We have Visual Search as a primary interface. However the goal is to build an application agnostic visual data analytics platform. Similar to a relational datab

We have Visual Search as a primary interface. However the goal is to build an application agnostic visual data analytics platform. Similar to a relational database we have high level concepts of indexers (convert image/bounding box into a feature vector), clusterers (cluster feature vectors) and retrievers (retrieve similar images/objects/annotated-regions). To answer second question we also detect objects (VOC, YOLO 9000, Faces etc.), detected objects are also indexed and retrieved when performing visual search. Further you can perform clustering on these set of "indexing" vectors for things such as fast retrieval and quick labeling/annotations. We use Flickr LOPQ to implement ANN but like all other things you can use custom algorithm. I am working on adding indexing over any set of annotations/detections/frames. You can find more information about the design goals and vision behind the project in presentation at https://deepvideoanalytics.com/ https://deepvideoanalytics.com/