Deploy your AI into production on a highly scalable REST API entirely managed by Theos.
Overview
Deploy is the fifth section of the platform. Here you can deploy your AI into a highly scalable REST API entirely managed by Theos, so you can finally use it in your software.
Create a new deployment
Go to the Deploy section of Theos and click the New deployment button to deploy your AI into a highly scalable REST API. Write a name for your deployment and click confirm.
Configure your deployment
Choose the algorithm
Choose the algorithm version you used to train your AI.
Choose the weights
Choose which weights you want your AI to use.
Deploy your AI
Click the Finish button to deploy your AI to a highly scalable REST API. Your AI should be deployed within a few minutes.
Try out your AI inside the playground
Drag and drop an image to Theos and click the Detect button to try your AI.
Use your AI in your software
Start using your AI in your software by making simple HTTP post requests to your deployment's URL. If you have one of our professional plans, in addition to having 2x faster response times and no cold starts, you will also have a Fallback URL that you must include to ensure 99.999% up time.
The request has 6 possible fields:
image (required): the binary data of an image or video frame.
conf_thres (optional): is the Minimum confidence value configurable in the Playground, possible values go from 0 to 1.
iou_thres (optional): is the Detection recall value configurable in the Playground, possible values go from 0 to 1.
ocr_model (optional): is the Text Recognition Model value configurable in the Playground, possible values are small, medium or large.
ocr_classes (optional): the class names on which to perform OCR on, they are comma separated. For example: license-plate, billboard, signature.
ocr_language (optional): if the ocr_model is small it is possible to set the target language for reading special characters of particular languages. If unspecified, the default language is English. See the language code list to find your language of choice. Example for reading German: "ocr_language":"deu".