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The implementation for this issue on detectron2

This python code uses detectron2 to perform instance segmentation on images, and these predictions are converted to labels/annotations in COCO JSON format

add your COCO JSON path and file name, as to where the files is located or has to be stored add your image/images ( use loop to call the main function, multiple times for multiple images ) path

all the changes related to output and input files and data should be made in detectToLabelConverter.py file

Sample Data

Input image

0

Output file

train.json

LABEL/ANNOTATION VISUALS

image

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Go from model.predict() to annotations.json in one line. This tool handles the mind-numbing task of formatting your predictions into COCO, so you can get back to arguing about activation functions.

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