Yolo_Label

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plotbbox : A Python package to plot pretty bounding boxes on image

YOLOv3Tiny : PyTorch based YOLOv3Tiny implementation

WHAT IS THIS?!

Reinventing The Wheel?!!!!

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

But... I've reinvented one...

WHY DID YOU REINVENT THE WHEEL? ARE YOU STUPID?

When I used the pre-existing programs to annotate a training set for YOLO V3, I was sooooooooooo bored...

So I thought why it is so boring??

And I found an answer.

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!

HMM... I SAW THIS DESIGN SOMEWHERE

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

TUTORIAL / USAGE

Install and Run

1. Download this project

For Windows

2. Download YOLOLabel_20211126_v1.0

3. Unzip

4. Run YoloLabel.exe

For macOS

2. Clone or download the source code of this repository

3. Open terminal and type command in the downloaded directory.

yourMacOS:Yolo_Label you$ qmake
yourMacOS:Yolo_Label you$ make

4. Run YoloLabel.app/Contents/MacOS/YoloLabel in terminal or double click YoloLabel.app to run

yourMacOS:Yolo_Label you$ ./YoloLabel.app/MacOS/YoloLabel

Prepare Custom Dataset and Load

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

2. Put the names of the objects, each name on a separate line and save the file( .txt, .names).

3. Run Yolo Label!

4. Click the button 'Open Files' and open the folder with the images and the file(''.names or ''.txt) with the names of the objects.

5. And... Label!... Welcome to Hell... I really hate this work in the world.

This program has adopted a different labeling method from other programs that adopt "drag and drop" method.

To minimize wrist strain when labeling, I adopted the method "twice left button click" method more convenient than

"drag and drop" method.

drag and drop

twice left button click

6. End

SHORTCUTS

Key	Action
A	Save and Prev Image
D, Space	Save and Next Image
S	Next Label
W	Prev Label
Ctrl + S	Save
Ctrl + C	Delete all existing bounding boxes in the image
Ctrl + D	Delete current image

Mouse	Action
Right Click	Delete Focused Bounding Box in the image
Wheel Down	Save and Next Image
Wheel Up	Save and Prev Image

Button Events

Remove

ETC

You can access all image by moving horizontal slider bar. But when you control horizontal slider bar, the last processed image will not be saved automatically. So if you want not to lose your work, you should save before moving the horizontal slider bar.

CONCLUSIONS

I've reinvented the wheel.

TO DO LISTS

Upload binary file for easy usage for windows and ubuntu

deployment for ubuntu

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