Closed tanejajatin1 closed 3 years ago
@tanejajatin1 I will help you
@tanejajatin1 iF it is possible, Can you share your document (please edit sensitive data on the document or add dummy values) ? OR Can u share screenshot of what is expected and what is actual value?
Hey, I created a sample document for further troubleshooting it. I created two tables inside it just to test it out. When I am tried calling document AI API from the try out function it gives us the JSON response with two headerrows, which is ideally true as there are two tables so it is the right one.
The same document gives different JSON response when called from inbuilt library of NodeJs for Document AI. It only gives one headerrows instead of two.
Please refer the document I created with two tables below
@tanejajatin1 Looks like python does not have sample that demonstrates batch table sample which exists in node repo https://github.com/googleapis/nodejs-document-ai/blob/master/samples/batch_parse_table.js
if you are using batch-process-document.v1beta3.js and batch_process_documents_sample_v1beta3.py, they produce same results (tested and confirmed). Currently, node samples has batch_process_table.js but python does not have it.
@tanejajatin1 I just added python sample for you
https://github.com/googleapis/python-documentai/pull/76
With that note, I would like to close this issue, Please let me know if this issue has been resolved for you
Thanks
Thanks for your response. But I think you misunderstood the requirement. Why are you recommending Batch process for a single document? We are just passing a single document which has multiple tables in it. It should ideally give back the table data present in the document. Also the point is it is able to identify the data inside another table as well. The only thing where issue is, it is not able to get the headers of second table inside headerrow object. But the data is present in rowobject. I hope I am making some sense now.
u can still process single document using batch_process_document.
Currently, we do not have python sample that processes table.
However, if you use this batch sample, it actually give you back table data present the document u wish for in gs://bucket
I will discuss with the team to deliver these v1beta2 samples.
As you can see, I used this batch sample to get the following output (which extracted two table headers from your given input)
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xcvc\n","pages":[{"pageNumber":1,"dimension":{"width":595,"height":841,"unit":"points"},"layout":{"textAnchor":{"textSegments":[{"endIndex":"174"}]},"confidence":1,"boundingPoly":{"vertices":[{},{"x":595},{"x":595,"y":841},{"y":841}],"normalizedVertices":[{},{"x":1},{"x":1,"y":1},{"y":1}]},"orientation":"PAGE_UP"},"blocks":[{"layout":{"textAnchor":{"textSegments":[{"endIndex":"8"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.1117717},{"x":0.17478992,"y":0.1117717},{"x":0.17478992,"y":0.12366231},{"x":0.1210084,"y":0.12366231}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"8","endIndex":"35"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.19857313},{"x":0.3226891,"y":0.19857313},{"x":0.3226891,"y":0.21046373},{"x":0.1210084,"y":0.21046373}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"35","endIndex":"43"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.25208086},{"x":0.17478992,"y":0.25208086},{"x":0.17478992,"y":0.26397145},{"x":0.1210084,"y":0.26397145}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"43","endIndex":"86"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.1391201},{"x":0.7058824,"y":0.1391201},{"x":0.7058824,"y":0.16765755},{"x":0.13109244,"y":0.16765755}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"86","endIndex":"174"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.27942926},{"x":0.8134454,"y":0.27942926},{"x":0.8134454,"y":0.3412604},{"x":0.13109244,"y":0.3412604}]},"orientation":"PAGE_UP"}}],"paragraphs":[{"layout":{"textAnchor":{"textSegments":[{"endIndex":"8"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.1117717},{"x":0.17478992,"y":0.1117717},{"x":0.17478992,"y":0.12366231},{"x":0.1210084,"y":0.12366231}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"8","endIndex":"35"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.19857313},{"x":0.3226891,"y":0.19857313},{"x":0.3226891,"y":0.21046373},{"x":0.1210084,"y":0.21046373}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"35","endIndex":"43"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.25208086},{"x":0.17478992,"y":0.25208086},{"x":0.17478992,"y":0.26397145},{"x":0.1210084,"y":0.26397145}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"43","endIndex":"86"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.1391201},{"x":0.7058824,"y":0.1391201},{"x":0.7058824,"y":0.16765755},{"x":0.13109244,"y":0.16765755}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"86","endIndex":"174"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.27942926},{"x":0.8134454,"y":0.27942926},{"x":0.8134454,"y":0.3412604},{"x":0.13109244,"y":0.3412604}]},"orientation":"PAGE_UP"}}],"lines":[{"layout":{"textAnchor":{"textSegments":[{"endIndex":"8"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.1117717},{"x":0.17478992,"y":0.1117717},{"x":0.17478992,"y":0.12366231},{"x":0.1210084,"y":0.12366231}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"8","endIndex":"35"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.19857313},{"x":0.3226891,"y":0.19857313},{"x":0.3226891,"y":0.21046373},{"x":0.1210084,"y":0.21046373}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"35","endIndex":"43"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.1210084,"y":0.25208086},{"x":0.17478992,"y":0.25208086},{"x":0.17478992,"y":0.26397145},{"x":0.1210084,"y":0.26397145}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"43","endIndex":"68"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.1391201},{"x":0.7058824,"y":0.1391201},{"x":0.7058824,"y":0.1510107},{"x":0.13109244,"y":0.1510107}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"68","endIndex":"86"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.15576695},{"x":0.67731094,"y":0.15576695},{"x":0.67731094,"y":0.16765755},{"x":0.13109244,"y":0.16765755}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"86","endIndex":"127"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y":0.27942926},{"x":0.8134454,"y":0.27942926},{"x":0.8134454,"y":0.29131985},{"x":0.13109244,"y":0.29131985}]},"orientation":"PAGE_UP"}},{"layout":{"textAnchor":{"textSegments":[{"startIndex":"127","endIndex":"143"}]},"confidence":1,"boundingPoly":{"normalizedVertices":[{"x":0.13109244,"y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Due to inactivity, I am closing this issue. Feel free to reopen this issue.
I am trying to call Document AI v1beta2 inbuilt client library to parse table inside the document. As a result I am getting the JSON result object but it doesn't have the table headers for all the table present inside the document. It shows the header for the first table only and then all the other tables data comes under body rows.
I also tried the try out function from the official documentation of Document AI it gives back the right results. It gives the data as required.
Can anyone please assist on this?