This article introduces an automated tool for processing PDF file splitting and drawing information extraction, aiming to split PDF documents in designated folders into separate pages, save each page as a separate file, and use text extraction or image recognition to obtain product model, group number, drawing number, and other information. Drawing naming is standardized according to research institute standards, improving the efficiency and accuracy of drawing management. This tool can quickly and effectively process large quantities of PDF files, providing convenience for the work of the research institute.
This article briefly introduces GPFS and GFS shared file systems, discusses the role of GPFS and GFS shared file systems in the field of server management, and compares the GPFS and GSP shared file systems of the PDM server cluster in the research institute; After testing, it was found that the GFS shared file system is more suitable for PDM server clusters. Three running servers in the PDM server cluster can concurrently access files in the GFS shared file system; Enable all three servers to independently provide services to the outside world. Moreover, any failure of two servers will not cause the PDM service to stop, ensuring the continuous progress of research and development in the research institute.
KEYWORDS: Image encryption, Image processing, Design and modelling, Matrices, 3D image processing, Human-machine interfaces, RGB color model, Information security, Data conversion, Computer vision technology
This paper proposes a design approach for an encryption tool based on image processing and PDF manipulation to meet the encryption requirements of sensitive design drawings. The tool is developed using Python programming language and the OpenCV-Python library. Designers can choose encryption fields through a GUI, including modifying product name, removing stage markers, and changing approval date, among others. Additionally, there are two encryption modes available for selection: combined into an one encrypted PDF or each PDF encrypted separately. Batch encryption of all PDF drawings within a selected path can be completed very quickly, significantly reducing the time and workload required for manually encrypting multiple PDF drawings. This greatly improves encryption efficiency and eliminates tedious repetitive work. The program avoids human errors and ensures that sensitive information remains protected from unauthorized access.
In the research institute's scientific design work, designers need to perform the task of statistical analysis for PDF drawings, including determining the dimension and number of pages of the PDF drawings, as well as calculating the equivalent amount of A4 pages. This process is tedious, time-consuming, and error prone. To solve this problem, this paper proposes the design and implementation of an automated PDF drawing statistical tool based on Python. The tool interacts with designers through a Graphical User Interface (GUI), enabling fast and accurate statistical analysis of all PDF drawings within a selected path. This significantly improves efficiency, reduces workload, and eliminates human errors.
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