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
Cutie + DINO Body-Part Tracker
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
annolid.postprocessing package
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annolid.postprocessing package
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Submodules
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annolid.postprocessing.glitter module
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annolid.postprocessing.visualizer module
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Module contents
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