Image Recognition API: The Straightforward Approach at Chooch AI

Image recognition is one of the most popular and recognizable applications of artificial intelligence, machine learning, and computer vision. And now, highly accurate, real-time image recognition is available for developers via image recognition APIs. Some platforms offer APIs that can help organizations add image and video analysis capabilities, but what’s needed is a easy-to-implement image recognition API that offers powerful computer vision services – like Chooch AI.

What is an Image Recognition API?

An image recognition API (short for “application programming interface”) is a set of procedures that defines how two different machines communicate: a client that wants to perform image recognition, and a server that executes the task of image recognition for the client. (Check out our article on the difference between an image recognition API and an image recognition SDK.)

You can think of an API as a kind of black box that allows users to interact with it via a limited set of pre-defined queries: the user sends a request, and the API returns the information the user has requested. In the case of an image recognition API, the user’s request will typically contain an image, and the API will return its best-guess prediction for the contents of that image.

The Benefits of an Image Recognition API

The benefits of an image recognition API include:

• Cost savings: Many businesses have access to more images and videos than they could possibly analyze with human employees, even working for hundreds of years around the clock. Image recognition APIs, meanwhile, can process input and return an answer in a fraction of a second, making them much more cost-effective.
• Time savings: While it’s possible to build your own image recognition system in-house, doing so requires full-time access to AI and deep learning experts—not to mention the long development time required. Using pre trained learning models can save you months of effort (plus additional time to retrain or recalibrate the system as necessary).
• High degree of accuracy: Today’s image recognition models are capable of equaling (or even exceeding) human performance on many tasks, especially given the human capacity to make mistakes and get tired. Cutting-edge image recognition APIs are more than accurate enough to be production-ready for many critical use cases.

How to Adopt an Image Recognition API with Chooch

Chooch is a visual AI company with a powerful, flexible, enterprise-class image recognition API, built by our dedicated team of computer vision experts. The Chooch platform is an all-in-one, user-friendly tool that unites every step of building AI models, from data collection and model development to training and deployment. Our clients have used the Chooch image recognition API to do everything from facial authentication to detecting forest fires.

Getting started with the Chooch image recognition API is simple—just check out these computer vision AI API videos

Use Chooch’s image recognition API by following these steps:

1. In the Chooch dashboard, create a new AI model (known as a “perception”). To perform image recognition, each perception requires the identification of one or more classes of objects. For example, you might create a perception to recognize different dog breeds with classes such as golden retriever, bulldog, and chihuahua.
2. For each class, upload images of objects that belong to that class. For optimal performance, you should have a large and diverse set of images taken from different perspectives, in different conditions, etc.
3. Once the model has been created and tested, it’s ready for real-world production use. Given a photo or video, the model will return its best guess for the image content. For example, a model trained to do facial recognition will return its best guess for the detected face, while another model that analyzes images for adult content will return a binary yes/no decision based on a pre-defined confidence interval.

The image recognition API from Chooch AI is a simple, REST-based API that uses the JSON data format. Below is an example of a client request to the image recognition API using Python:

import requests
import json
url = ‘https://api.chooch.ai/predict/image?url=https://s3.amazonaws.com/choochdashboard/base_site/ronaldo_suit.jpg&apikey=346g5717-1sd3-35h6-9104-b8h5c819dn19’
response = requests.post(url)
print(response.content)

In response to this request, the image recognition API will return a response in real time containing information such as:

• The status of the request
• A list of predictions about the image’s content
• The coordinates of each object in the image
• The number of times that each object appears in the image

Conclusion

The benefits of a dedicated image recognition API are countless. It saves employees from tedious manual work, while businesses can start enjoying highly accurate performance immediately instead of taking months to build their own image recognition system. Check out our computer vision API videos to see just how easy it is to get started, or sign up for our AI platform to get your free API key for the Chooch image recognition API. Or, for more information sign up for an image recognition demo or object recognition demo.