Introduction
YOLOSHOW is a graphical user interface (GUI) application embed withYOLOv5 YOLOv7 YOLOv8 YOLOv9 RT-DETR algorithm.
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Demo Video
YOLOSHOW v1.x : YOLOSHOW-YOLOv9/YOLOv8/YOLOv7/YOLOv5/RTDETR GUI
YOLOSHOW v2.x : YOLOSHOWv2.0-YOLOv9/YOLOv8/YOLOv7/YOLOv5/RTDETR GUI
Todo List
- Add
YOLOv9Algorithm - Adjust User Interface (Menu Bar)
- Complete Rtsp Function
- Support Instance Segmentation （
YOLOv5&YOLOv8） - Add
RT-DETRAlgorithm (Ultralyticsrepo) - Add Model Comparison Mode（VS Mode）
- Support Pose Estimation （
YOLOv8） - Tracking & Counting (
Industrialization)
Functions
1. Support Image / Video / Webcam / Folder (Batch ) Object Detection
Choose Image / Video / Webcam / Folder (Batch ) in the menu bar on the left to detect objects.
2. Change Models / Hyper Parameters dynamically
When the program is running to detect targets, you can change models / hyper Parameters
- Support changing model in
YOLOv5/YOLOv7/YOLOv8/YOLOv9/RTDETR/YOLOv5-seg/YOLOv8-segdynamically - Support changing
IOU/Confidence/Delay time/line thicknessdynamically
3. Loading Model Automatically
Our program will automatically detect pt files including YOLOv5 Models / YOLOv7 Models / YOLOv8 Models / YOLOv9 Models that were previously added to the ptfiles folder.
If you need add the new pt file, please click Import Model button in Settings box to select your pt file. Then our program will put it into ptfiles folder.
Notice :
- All
ptfiles are named includingyolov5/yolov7/yolov8/yolov9/rtdetr. (e.g.yolov8-test.pt) - If it is a
ptfile of segmentation mode, please name it includingyolov5n-seg/yolov8s-seg. (e.g.yolov8n-seg-test.pt) - If it is a
ptfile of pose estimation mode, please name it includingyolov8n-pose. (e.g.yolov8n-pose-test.pt)
4. Loading Configures
- After startup, the program will automatically loading the last configure parameters.
- After closedown, the program will save the changed configure parameters.
5. Save Results
If you need Save results, please click Save MP4/JPG before detection. Then you can save your detection results in selected path.
6. Support Object Detection, Instance Segmentation and Pose Estimation
From YOLOSHOW v2.2，our work supports both Object Detection , Instance Segmentation and Pose Estimation. Meanwhile, it also supports task switching between different versions，such as switching from YOLOv5 Object Detection task to YOLOv8 instance task.
7. Support Model Comparison among Object Detection, Instance Segmentation and Pose Estimation
From YOLOSHOW v2.0，our work supports compare model performance among Object Detection, Instance Segmentation and Pose Estimation.
Preparation
Experimental environment
OS : Windows 11
CPU : Intel(R) Core(TM) i7-10750H CPU @2.60GHz 2.59 GHz
GPU : NVIDIA GeForce GTX 1660Ti 6GB
1. Create virtual environment
create a virtual environment equipped with python version 3.9, then activate environment.
conda create -n yoloshow python=3.9
conda activate yoloshow
2. Install Pytorch frame
Windows: pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
Linux: pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
Change other pytorch version in 
3. Install dependency package
Switch the path to the location of the program
cd {the location of the program}
Install dependency package of program
pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install "PySide6-Fluent-Widgets[full]" -i https://pypi.tuna.tsinghua.edu.cn/simple
pip install -U Pyside6 -i https://pypi.tuna.tsinghua.edu.cn/simple
4. Add Font
Windows User
Copy all font files *.ttf in fonts folder into C:\Windows\Fonts
Linux User
mkdir -p ~/.local/share/fonts
sudo cp fonts/Shojumaru-Regular.ttf ~/.local/share/fonts/
sudo fc-cache -fv
MacOS User
The MacBook is so expensive that I cannot afford it, please install .ttf by yourself. 😂
5. Run Program
python main.py
Frames
