Forced Ripened Tomato Detection API - TomatoAesis (also known as Forced Ripened Tomato Recognition API or Forced Ripened Tomatoes Detector API) is a cross browsers REST API which get a JSON input with a still photo (as base64 encoded string), containing a longitudinal cross section of a tomato (like in the example picture below) and returns a JSON string which contains predictions of the input photo regarding the probability of Forced Ripened Tomato. The recognized Forced Ripened Tomato have confidence score, timestamp, tagId, tagName. Of course, there are some limitations in order to get a higher accuracy. We recommend properly exposed, unobstructed JPEG photos at 1920x1080 (full HD resolution) where the Forced Ripened Tomato is clear and focused. If the Forced Ripened Tomato details are too small or blured, the accuracy is lower and the AI algorithm may not classify in a proper way. We do not store pictures. Also, the quality and the angles of the camera are very important and it contribute to a higher reading accuracy. It should has varifocal lenses, high shutter speed, good infrared lighting beam, full HD resolution.
Allthough this Automatic Forced Ripened Tomato Detection API (currently we do not offer a Forced Ripened Tomato Detection sdk) is intended for software development and therefore developers, we have also here an Forced Ripened Tomato Detection online application that may be used to check the input and output JSONs of the API. The necessary steps are written below, basically for this real time Forced Ripened Tomato Detection API you send an authorized POST request in JSON format to the API endpoint and you get as JSON response the output as described below through parameters and examples.
This Forced Ripened Tomato Detection API is useful for a large number of domains like apps for: food, tomato growers, e-commerce, food health, students, teachers etc. You own the commercial copyright of the resulted JSON with no additional fee meaning you may use it in your own apps for sale.