annolid
  • Annolid User Guide
  • Install Annolid
  • Install Detectron2 locally
  • Install Detectron2 on Google Colab
  • Optional: Install older version of Pytorch for YOLACT
  • Extract desired number of frames from a video based on optical flow
  • Display optical flow while extracting frames with –show_flow=True
  • Save all the frames as images
  • Select frames randomly by reservoir sampling
  • Extract all the key frames from a video used by the compression methods
  • Track animals and Auto labeling
  • Output CSV format
  • Config keypoint connection rules, events, and instances
  • Threshold based object segmenation
  • Convert WMV format to mp4 format using ffmpeg
  • Save the extracted frames to a user selected output directory
  • How to track multiple objects in the video?
  • How to convert coco annonation format to YOLOV5 format?
  • How to train a custom YOLOV5 model?
  • How to track objects in a video with the trained model?
  • How to convert labelme labeled dataset to COCO format?
  • How to train a YOLACT model with a custom dataset?
  • How to evaluate a video based on a trained model?
  • Convert the tracking results csv file to Glitter2 csv format
  • Convert the keypoint annotations to labelme format
annolid
  • Python Module Index

Python Module Index

a | t
 
a
- annolid
    annolid.annotation
    annolid.annotation.coco2yolo
    annolid.data
    annolid.datasets
    annolid.gui
    annolid.postprocessing
    annolid.segmentation
    annolid.segmentation.yolact
    annolid.tracker
    annolid.utils
 
t
tests

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