includes:
tensor Flow model.
Optionally, the processing unit is specifically configured to:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
In still another aspect, an embodiment of the present invention further provides a computer storage medium, where computer-executable instructions are stored in the computer storage medium, and the computer-executable instructions are used to execute the above method for editing a document.
In another aspect, an embodiment of the present invention further provides a terminal, including: a memory and a processor; wherein the content of the first and second substances,
the processor is configured to execute program instructions in the memory;
the program instructions read on the processor to perform the following operations:
for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
labeling the position of each line of characters contained in each sample picture obtained by conversion;
training a neural network model by taking the sample picture with the marked character position as training data;
after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner.
Compared with the related art, the technical scheme of the application comprises the following steps: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively; labeling the position of each line of characters contained in each sample picture obtained by conversion; training a neural network model by taking the sample picture with the marked character position as training data; after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model; editing a PDF document according to the determined position of the character contained in the picture to be processed; the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner. The embodiment of the invention edits the PDF document after determining the distribution of characters in the PDF, avoids the influence on document editing due to typesetting conversion, and improves the document editing efficiency.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the example serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a flow diagram of a method of document editing according to an embodiment of the present invention;
fig. 2 is a block diagram of a device for document editing according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
The steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.
FIG. 1 is a flowchart of a document editing method according to an embodiment of the present invention, as shown in FIG. 1, including:
it should be noted that, in the embodiment of the present invention, the sample picture may be a picture in any format determined by a person skilled in the art according to the advantage and disadvantage analysis of pictures in various formats and suitable for the embodiment of the present invention.
it should be noted that the method for standard text position in the embodiment of the present invention may include a labeling method existing in the related art, which is not described herein again.
Optionally, the marking the position of each line of characters included in the sample picture in the embodiment of the present invention includes:
marking the following part or all information of each line of characters by taking the pixel as a marking unit:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
103, training a neural network model by taking the sample picture with the marked character position as training data;
it should be noted that the method for training the neural network model according to the training data in the embodiment of the present invention may include a training method known in the related art.
Optionally, the neural network model in the embodiment of the present invention includes:
tensor Flow model.
It should be noted that the sensor Flow model is only an optional embodiment of the neural network model according to the embodiment of the present invention, and other neural network models that can be applied to the embodiment of the present invention may be applied to the present application.
it should be noted that, the determining, by the trained neural network model, the position including the text in the to-be-processed picture in the embodiment of the present invention includes: and determining the position of the characters contained in each page of the picture to be processed by the trained neural network model page by page for the picture to be processed obtained by conversion.
105, editing the PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
Optionally, the performing PDF document editing according to the embodiment of the present invention includes:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
It should be noted that, the identification method for the characters in the to-be-processed picture according to the embodiment of the present invention may include an existing identification method in the related art, which is not described herein again; after the text information is identified, the identified text is written into a newly-created PDF document by using an existing editing mode in the related art according to the position of the determined text included in the picture to be processed, that is, the PDF document is edited under the condition that the layout of the scanned PDF file is kept.
Compared with the related art, the technical scheme of the application comprises the following steps: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively; labeling the position of each line of characters contained in each sample picture obtained by conversion; training a neural network model by taking the sample picture with the marked character position as training data; after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model; editing a PDF document according to the determined position of the character contained in the picture to be processed; the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner. The embodiment of the invention edits the PDF document after determining the distribution of characters in the PDF, avoids the influence on document editing due to typesetting conversion, and improves the document editing efficiency.
Fig. 2 is a block diagram of a device for document editing according to an embodiment of the present invention, as shown in fig. 2, including: the device comprises a conversion unit, a marking unit, a training unit, a determination unit and a processing unit; wherein the content of the first and second substances,
the conversion unit is used for: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
it should be noted that, in the embodiment of the present invention, the sample picture may be a picture in any format determined by a person skilled in the art according to the advantage and disadvantage analysis of pictures in various formats and suitable for the embodiment of the present invention.
The marking unit is used for: labeling the position of each line of characters contained in each sample picture obtained by conversion;
it should be noted that the method for standard text position in the embodiment of the present invention may include a labeling method existing in the related art, which is not described herein again.
The training unit is used for: training a neural network model by taking the sample picture with the marked character position as training data;
it should be noted that the method for training the neural network model according to the training data in the embodiment of the present invention may include a training method known in the related art.
The determination unit is used for: after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
it should be noted that, the determining, by the trained neural network model, the position including the text in the to-be-processed picture in the embodiment of the present invention includes: and determining the position of the characters contained in each page of the picture to be processed by the trained neural network model page by page for the picture to be processed obtained by conversion.
The processing unit is used for: editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
Optionally, the labeling unit in the embodiment of the present invention is specifically configured to:
and marking the following part or all of information of each line of characters by taking the pixels as marking units for each sample picture obtained by conversion:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
Optionally, the neural network model includes:
tensor Flow model.
It should be noted that the sensor Flow model is only an optional embodiment of the neural network model according to the embodiment of the present invention, and other neural network models that can be applied to the embodiment of the present invention may be applied to the present application.
Optionally, the processing unit is specifically configured to:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
It should be noted that, the identification method for the characters in the to-be-processed picture according to the embodiment of the present invention may include an existing identification method in the related art, which is not described herein again; after the text information is identified, the identified text is written into a newly-created PDF document by using an existing editing mode in the related art according to the position of the determined text included in the picture to be processed, that is, the PDF document is edited under the condition that the layout of the scanned PDF file is kept.
Compared with the related art, the technical scheme of the application comprises the following steps: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively; labeling the position of each line of characters contained in each sample picture obtained by conversion; training a neural network model by taking the sample picture with the marked character position as training data; after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model; editing a PDF document according to the determined position of the character contained in the picture to be processed; the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner. The embodiment of the invention edits the PDF document after determining the distribution of characters in the PDF, avoids the influence on document editing due to typesetting conversion, and improves the document editing efficiency.
In still another aspect, an embodiment of the present invention further provides a computer storage medium, where computer-executable instructions are stored in the computer storage medium, and the computer-executable instructions are used to execute the above method for editing a document.
In another aspect, an embodiment of the present invention further provides a terminal, including: a memory and a processor; wherein the content of the first and second substances,
the processor is configured to execute program instructions in the memory;
the program instructions read on the processor to perform the following operations:
for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
labeling the position of each line of characters contained in each sample picture obtained by conversion;
training a neural network model by taking the sample picture with the marked character position as training data;
after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner.
It will be understood by those skilled in the art that all or part of the steps of the above methods may be implemented by a program instructing associated hardware (e.g., a processor) to perform the steps, and the program may be stored in a computer readable storage medium, such as a read only memory, a magnetic or optical disk, and the like. Alternatively, all or part of the steps of the above embodiments may be implemented using one or more integrated circuits. Accordingly, each module/unit in the above embodiments may be implemented in hardware, for example, by an integrated circuit to implement its corresponding function, or in software, for example, by a processor executing a program/instruction stored in a memory to implement its corresponding function. The present invention is not limited to any specific form of combination of hardware and software.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A method of document editing, comprising:
for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
labeling the position of each line of characters contained in each sample picture obtained by conversion;
training a neural network model by taking the sample picture with the marked character position as training data;
after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
2. The method of claim 1, wherein the labeling the position of each line of text included in the sample picture comprises:
marking the following part or all information of each line of characters by taking the pixel as a marking unit:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
3. The method of claim 1, wherein the neural network model comprises:
tensor Flow model.
4. The method according to any one of claims 1 to 3, wherein the performing PDF document editing comprises:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
5. An apparatus for document editing, comprising: the device comprises a conversion unit, a marking unit, a training unit, a determination unit and a processing unit; wherein the content of the first and second substances,
the conversion unit is used for: for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
the marking unit is used for: labeling the position of each line of characters contained in each sample picture obtained by conversion;
the training unit is used for: training a neural network model by taking the sample picture with the marked character position as training data;
the determination unit is used for: after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
the processing unit is used for: editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of the PDF document and the PDF document needing to be edited comprise: a PDF document obtained in a scanned manner.
6. The apparatus according to claim 5, wherein the labeling unit is specifically configured to:
and marking the following part or all of information of each line of characters by taking the pixels as marking units for each sample picture obtained by conversion:
a transverse starting position, a transverse ending position, a longitudinal starting position and a longitudinal ending position.
7. The apparatus of claim 5, wherein the neural network model comprises:
tensor Flow model.
8. The device according to any one of claims 5 to 7, wherein the processing unit is specifically configured to:
identifying characters in the picture to be processed according to the determined position of the characters in the picture to be processed;
and writing the recognized characters into a newly-built PDF document according to the determined positions of the characters contained in the picture to be processed so as to edit the PDF document.
9. A computer storage medium having computer-executable instructions stored therein for performing the method of document editing of any of claims 1-4.
10. A terminal, comprising: a memory and a processor; wherein the content of the first and second substances,
the processor is configured to execute program instructions in the memory;
the program instructions read on the processor to perform the following operations:
for portable document format PDF documents with preset pages, converting each page of PDF document into corresponding sample pictures respectively;
labeling the position of each line of characters contained in each sample picture obtained by conversion;
training a neural network model by taking the sample picture with the marked character position as training data;
after a PDF document needing to be edited is converted into a picture to be processed, determining the position containing characters in the picture to be processed through a trained neural network model;
editing a PDF document according to the determined position of the character contained in the picture to be processed;
the preset number of pages of PDF documents and the PDF documents needing to be edited comprise: a PDF document obtained in a scanned manner.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811110450.0A CN110941947A (en) | 2018-09-21 | 2018-09-21 | Document editing method and device, computer storage medium and terminal |
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| CN201811110450.0A CN110941947A (en) | 2018-09-21 | 2018-09-21 | Document editing method and device, computer storage medium and terminal |
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| CN112417826A (en) * | 2020-11-24 | 2021-02-26 | 济南智学承远信息技术有限公司 | PDF online editing method and device, electronic equipment and readable storage medium |
| CN112560767A (en) * | 2020-12-24 | 2021-03-26 | 南方电网深圳数字电网研究院有限公司 | Document signature identification method and device and computer readable storage medium |
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