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We are looking for someone, who will help implement an solution to use the given model, to detect Tables from google spreadsheets. As input You will have XLS files or json file which we will create in runtime in google an spreadsheet plugin.
We should than send the request to the model or try to make the prediction inside plugin.
Please note there is an Script in point 8. which might usefull for convertion of spreadsheet
The Main goal should be ranges of all found tables in all sheets ( In yt example shown as _T_0 or _0_X, via defined ranges )
The optional goal should be to detect Headers ( In yt example shown as _H_0 or _H_X or _V_0 or _V_X , via defined ranges )
The Detection probality and accuracy should be high for typical Tables.
B) An probably easier aproach to solve the issue from A) might be using images native to CascadeTables, we attach Example images.
We still would like to indentify Headers( optional)
We will provide Training data if needed, similar as those attached in Zip file.
I attach an playlist with 9 vidoes showing many diferent issues regarding labeling of Tables in Spreadsheets, please review them carefuly. [login to view URL]
I also Attach an Zip with example labeled Spredsheets for A) and example pack of iamges for B)
SS - Spreadsheet
Ranges - Typical Excel Term to specify a group of cells.
8 фрилансеров(-а) готовы выполнить эту работу в среднем за $506
Hi, there. I am a machine learning engineer with 5+ years of hands-on experience in PyTorch. Carefully checked your requirements. Hope to work for you with this project. Best regards, Sgadou