Please add feature to obtain table data as CSV which makes it easier to use ETL tools like ADF for loading data into relational database

When I copied and pasted the sample C# client code snippets from the Quickstart documentation, the code doesn't even compile. Please share a simple working C# client program via github so we don't have to copy/paste bits and pieces and we don't have to struggle with compiler errors. The sample should work as long as the FORMRECOGNIZERENDPOINT and FORMRECOGNIZERKEY environment variables are set to valid values. [Oh, please make this textarea box resizable]

When I used label tool to open the project from cloud, it will auto create the same connection in my Connections setting.
This situation can be fix?

Often, OCR detects handwritten text incorrectly.

For example:

"Bridget Sims, MD" was detected at "Bridge+ Sims, MD"

There should be a way to correct this and enter in the correct value of the text detected as "Bridget Sims MD" after the OCR has done its work.

Is there a way to do this already?

Hello, I followed the tutorial here: https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/quickstarts/label-tool

I setup a Azure web app (ACI) to run the docker image according to this tutorial: https://docs.microsoft.com/en-us/azure/cognitive-services/form-recognizer/deploy-label-tool#deploy-with-azure-container-instances-aci

I setup the connection. Then when I went to create the project it kept giving me this error and I have no idea what is wrong? I tried removing all spaces and non alpha characters from project name but nothing seems to work :(

I am using a single storage container having different types of forms.

1. Is it possible to generate different custom models with labeling based on the form types. For Example, one Model Id for W2 wage form and other Model Id for 1040 tax form etc..




2. Is there any possibility to filter the tags based on Form Types. It is very confusing to see all the tags of different form types spanning across all different forms.




3. Is it possible to store the training data on premise.

Hello,

it would be nice to allow to name the model when training.. will allow to not waist time saving id ect

I’m working on a project to create custom Machine Learning models for the processing of invoices using Azure Form Recognizer and OCR Form Labeling Tool.

In general it’s working really well, however, I have a situation where I have more than one invoice in the same PDF file. In is current form, the OCR Form Labeling Tool & Azure Form Recognizer don’t handle this situation very well. I‘m wondering if there are any tips or guidelines for this situation or will this use case be covered in the future?

Any guidance would be greatly appreciated!!

Can i use my own ocr service to capture text ? Cause many languages are not supported and there is no schedule.

We should be able to use a setting to only analyze the first X pages of forms.
I.e. we have forms related to phone bills, which the first 2 pages have relevant info then there is 20+ pages of just call records which we do not want to analyze.
We should be able to tell the analyze forms function to only process the first X number of pages.

Especially in the power automate function.

There is a max number of custom models that I can create?

For example, If I trained a custom model from a dataset and I add more files to this dataset, I need to delete the old one and use the new one?

The API console struggles with the local file path definition and I don't always want to use embedded assets/resources in Xamarin projects. So is there a robust/consistent way to use local file path (say for Android/iOS) - and is the only option the local application data folder?

This query may already be out there...apologies in advance...
Is there any roadmap/plan to add general URL sources for Training api other than azure blob containers?
(Have a separate question relating to local file paths)

I know Form Recognizer does not yet support labeling tables as tables. Suggestions please.
Please see pic1 for reference. Number of Line Items may vary at large.
And, What can we do if some text is not recognized by the OCR labeling tool see pic1 ?

after prediction in progress...

I uploaded 5 documents –– 2 batches of similar files. However, the model's confidence is very low. When I upload files though the model is working correctly. I'd love to be able to confirm the model if it were correct and automatically have it added to the training so that I don't have to manually tag each of the fields for that document.

I could not get tagging to work with jpgs in a folder in the container and the same folder name in the project in the Docker image.
Is there a GitHub project for this?

The original forms labeling tool (VoTT) creates vott files and the new one (OCR Form Labeling Tool) uses fott files. I labeled and trained a bunch of forms using the original labeling tool. Is there a way for me to migrate those vott files to the fott file format?

It seems kind of strange you would switch labeling tools without providing any guidance on how to migrate their trained forms.

I pulled the latest Docker image on April 27th, on two separate computers and two separate subscriptions/tenants. I can create the connection and the project, but upon project save, it moves to the label screen and seems hung.

I have tried the hosted Docker image and the local one. Both act the same, as does my corporate and personal Azure accounts. Any idea as to what I am doing wrong?