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Label data for ML/DL methods with ease

[Not finished yet!]

Some existing tools

Blogs

A Definitive Guide To Build Training Data For Computer Vision

This one

Design Philosophy

Semi-automatic labeling, label aided by algorithms.

Pipeline

Video ->
image frames (png for potential transparent part) ->
distinguish the blurred ->
extracted very N frame for labeling ->
use existing tracking algorithms to track, both forward and backward ->
combine the tracked BBox -> refine BBox (optional) ->
train with ML detection algorithms

NOTES

  • the object is out of the scene for tracking
  • data format transfer coco2pascal.py

TODO

It seems that, we need a UI, really.

Possible lib:

Dependencies

  • dlib

  • labelme

  • scipy

  • preprocess

  • tqdm

  • scikit-image

  • json_tricks

  • imutils

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Data labeling with ease.

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