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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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EN-1 Data Dictionary

Last contributed to project: 8/17/2022

Overview

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

Goal

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

Collaborators

Neil Kuldip

Navjot Singh

Katrina Chen

Samuel Wolnerman

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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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