GUI for marking bounded boxes of objects in images for training neural network YOLO
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Yolo_label

WHAT IS THIS?!

Reinventing The Wheel!!!!

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In the world, there are many good image labeling tools for object detection. -e.g. , (Yolo_mark, BBox-Label-Tool, labelImg).

But... I reinvented it...

WHY DID YOU REINVENT THE WHEEL? ARE YOU STUPID?

When I use the pre-existing program to annotate a training set for YOLO V3, I am sooooooooooo bored...

So I thought about why it is so fxxking bored??

And I found that anwer.

The answer is that pre-existing programs are not sensitive.

So I decided to make a sensitive image labeling tool for object detection.

SHOW ME YOUR SENSITIVE IMAGE LABELING TOOL!!

It's the SENSITIVE image labeling tool for object detection!

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HMM... I SAW THIS DESIGN SOMEWHERE

I referred to the website of Joseph Redmon who invented the YOLO.

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TUTORIAL / USAGE

  1. Put your .jpg, .png -images into some directory (In this tutorial I will use the Kangarooo and the Raccoon Images. These images are in the 'Samples' folder.)

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  1. Put names of objects, one for each line in some file( .txt, .names) and save

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  1. Run Yolo label!

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  1. Click the button 'Open Files'and open the directory that you saved your custom images and object name lists file that you saved at step 2.

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  1. And... Drag and Drop... Welcome to Hell... I really hate this work in the world