According to the Microsoft documentation, Computer Vision is a cloud-based service that provides developers with access to advanced algorithms for processing images and returning information. By uploading an image or specifying an image URL, Computer Vision algorithms can analyze visual content in different ways based on inputs and user choices.
According to the Microsoft documentation, image type detection is one of the features of Computer Vision that can categorize an image as either a photograph or a drawing. You can use the image type detection feature by calling the Analyze Image API with the visualFeatures parameter set to ImageType. The API will return a JSON response with an imageType field that indicates whether the image is a photo or a clipart.
According to the Microsoft documentation, image descriptions is another feature of Computer Vision that can generate a caption for an image. You can use the image descriptions feature by calling the Analyze Image API with the visualFeatures parameter set to Description. The API will return a JSON response with a description field that contains a list of captions for the image, each with a confidence score.
Therefore, by using these two features of Computer Vision, you can achieve your app requirements with minimal development effort. You don't need to use any other services, such as object detection, content tags, or Custom Vision, which are designed for different purposes.

1 - or the knowledge base, select Show active learning suggestions.
2 - Approve and reject suggestions.
3 - Save and train the knowledge base.
4 - Publish the knowledge base.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/how-to/improve-knowledge-base

"When an AI application relies on personal data, such as a facial recognition system that takes images of people to recognize them; you should make it clear to the user how their data is used and retained, and who has access to it." from: https://docs.microsoft.com/en-us/learn/paths/prepare-for-ai-engineering/