- Text in Image
- Celebrity Recognition
- Object Detection
- Custom Classification
- Auto-tagging (Image)
Digital media analysis and documentation made seamless
(95 ratings)
Starts from $1Pay As You Go, also offers free forever plan
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The Microsoft Computer Vision API detects objects, faces, barcodes, and texts in images across 20+ languages. It performs face detection on up to 8 faces simultaneously, and can detect smiles, facial landmarks, and blink states. It also uses AI to ... Read More
Text in Image is a powerful software feature that allows users to insert text into images seamlessly. Whether it's for creating promotional materials, adding captions to social media posts, or personalizing photos, Text in Image makes it easy and efficient to enhance any visual content. With Text in Image, users have the ability to choose from a variety of fonts, sizes, and colors to customize their text. This gives them the flexibility to match the text with the overall look and feel of the image. Furthermore, the
Celebrity recognition is a cutting-edge technology that uses artificial intelligence to identify celebrities in photos and videos. This feature is highly useful for businesses and media companies that need to quickly and accurately identify celebrities for marketing, advertising, or security purposes. With this feature, users can simply upload an image or video and the software will automatically detect and recognize any famous faces present. The technology uses advanced algorithms to analyze facial landmarks and match them with a database of celebrity images, resulting in efficient and reliable identification.
Object detection is a powerful software feature that allows users to identify and locate different objects within an image or video. It utilizes advanced algorithms and techniques to recognize and categorize objects based on their visual characteristics, such as shape, color, and texture. With object detection, users can easily detect and track individuals, vehicles, and other uniquely identifiable objects in real-time. This feature is especially useful in surveillance systems and traffic management, helping to enhance security and optimize roadway operations. One of the key components of
Custom Classification is a feature that is commonly found in software applications. It is a method of organizing and categorizing data in a customized manner according to the user's needs and preferences. Essentially, it allows users to create their own unique classification system, specific to their business or personal requirements. With Custom Classification, users can define their own categories, subcategories, and even sub-subcategories to classify data. This means that the data can be arranged in a way that is most relevant and meaningful to the
Auto-tagging (Image) is a feature that utilizes advanced image recognition technology to automatically assign relevant tags or labels to images. This means that instead of manually typing in keywords or tags for each image, the software can quickly analyze the visual content and accurately assign the appropriate tags. This saves users a great deal of time and effort, as manually tagging images can be a tedious and time-consuming task. The auto-tagging feature greatly benefits businesses and individuals who deal with large amounts of images on a regular
Starts from $1, also offers free forever plan
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Disclaimer: Pricing information for Microsoft Computer Vision API is provided by the software vendor or sourced from publicly accessible materials. Final cost negotiations and purchasing must be handled directly with the seller. For the latest information on pricing, visit website. Pricing information was last updated on .
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The Microsoft Computer Vision API detects objects, faces, barcodes, and texts in images across 20+ languages. It performs face detection on up to 8 faces simultaneously, and can detect smiles, facial landmarks, and blink states. It also uses AI to read license plates of moving vehicles, understand sentiment in text, determine if an object is visible in an image, and find similar images from a CMYK color space.
Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].
Researched by Rajat Gupta