[yolov5 practice 5] traffic sign recognition system based on yolov5 -yolov5 integration pyqt5

Practical blog Guide ( Ongoing update …)：

1. Construction of actual combat environment
2. Custom datasets
3. model training
4. Model testing and evaluation
5. YOLOv5 Integrate PyQt5

After the first four steps, it has been successfully built YOLOv5 Environment and completed the traffic sign recognition system . But because of YOLOv5 There is no graphical interface , So use it here YOLOv5 Integrate PyQt5 Make a simple visual interface .

Preview it , The resulting interface looks like this ：

1. install PyQt5

Type the following command to install PyQt5:

pip install PyQt5
pip install PyQt5-tools

2. start-up PyQt5

Open console , Enter the following command , You can open Qt Tools ：

designer.exe

If you report an error, you can check whether something is missing , And then use pip Install and restart .
If the startup is successful, you will get the interface shown in the following figure ：

choice Main Window, And I'm gonna go ahead and create , You can get the following interface ：

3. Layout creation

Then we will add two buttons and a text box , Used to select image or video and display area .
You can choose what we need on the left as shown in the figure above Push Button, Used to create buttons . and label You can go through the filter Filter to get . Then change the name of the button , The results shown in the figure above are obtained .

Then select these two buttons , Right click to select vertical layout ：

Then select the button and text box , Use horizontal layout .

For adaptive layout , That is, when you zoom in 、 When you reduce the size of the window , Still keep the scale of the interface elements , Can be in a blank space , Right click , choice Layout --> Horizontal layout

Then modify the size scale

Finally, adjust the width and height of the button , You can complete the layout style .

And save it , obtain untitled.ui file .

4. Convert to py file

Start the terminal under the path of this file , Run the following code to convert it to py file ：

pyuic5.bat -o main.py untitled.ui

Finally, bind the corresponding button with the relevant code , Relevant functions can be realized .

5. Sample demonstration

Picture detection
Click image detection , Select relevant pictures , Then we get the following results ：