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Content that is classified as ‘Not Safe for Work’ (NSFW) usually features racy, offensive, or undesirable visualizations. To ensure none of this type of content makes its way to your company’s website or application, you can utilize the following API in Ruby to automatically detect NSFW content in an image and provide a NSFW score and classification.

Let’s start by installing the Ruby client:

After the installation, we can input the image, configure the API key, and call the function:


Outdated file formats can be a difficult roadblock when it comes to sharing or manipulating the contents of the files. One way to remove this roadblock is converting to another, more convenient format, such as CSV. Since conversions themselves can be complicated as well, we will be showing you how to automatically convert an Excel (97–2003) file to CSV in Ruby.

We will start by adding the Ruby client to the Gemfile:

After this, we can input the file and API key into the following code to call the ConvertDocumentXLStoCSV function:


Looking for an easy way to detect age from an image without going through the long and laborious process of training an AI with Deep Learning? If so, you’re in the right place; in this quick tutorial, we will demonstrate how you can use an API in Ruby to instantly detect the age of human faces from an image, along with their position and size.

To begin, we will add the Ruby client to the Gemfile:

Next, we can call the function with the following code:


If you’re noticing inappropriate images sneaking into the content of your website, it may be time to integrate a system to recognize the ‘Not Safe for Work’ materials so you can eliminate any potentially damaging repercussions to your company’s reputation. In this short tutorial, we will show you how to use an API in C/C++ to automatically detect NSFW content from images and provide a NSFW score and classification.

Our first step is installing libcurl into our C/C++ project:

Next, we can call the function with the following code:


File conversions are not the easiest processes to perform manually, especially when working with outdated formats such as the 97–2003 version of Excel. In this tutorial, we will demonstrate how you can simplify a conversion from XLS to the CSV format by using an API in C/C++.

Let’s begin by installing libcurl:

Then, we can call the ConvertXLStoCSV function with the following code:


Gathering demographic information from images has never been easier — instead of perusing photos and attempting to analyze age, you can use Deep Learning technology to do the job for you. The following API leverages Deep Learning to identify the age, position, and size human faces in an image, and even provides a recognition confidence level on top of that.

The first step is to install libcurl in your C/C++ project:

After the installation, you can call the function with the below example code:


Ensuring all images portrayed on your website or application meet your content standards can be a constant and lengthy chore. In this brief article, we will show you how to turn the task of detecting undesirable image content into a quick and efficient process by using an API in Go. The API supports most common input image formats, such as PNG and JPG.

To call the image function, we will input the image file and our API key into the following code:


CSV files are frequently the chosen format for developers who need to organize data in a straightforward and simple manner. If you receive a data file in the old Excel (97–2003) format, you will most likely want to switch it to a more convenient and compatible format as soon as possible. In this quick tutorial, we will demonstrate how you can use an API in Go to automatically convert an XLS file to CSV — no hassle needed.

We can simply input the XLS file into the following example code to call the conversion function:


Determining the user demographics of your website can be incredibly helpful for crafting targeted marketing materials and campaigns. These demographics can be gathered in a number of ways, but one that is particularly simple is analyzing images uploaded by users to provide age data on each human face in the photo. …


Maintaining a website that allows users to upload content is a demanding task; with the wide variety of content that is available online, it’s hard to keep track of which materials contain racy or inappropriate content, and which do not. If you frequently encounter content on your site that could damage your company’s reputation, it may be time to integrate a safety net. In this quick tutorial, we will show you how to automatically detect ‘Not Safe for Work’ content from an image by using an API in Swift.

Simply input your image file and API key into the below…

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