Today, we are announcing CognitiveJ, an open source Java library that makes it easy to detect, interpret, and identify faces or features contained within raw images.
Powered by Project Oxford, the library can suggest a persons age, gender, and emotional state. Based on machine learning, the library can also attempt to interpret and describe what is contained within an image.
It's being released for public preview under the Apache 2 License and at the time of this writing, and the features include:
Facial Detection: Capture faces, gender, age, associated facial features, and landmarks from an image.
Emotion Detection: Derive emotional state from faces within an image.
Verification: Verify, with a confidence scale, on whether two different faces are of the same person.
Identification: Identify a person from a set of known people.
Find Similar: Detect, group, and rank similar faces.
Grouping: Group people based on facial characteristics.
Person Group/Person/Face Lists: Create, manage, and train groups, face lists, and persons to interact with identification/grouping/find similar face features.
Image Describe: Describe visual content of an image and return real world caption to what the image contains.
Image Analysis: Extract key details from an image and if the image is of an adult/racy nature.
OCR: Detect and extract a text stream from an image.
Thumbnail: Create thumbnail images based on key points of interest from an image.
Apply layers onto images to visually represent found features.
Apply captions onto faces and images.
Graphically illustrate the Faces/Vision feature sets.
Pixelate faces within an image.
Other Notable Features
Supports local and remote images.
Validation of parameters.