# Complex OCR scenarios **URL:** \ **Category:** Models\ **Created:** [April 4, 2025, 3:20pm UTC](https://discuss.huggingface.co/t/complex-ocr-scenarios/148873 "2025-04-04T15:20:22Z")\ **Posts on this page:** 1\ **Showing post:** 2
**Author:** ![John6666](https://sea2.discourse-cdn.com/hellohellohello/user_avatar/discuss.huggingface.co/john6666/32/27664_2.png) [@John6666](https://discuss.huggingface.co/u/John6666)\ **Post date:** [April 4, 2025, 4:33pm UTC](https://discuss.huggingface.co/t/complex-ocr-scenarios/148873/2 "2025-04-04T16:33:25Z")
[https://discuss.huggingface.co/search?q=OCR%20order%3Alatest](https://discuss.huggingface.co/search?q=OCR%20order%3Alatest) I think we can help you with your consultation, but we are far from being a one-stop solution for PDF-related issues at the moment. You probably need to combine several models together to get the best results… > [@Extracting and segmenting handwritten and printed text in the images](https://discuss.huggingface.co/t/extracting-and-segmenting-handwritten-and-printed-text-in-the-images/99536): > > The project aim is to first segment (or draw Bounding box ) and classify the handwritten and printed text in the images and then extract handwritten and printed text from the images. The printed text can be extracted easily but the problem is that the extraction of handwritten text with good accuracy becomes difficult. the above image is an example image which will be used for inferencing. I have used pytesseract library to extract text but it fails on handwritten text. the example output is gi… > **[GitHub - SyedShahith/Handwritten-Text-Recognition-using-ocr-model](https://github.com/SyedShahith/Handwritten-Text-Recognition-using-ocr-model)** > > Contribute to SyedShahith/Handwritten-Text-Recognition-using-ocr-model development by creating an account on GitHub. --- _[View the full topic](https://discuss.huggingface.co/t/complex-ocr-scenarios/148873)._