Last contributed to project: 8/17/2022
A program, part of a larger project, that creates a custom dictionary to be utilized by the Tesseract OCR engine to extract terms relevant to the EN-1 workbook
The overall project designed by the City University of New York Building Performance Lab (CUNY BPL) to create a faster way to organize and automate extracting table data from building construction drawings
This acquired data would then be autofilled in the respective building's energy audit template
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Custom data dictionary model built using Google's Tesseract Engine containing terms found in EN-1 workbooks to fill building energy audit templates
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