videoanalytics

Python library for prototyping of video analytic applications. Relies on OpenCV, Keras, and other standard computer vision and machine learning python packages.

References:

• Code for YOLOv4 and DeepSORT was adapted from yolov4-deepsort.

Component reference

Components are organized as Sources and sinks which are instanced and connected at execution time as pipelines. Sources consume data from a camera or file and trigger the processing pipeline. Sinks process data that was made available from other components and generate new.

• Sources
  • VideoReader
• Sinks
  • Object detection
    • YOLOv4Detector
    • DetectorCSV
  • Visualization
    • Bounding box annotation
    • Matplotlib
  • Outputs
    • Metadata
      • DetectionsCSVWriter
        • Store object detections as CSV.
      • TrackingCSVWriter
        • Store tracked objects as CSV.
    • Database
      • InfluxDB.
      • ELasticSearch
    • Video
      • Write frames to video file.

Instructions for developers

Import conda environment (GPU):

conda env create -f videoanalytics-gpu.yml

Some examples are provided as jupyter notebooks.

conda activate videoanalytics-gpu.yml
jupyter notebook .