(Please insert an screenshot of the Tool)
Type of tool: e.g. web application or desktop application
Required skills:
- Process/material knowledge: e.g. knowledge of material properties
- Digitalization knowledge: e.g. no programming
Short description of the tool:
- Detailed description: Link to the guideline:
Use case/problem: Selecting material (recyclate) for specific
product requirements
Description of the problem the tools solves: [General] + [Tool-specific]
Disclaimer:
How to use/download/access it: e.g. got the the gitup [link], copy
the code into [XY] and start using
Contact person of the tool:
Stefan Bloemheuvel
Related tools:
- Set up a working data infrastucture
- Find the right sensor to survey your process
- Validate your process data
-
Matrix Data Extractor (MDE) is a web-based application that identifies document table regions on PDF documents using Computer Vision based Deep Learning algorithm and extracts data to text files by applying Optical Character Recognition (OCR). It supports to transfer extracted data to MongoDB database tables. A search functionality is also provided to retrieve data on user interface based on Keyword matching (e.g. Manufacturer Name, Technical Datasheet Name, Keyword for Table Data).
Before getting started, please take a look at
Data Extractor/MatrixDataExtractor_UserGuide.pdf and make yourself familiar with how to use the tool.
The code for the tool is available at
https://github.com/cslab-hub/MatrixDataExtractor
Table detection model weights and datasets can be provided on request. It is not publicly available. Also a Jupyter Notebook can be provided on request to show model inference result on domain specific dataset.
Please use Secret Key as
'SECRET_KEY=!zhn#9$0pvr!+jp5q0f-vhvkfp0w$@tpvy4kf20pb89vf#w1q-' in mde.env file without single quotes.