GUI for marking bounded boxes of objects in images for training neural network YOLO
annotationdetectionimage-labelimage-labelingimage-labeling-toollabeling-toolobject-detectiontraining-yoloyoloyolo-annotationyolo-labelyolov2yolov3yolov3-tinyyolov4yolov5yolov6yolov7yolov8
| Samples | ||
| label_img.cpp | ||
| label_img.h | ||
| main.cpp | ||
| mainwindow.cpp | ||
| mainwindow.h | ||
| mainwindow.ui | ||
| README.md | ||
| YoloLabel.pro | ||
Yolo_label
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 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!
HMM... I SAW THIS DESIGN SOMEWHERE
I referred to the website of Joseph Redmon who invented the YOLO.
TUTORIAL / USAGE
- 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.)
- Put names of objects, one for each line in some file( .txt, .names) and save
- Run Yolo label!
- 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.
- And... Drag and Drop... Welcome to Hell... I really hate this work in the world
- End
Shorcuts
| Key | Action |
|---|---|
A |
Save and Next Image |
D, Space |
Save and Prev Image |
S |
Next Label  |
W |
Prev Label  |
Ctrl + S |
Save |
Ctrl + C |
Delete All Rect Box |
| Mouse | Action |
|---|---|
Right Click |
Delete Focused Rect Box |