Explicit Content Detection is the process of identifying and tagging images that contain explicit or offensive content, such as nudity, sexually suggestive or explicit images, hate symbols, and other forms of offensive content. The method involves the use of Computer Vision and Machine Learning techniques, including image recognition algorithms, object detection, and other computer vision methods, to analyze and classify explicit content in images.
The goal of Explicit Content Detection is to help organizations, such as social media platforms, protect their users from potentially harmful or offensive content and ensure compliance with legal and industry regulations.
The first step is to set Axios, a promise-based HTTP client for the browser and Node.js, that will allow you to call Eden AI API.
Next, you'll need to initialize the File System module in order to access local files on your computer.
Finally, you'll need to create your multipart/formdata parameters form:
To perform Explicit Content Detection, you'll need to create an account on Eden AI for free. Then, you will be able to get your API key directly from the homepage with free credits offered by Eden AI.
As shown in the script, we called one Explicit Content Detection engine. Once the parameters values are passed, you can configure your request:
Then, you'll need to launch the request and print the result:
Here is an example of an Explicit Content Detection API response:
As you can see, using Explicit Content Detection with Eden AI API is quick and easy.
We offer a unified API for all providers: simple and standard to use, with a quick switch between providers and an access to the specific features of each provider.
The JSON output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.
With Eden AI you have the possibility to integrate a third party platform: we can quickly develop connectors. To go further and customize your Explicit Content Detection request with specific parameters, check out our documentation.