Amazon Rekognition | Unsafe Content Detection

Question 1

I can’t find the label I need. How do I request a new label?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 1

Please send us your requests through AWS Customer Support. Amazon Rekognition continuously expands its catalog of labels based on customer feedback.

Question 2

What is Unsafe Content Detection?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 2

Amazon Rekognition’s Unsafe Content Detection is a deep-learning based easy to use API for detection of explicit and suggestive adult content in images. Developers can use this additional metadata to filter inappropriate content based on their business needs. Beyond flagging an image based on presence of adult content, Image Moderation also returns a hierarchical list of labels with confidence scores. These labels indicate specific categories of adult content, thus providing more granular control to developers to filter and manage large volumes of user generated content (UGC). This API can be used in moderation workflows for applications such as social and dating sites, photo sharing platforms, blogs and forums, apps for children, e-commerce site, entertainment and online advertising services.

Question 3

What types of explicit and suggestive adult content does Amazon Rekognition detect?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 3

Amazon Rekognition detects the following types of explicit and suggestive adult content in images:

Explicit Nudity

Nudity

Graphic Male Nudity

Graphic Female Nudity

Sexual Activity

Partial Nudity

Suggestive

Female Swimwear or Underwear

Male Swimwear or Underwear

Revealing Clothes

Amazon Rekognition’s Unsafe Image Detection API returns a hierarchy of labels, as well as a confidence score for each detected label. For instance, given an inappropriate image, Rekognition may return “Explicit Nudity” with a confidence score as a top level label. Developers could just use this to flag content. In the same response, Rekognition also returns second level of granularity by providing additional context like “Graphic Male Nudity” with its own confidence score. Developers could use this information to build more complex filtering logic.

Please note that the Unsafe Image Detection API is not an authority on, or in any way purports to be an exhaustive filter of, explicit and suggestive adult content. Furthermore, this API does not detect whether an image includes illegal content (such as child pornography) or unnatural adult content.

Question 4

Can Amazon Rekognition’s Unsafe Content Detection API detect other inappropriate content besides explicit and suggestive adult content?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 4

Currently, Rekognition only supports the labels we have outlined above. We will work to continuously add and improve labels based on feedback from our customers.

If you require other types of inappropriate content to be detected in images, please reach out to us using the feedback process outlined later in this section.

Question 5

How is Unsafe Content Detection different for video analysis?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 5

Rekognition Video enables you to automatically identify explicit or suggestive adult content and also provides you with timestamps and a confidence score for each content type label.

Question 6

How can I ensure that Rekognition meets my adult image and video detection use case?

Unsafe Content Detection

Amazon Rekognition | Machine Learning

Answer 6

Rekognition’s Unsafe Content Detection models have been and tuned and tested extensively, but we recommend that you measure the accuracy on your own data sets to gauge performance.

You can use the ‘MinConfidence’ parameter in your API requests to balance detection of content (recall) vs the accuracy of detection (precision). If you reduce ‘MinConfidence’, you are likely to detect most of the inappropriate content, but are also likely to pick up content that is not actually explicit or suggestive. If you increase ‘MinConfidence’ you are likely to ensure that all your detected content is actually explicit or suggestive but some inappropriate content may not be tagged. For examples on how to use ‘MinConfidence’ for images, please refer to the documentation here.

In case Rekogntion fails to detect adult content in images or videos, please reach out to us using the feedback process outlined below.