pip install pyside6
运行designer.exe
保存为main_window.ui文件
Vscode将.ui文件转成.py文件方法：Vscode将.ui文件转成.py文件方法_vscode 将 .ui 转为 .py 输出_流动的星的博客-CSDN博客
编译成.py文件，右键编译：
可能会出现关于utf8编码问题,没有出现可忽略:
（一）实现检测图片和检测视频的基本代码框架：
import sys
import PySide6
from PyQt5.QtWidgets import QMainWindow,QApplication
# from PySide6.QtWidgets import QMainWindow,QApplication
from Ui_main_window import Ui_MainWindow
import os
dirname = os.path.dirname(PySide6.__file__)
plugin_path = os.path.join(dirname, 'plugins', 'platforms')
os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = plugin_path
# def covert2QImage(img):
# height,width,channel = img.shape
# return QImage(img,width,height,width * channel,QImage.Formate_RGB888)
class MainWindow(QMainWindow,Ui_MainWindow):
def __init__(self):
super(MainWindow,self).__init__()
self.setupUi(self)
self.bind_slots()
def open_image(self):
print("点击了检测图片")
def open_video(self):
pass
def bind_slots(self):
self.det_image.clicked.connect(self.open_image)
self.det_video.clicked.connect(self.open_video)
if __name__ == "__main__":
app = QApplication(sys.argv)
# app = QApplication([])
window = MainWindow()
window.show()
app.exec() （二）图片检测代码编写：
import sys
import PySide6
import torch
# from PySide6.QtWidgets import QMainWindow,QApplication,QFileDialog
# from PySide6.QtGui import QPixmap
from PyQt5.QtWidgets import QMainWindow,QApplication,QFileDialog
from PyQt5.QtGui import QPixmap,QImage
from Ui_main_window import Ui_MainWindow
import os
dirname = os.path.dirname(PySide6.__file__)
plugin_path = os.path.join(dirname, 'plugins', 'platforms')
os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = plugin_path
def covert2QImage(img):
height,width,channel = img.shape
return QImage(img,width,height,width * channel,QImage.Format_RGB888)
class MainWindow(QMainWindow,Ui_MainWindow):
def __init__(self):
super(MainWindow,self).__init__()
self.setupUi(self)
self.model = torch.hub.load("./","custom",path="runs/train/exp12/weights/best.pt",source="local")
self.bind_slots()
def image_pred(self,file_path):
results = self.model(file_path)
image = results.render()[0]
return covert2QImage(image)
def open_image(self):
print("点击了检测图片")
# file_path = QFileDialog.getOpenFileName(self,dir="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PySide6.QtWidgets
file_path = QFileDialog.getOpenFileName(self,directory="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PyQt5.QtWidgets
if file_path[0]:
file_path = file_path[0]
qimage = self.image_pred(file_path)
self.input.setPixmap(QPixmap(file_path))
self.output.setPixmap(QPixmap.fromImage(qimage))
def open_video(self):
pass
def bind_slots(self):
self.det_image.clicked.connect(self.open_image)
self.det_video.clicked.connect(self.open_video)
if __name__ == "__main__":
app = QApplication(sys.argv)
# app = QApplication([])
window = MainWindow()
window.show()
app.exec() 》》效果图：
（三）视频检测代码编写
方案一：
import sys
import PySide6
import torch
import cv2
# from PySide6.QtWidgets import QMainWindow,QApplication,QFileDialog
# from PySide6.QtGui import QPixmap
from PyQt5.QtWidgets import QMainWindow,QApplication,QFileDialog
from PyQt5.QtGui import QPixmap,QImage
from Ui_main_window import Ui_MainWindow
import os
dirname = os.path.dirname(PySide6.__file__)
plugin_path = os.path.join(dirname, 'plugins', 'platforms')
os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = plugin_path
def covert2QImage(img):
height,width,channel = img.shape
return QImage(img,width,height,width * channel,QImage.Format_RGB888)
class MainWindow(QMainWindow,Ui_MainWindow):
def __init__(self):
super(MainWindow,self).__init__()
self.setupUi(self)
self.model = torch.hub.load("./","custom",path="runs/train/exp12/weights/best.pt",source="local")
self.bind_slots()
def image_pred(self,file_path):
results = self.model(file_path)
image = results.render()[0]
return covert2QImage(image)
def open_image(self):
print("点击了检测图片")
# file_path = QFileDialog.getOpenFileName(self,dir="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PySide6.QtWidgets
file_path = QFileDialog.getOpenFileName(self,directory="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PyQt5.QtWidgets
if file_path[0]:
file_path = file_path[0]
qimage = self.image_pred(file_path)
self.input.setPixmap(QPixmap(file_path))
self.output.setPixmap(QPixmap.fromImage(qimage))
def image_pred(self,img):
results = self.model(img)
image = results.render()[0]
return covert2QImage(image)
def open_video(self):
print("点击了检测视频")
file_path = QFileDialog.getOpenFileName(self,directory="./datasets",filter="*.mp4") # PyQt5.QtWidgets
if file_path[0]:
file_path = file_path[0]
video = cv2.VideoCapture(file_path)
while True: # 缺点，引起事件阻塞
ret,frame = video.read()
if not ret:
break
frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
qimage = self.image_pred(frame)
self.input.setPixmap(QPixmap(covert2QImage(frame)))
self.output.setPixmap(QPixmap.fromImage(qimage))
def bind_slots(self):
self.det_image.clicked.connect(self.open_image)
self.det_video.clicked.connect(self.open_video)
if __name__ == "__main__":
app = QApplication(sys.argv)
# app = QApplication([])
window = MainWindow()
window.show()
app.exec() 存在缺陷： 引起事件阻塞
方案二：设置timer
import sys
import PySide6
import torch
import cv2
# from PySide6.QtWidgets import QMainWindow,QApplication,QFileDialog
# from PySide6.QtGui import QPixmap
from PyQt5.QtWidgets import QMainWindow,QApplication,QFileDialog
from PyQt5.QtGui import QPixmap,QImage
from PyQt5.QtCore import QTimer
from Ui_main_window import Ui_MainWindow
import os
dirname = os.path.dirname(PySide6.__file__)
plugin_path = os.path.join(dirname, 'plugins', 'platforms')
os.environ['QT_QPA_PLATFORM_PLUGIN_PATH'] = plugin_path
def covert2QImage(img):
height,width,channel = img.shape
return QImage(img,width,height,width * channel,QImage.Format_RGB888)
class MainWindow(QMainWindow,Ui_MainWindow):
def __init__(self):
super(MainWindow,self).__init__()
self.setupUi(self)
self.model = torch.hub.load("./","custom",path="runs/train/exp12/weights/best.pt",source="local")
#创建timer
self.timer = QTimer()
self.timer.setInterval(0.05)
self.video = None
self.bind_slots()
def image_pred(self,file_path):
results = self.model(file_path)
image = results.render()[0]
return covert2QImage(image)
def open_image(self):
print("点击了检测图片")
# file_path = QFileDialog.getOpenFileName(self,dir="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PySide6.QtWidgets
file_path = QFileDialog.getOpenFileName(self,directory="./datasets/images/train",filter="*.jpg;*.png;*.jpeg") # PyQt5.QtWidgets
if file_path[0]:
file_path = file_path[0]
qimage = self.image_pred(file_path)
self.input.setPixmap(QPixmap(file_path))
self.output.setPixmap(QPixmap.fromImage(qimage))
def video_pred(self):
ret,frame = self.video.read()
if not ret:
self.timer.stop()
else:
frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
self.input.setPixmap(QPixmap.fromImage(covert2QImage(frame)))
results = self.model(frame)
image = results.render()[0]
self.output.setPixmap(QPixmap.fromImage(covert2QImage(image)))
def open_video(self):
print("点击了检测视频")
file_path = QFileDialog.getOpenFileName(self,directory="./datasets",filter="*.mp4") # PyQt5.QtWidgets
if file_path[0]:
file_path = file_path[0]
self.video = cv2.VideoCapture(file_path)
self.timer.start()
def bind_slots(self):
self.det_image.clicked.connect(self.open_image)
self.det_video.clicked.connect(self.open_video)
# 绑定timer
self.timer.timeout.connect(self.video_pred)
if __name__ == "__main__":
app = QApplication(sys.argv)
# app = QApplication([])
window = MainWindow()
window.show()
app.exec() 解决一些小Bug:关闭定时器
（四）最终实现效果演示视频：
演示视频