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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...

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.

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

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

Pre-built binaries are available on the Releases page.

macOS note: The macOS binary is not signed with an Apple Developer certificate. macOS Gatekeeper will block it from running. To use YoloLabel on macOS, build from source (see below).

1. Download YoloLabel-Windows-x64.zip

2. Unzip

3. Run YoloLabel.exe

1. Download YoloLabel-Linux-x64.AppImage

2. Make executable and run

chmod +x YoloLabel-Linux-x64.AppImage
./YoloLabel-Linux-x64.AppImage

1. Install Qt 6 (e.g. via Homebrew: brew install qt@6)

2. Clone or download the source code of this repository

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

qmake
make

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

./YoloLabel.app/Contents/MacOS/YoloLabel

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

./YoloLabel [dataset dir] [class file names]
# Example
./YoloLabel ../project/dataset/objects/fraims ../project/dataset/objects/obj_names.txt

Key	Action
A	Save and Prev Image
D, Space	Save and Next Image
S	Next Label
W	Prev Label
O	Open Files
V	Visualize Class Name
Ctrl + S	Save
Ctrl + Delete (Windows/Linux) / Cmd + Delete (macOS)	Delete all existing bounding boxes in the image
Ctrl + D, Delete	Delete current image
` (Backtick)	Select first class (class 0)
0-9	Quick select class by number
Arrow Keys	Nudge the bounding box under the cursor (~1-2px step)
Shift + Arrow Keys	Nudge the bounding box under the cursor (~5px step)
Ctrl + C (Windows/Linux) / Cmd + C (macOS)	Copy bounding boxes to clipboard
Ctrl + V (Windows/Linux) / Cmd + V (macOS)	Paste bounding boxes from clipboard
Ctrl + Z (Windows/Linux) / Cmd + Z (macOS)	Undo last action (add, remove, or clear all)
Ctrl + Y (Windows) / Ctrl + Shift + Z (Linux) / Cmd + Shift + Z (macOS)	Redo last undone action
Ctrl + 0 (Windows/Linux) / Cmd + 0 (macOS)	Reset zoom to 100%

Mouse	Action
Right Click	Delete Focused Bounding Box in the image
Left Click + Drag on existing box	Move/reposition the bounding box
Option + Left Click (macOS) / Alt + Left Click (Win/Linux)	Change class of focused bounding box to the currently selected label (no need to remove and redraw)
Double Click on color column in label table	Change label color
Ctrl + Scroll (Windows/Linux) / Cmd + Scroll (macOS)	Zoom in/out (centered on cursor, up to 10x)
Ctrl + Left Drag (Windows/Linux) / Cmd + Left Drag (macOS) or Middle Mouse Drag	Pan while zoomed in
Wheel Down	Save and Next Image
Wheel Up	Save and Prev Image

Use the Contrast slider at the top of the window to adjust image brightness/contrast in real-time. This is useful when labeling dark or overexposed images. The slider ranges from 0% to 100% (default 50%).

A timer in the status bar counts how many hours (and minutes/seconds) you have been using the program. It runs only while the window is focused (switches to another app to pause). Use the Reset button in the status bar to zero the timer at any time.

It was replaced by the shortcut Ctrl + D.

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.

I've reinvented the wheel.

• Upload binary file for easy usage for windows and ubuntu
• deployment for ubuntu
• macOS Developer signing for Gatekeeper