1. Tutorial Introduction

InkSight is a revolutionary artificial intelligence technology launched by Google Research in 2024. It is specifically used for handwritten text recognition and digitization.InkSight: Offline-to-Online Handwriting Conversion by Learning to Read and WriteThe core advantage of this technology lies in its unique learning method, which accumulates an understanding of the appearance and meaning of text by constantly rewriting and learning handwritten text by imitating the human reading and learning process. Compared with traditional optical character recognition (OCR) technology, InkSight has shown higher recognition accuracy when dealing with handwritten text in complex backgrounds, blurry or low-light conditions.

This tutorial contains 2 functions:

Word-level transcription: This feature supports word-level transcription, where the input image is converted into a single word and the output is InkSight.
Full page transcription: This feature supports the whole page level. The input image can be the entire writing page, and the output is the full InkSight.

InkSight has a very high recognition accuracy. Experiments show that humans can read the text tracing generated by InkSight with an accuracy of up to 87%, and more than two-thirds of the tracing results are almost indistinguishable from real handwriting. This means that InkSight can not only recognize handwritten text, but also restore the handwritten content with extremely high accuracy, which is a great boon for users who like to record handwriting.

InkSight also shows great potential in the field of cultural heritage protection. It can effectively digitize precious handwritten documents, facilitate historical research, and protect and pass on languages and cultures that are less digitized.

InkSight's technology not only surpasses traditional OCR technology, but also brings new breakthroughs in the field of handwriting recognition. It uses modern machine learning technologies such as deep learning and neural networks to make the recognition of handwritten text more flexible and powerful. The launch of this technology may trigger a race for more innovations and breakthroughs in the handwriting recognition track.

2. Operation steps

After starting the container, wait for about 5 seconds to load the model, and click the API address to enter the web interface.

1. Word transcription

Select Word-level inference
Upload a single word handwritten
Click ink to render
View the rendering results

2. Full page transcription

Select Full page inference
Upload a full page of handwriting
Click ink to render
View the rendering results

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