Hive's text recognition models detect and transcribe each word in an image. They also return semantically grouped and ordered text blocks (Block Text) in their natural reading order for detections that are spatially close. For details on our OCR moderation API, please see the OCR (Text Recognition) Moderation tab.
As part of our OCR endpoints, we also support emoji detection and classification for Apple, Samsung, and Google devices (over 3000 emojis for each).
For documents that have a structure, such as receipts, Hive provides APIs that interpret the structure — such as returning each item on a receipt, its unit price, quantity, and total price.
Note: these models are optimized for images with 150 words or fewer. If you submit images with more words than that, we recommend you split the image into multiple segments and submit them separately.
Our models currently support the following languages:
- Chinese (simplified + traditional)
If you are unsure if your required language is supported/want to request an additional language, please reach out to our sales team ([email protected]).
We've trained our models across a wide variety of domains, including but not limited to the following categories:
- Rotated Text
- Handwritten Text
- Scene Text (text in photographs)
The request format for this API includes a field for the media being submitted, either as a local file path or as a url. For more information about submitting a task, see our API reference guides to synchronous and asynchronous submissions.
# submit a task with media with url curl --request POST \ --url https://api.thehive.ai/api/v2/task/sync \ # this is a sync example, see API reference for async --header 'accept: application/json' \ --header 'authorization: token <API_KEY>' \ --form 'url=http://hive-public.s3.amazonaws.com/demo_request/gun1.jpg' # submit a task with media with local media file curl --request POST \ --url https://api.thehive.ai/api/v2/task/sync \ # this is a sync example, see API reference for async --header 'Authorization: Token <token>' \ --form 'media=@"<absolute/path/to/file>"'
Updated 8 months ago