This page lists most of the operations available in Vaas.
Vaas supports these data types:
- Object Detections
- Object Tracks
- Image Lists (associate list of images with each frame/timestep)
- Integer (including image classes)
- String (including arbitrary JSON data)
- Rich Text (for rendering on video)
YOLOv3 (video -> detection)
YOLOv3 is an object detection model. See https://pjreddie.com/darknet/yolo/.
Simple Classifier (video -> int)
An image classification model consisting of a simple series of strided convolutional layers. The number of layers is determined based on the input resolution. The model is trained using cross entropy loss.
Detection Filter (detection -> detection)
Filter detections by confidence score or object category.
Track Filter (track -> track)
Filter object tracks based on bounding boxes. For example, specify a sequence of bounding boxes that tracks must pass through in order, or a set of boxes that the tracks must pass through in any order, or multiple sequences or sets.
An overlap-based multi-object tracker. It is similar to https://github.com/abewley/sort but without Kalman filter.
Crop video at a bounding box.
Re-scale video to a different resolution.
Develop an arbitrary Python function using the Vaas Python library in skyhook_pylib.py.
Re-sample any data at a different framerate.
Combine predicates in an AND expression. Predicates are currently evaluated left-to-right, but execution should be automatically optimized in the future.