项目概况
本项目是应用YOLOv8框架实现训练自定义模型实现单一零件的缺陷检测，软件界面由PyQt5实现。
功能已正式使用，识别效果达到预期。
项目实现
项目使用了以下几个要素：
- 全新的界面设计 ，PyQt5结合QtDesigner自定义界面设计，快速构建想要的UI；
- 相机选型和光源 ，项目使用了迈德威视工业相机GYD-GE130M-T，对照官方给出的文档很容易就可以实现相机的使用，光源方面使用12V常规灯带打光，去除其他光源的干扰；
- IO触发 功能，实现串口控制IO，以快速输出检测识别结果，便于对接工业传送装置；
YOLOv8_14">YOLOv8安装及模型训练
可参考该大佬文章: 传送门
项目展示图: 
关键代码展示
迈德威视相机使用线程代码片.
python">import time
import cv2
from ultralytics import YOLO
import numpy as np
from PyQt5 import QtGui
from PyQt5.QtCore import pyqtSignal, QThread
from MindVisionSdk import mvsdk
import warnings
warnings.filterwarnings('ignore')
class MyThread(QThread):
camera_signal = pyqtSignal(object) # 输出相机数据流
info_signal = pyqtSignal(str) # 输出信息状态
def __init__(self, parent=None):
super().__init__(parent)
self.drawLine = False
self.monoCamera = None
self.FrameBufferSize = None
self.isPause = False
self.mCamera = None
self.pFrameBuffer = None
self.model = YOLO(model="./YoloModel/best.pt")
def __del__(self):
mvsdk.CameraUnInit(self.mCamera)
mvsdk.CameraAlignFree(self.pFrameBuffer)
def run(self):
# 枚举相机设备列表
DevList = mvsdk.CameraEnumerateDevice()
if len(DevList) >= 1:
DevInfo = DevList[0] # 选取设备列表第一个相机
try:
self.mCamera = mvsdk.CameraInit(DevInfo, -1, -1)
self.info_signal.emit("【{}】 初始化相机成功".format(time.strftime("%Y-%m-%d %H:%M:%S")))
except mvsdk.CameraException as e:
self.info_signal.emit("【{}】 初始化相机异常:{}".format(time.strftime("%Y-%m-%d %H:%M:%S"), e))
cap = mvsdk.CameraGetCapability(self.mCamera)
self.monoCamera = (cap.sIspCapacity.bMonoSensor != 0)
if self.monoCamera:
mvsdk.CameraSetIspOutFormat(self.mCamera, mvsdk.CAMERA_MEDIA_TYPE_MONO8)
else:
mvsdk.CameraSetIspOutFormat(self.mCamera, mvsdk.CAMERA_MEDIA_TYPE_BGR8)
mvsdk.CameraSetTriggerMode(self.mCamera, 0)
mvsdk.CameraSetAeState(self.mCamera,True) # True为自动曝光 False为手动曝光
mvsdk.CameraSetRotate(self.mCamera, 0)
mvsdk.CameraSetMirror(self.mCamera, 0, True)
mvsdk.CameraPlay(self.mCamera)
# 计算RGB buffer所需的大小，这里直接按照相机的最大分辨率来分配
self.FrameBufferSize = cap.sResolutionRange.iWidthMax * cap.sResolutionRange.iHeightMax * (
1 if self.monoCamera else 3)
# 分配RGB buffer，用来存放ISP输出的图像
# 备注：从相机传输到PC端的是RAW数据，在PC端通过软件ISP转为RGB数据（如果是黑白相机就不需要转换格式，但是ISP还有其它处理，所以也需要分配这个buffer）
self.pFrameBuffer = mvsdk.CameraAlignMalloc(self.FrameBufferSize, 16)
while True:
try:
if not self.isPause:
pRawData, FrameHead = mvsdk.CameraGetImageBuffer(self.mCamera, 10)
mvsdk.CameraImageProcess(self.mCamera, pRawData, self.pFrameBuffer, FrameHead)
if self.drawLine:
mvsdk.CameraImageOverlay(self.mCamera, self.pFrameBuffer, FrameHead)
mvsdk.CameraReleaseImageBuffer(self.mCamera, pRawData)
# 此时图片已经存储在pFrameBuffer中，对于彩色相机pFrameBuffer=RGB数据，黑白相机pFrameBuffer=8位灰度数据
# 把pFrameBuffer转换成opencv的图像格式以进行后续算法处理
frame_data = (mvsdk.c_ubyte * FrameHead.uBytes).from_address(self.pFrameBuffer)
frame = np.frombuffer(frame_data, dtype=np.uint8)
frame = frame.reshape((FrameHead.iHeight, FrameHead.iWidth,
1 if FrameHead.uiMediaType == mvsdk.CAMERA_MEDIA_TYPE_MONO8 else 3))
frame = cv2.resize(frame,(960,540), interpolation=cv2.INTER_LINEAR)
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = self.model.predict(source=frame,verbose=False)
# 提取检测结果
# for result in results:
# boxes = result.boxes.xyxy # 边界框坐标
# scores = result.boxes.conf # 置信度分数
# classes = result.boxes.cls # 类别索引
# # 如果有类别名称，可以通过类别索引获取
# class_names = [self.model.names[int(cls)] for cls in classes]
# # 打印检测结果
# for box, score, class_name in zip(boxes, scores, class_names):
# print(f"Class: {class_name}, Score: {score:.2f}, Box: {box}")
annotated_frame = results[0].plot()
showImage = QtGui.QImage(annotated_frame.data, frame.shape[1], frame.shape[0], QtGui.QImage.Format_RGB888)
self.camera_signal.emit(showImage)
self.info_signal.emit("【{}】 实时显示中......".format(time.strftime("%Y-%m-%d %H:%M:%S")))
except mvsdk.CameraException as e:
if e.error_code != mvsdk.CAMERA_STATUS_TIME_OUT:
self.info_signal.emit("【{}】 实时显示线程报错:{}".format(time.strftime("%Y-%m-%d %H:%M:%S"), e))
finally:
self.msleep(20)
主界面逻辑代码片
python">import os.path
import sys
import time
import cv2
from PyQt5 import QtWidgets
from PyQt5 import QtGui
from PyQt5.QtWidgets import QMessageBox
from WindowUI import Ui_MainWindow
from CameraThread import MyThread
from MindVisionSdk import mvsdk
from Yaml_Tool import myYamlTool
class MainWindow(QtWidgets.QMainWindow, Ui_MainWindow):
def __init__(self):
super(MainWindow, self).__init__()
self.setupUi(self)
self.camera_thread = MyThread()
self.camera_thread.camera_signal.connect(self.showVideo)
self.camera_thread.info_signal.connect(self.showStatus)
self.pushButton_open_close.clicked.connect(self.camera_start_stop)
self.pushButton_play.clicked.connect(self.camera_play_pause)
self.pushButton_play.setEnabled(False)
self.pushButton_catch.clicked.connect(self.catchPicture)
self.pushButton_addline.clicked.connect(self.drawLine)
self.radioButton_run.setStyleSheet("QRadioButton::indicator:!checked {border: 2px solid #8f8f91;}"
"QRadioButton::indicator:checked {background-color: #55ff7f;}"
"QRadioButton::indicator:checked:hover {border: 2px solid #8f8f91;}")
self.radioButton_mark.setStyleSheet("QRadioButton::indicator:!checked {border: 2px solid #8f8f91;}"
"QRadioButton::indicator:checked {background-color: #55ff7f;}"
"QRadioButton::indicator:checked:hover {border: 2px solid #8f8f91;}")
self.yamlTool = myYamlTool()
self.yamlData = self.yamlTool.read_yaml('config.yaml')
if self.yamlData['runMode'] == 'mark':
self.radioButton_mark.setChecked(True)
else:
self.radioButton_run.setChecked(True)
self.radioButton_mark.clicked.connect(lambda: self.selectMode(0))
self.radioButton_run.clicked.connect(lambda: self.selectMode(1))
self.doubleSpinBox_threshold.setValue(self.yamlData['threshold'])
self.doubleSpinBox_threshold.valueChanged.connect(self.thresholdChange)
def closeEvent(self, event):
"""
重写关闭按钮事件
:param event:
:return:
"""
reply = QMessageBox.question(self, '警告', '<font color=red><b>确定退出工具?</b></font>',
QMessageBox.Yes | QMessageBox.No, QMessageBox.No)
if reply == QMessageBox.Yes:
if self.camera_thread.isRunning():
self.camera_thread.__del__()
self.camera_thread.terminate()
event.accept()
else:
event.ignore()
def camera_start_stop(self):
"""
打开关闭相机按钮事件
:return:
"""
if self.pushButton_open_close.text() == "打开相机":
self.camera_thread.start()
self.camera_thread.isPause = False
self.pushButton_open_close.setText("关闭相机")
self.statusbar.showMessage("【{}】 已打开相机".format(time.strftime("%Y-%m-%d %H:%M:%S")))
self.pushButton_play.setEnabled(True)
self.pushButton_play.setText("暂停")
self.pushButton_catch.setEnabled(True)
else:
self.camera_thread.__del__()
self.camera_thread.terminate()
self.camera_thread.isPause = True
self.pushButton_open_close.setText("打开相机")
self.statusbar.showMessage("【{}】 已关闭相机".format(time.strftime("%Y-%m-%d %H:%M:%S")))
self.label_display.setText("相机已关闭")
self.pushButton_play.setEnabled(False)
self.pushButton_play.setText("播放")
self.pushButton_catch.setEnabled(False)
def camera_play_pause(self):
"""
相机暂停和继续
:return:
"""
if self.camera_thread.isRunning():
if self.pushButton_play.text() == "暂停":
mvsdk.CameraPause(self.camera_thread.mCamera)
self.camera_thread.isPause = True
self.statusbar.showMessage("【{}】 实时显示已暂停".format(time.strftime("%Y-%m-%d %H:%M:%S")))
self.pushButton_play.setText("播放")
else:
mvsdk.CameraPlay(self.camera_thread.mCamera)
self.camera_thread.isPause = False
self.statusbar.showMessage("【{}】 实时显示已恢复".format(time.strftime("%Y-%m-%d %H:%M:%S")))
self.pushButton_play.setText("暂停")
def catchPicture(self):
"""
抓取图片
:return:
"""
if self.camera_thread.isRunning():
try:
mvsdk.CameraSetMirror(self.camera_thread.mCamera, 1, True)
pFrameBuffer = mvsdk.CameraAlignMalloc(self.camera_thread.FrameBufferSize, 16)
pRawData, FrameHead = mvsdk.CameraGetImageBuffer(self.camera_thread.mCamera, 1000)
mvsdk.CameraImageProcess(self.camera_thread.mCamera, pRawData, pFrameBuffer, FrameHead)
mvsdk.CameraReleaseImageBuffer(self.camera_thread.mCamera, pRawData)
mvsdk.CameraSetMirror(self.camera_thread.mCamera, 1, False)
# 此时图片已经存储在pFrameBuffer中，对于彩色相机pFrameBuffer=RGB数据，黑白相机pFrameBuffer=8位灰度数据
# 该示例中我们只是把图片保存到硬盘文件中
if self.yamlData['runMode'] == 'mark':
if not os.path.exists("CatchImage"):
os.mkdir("CatchImage")
dirName = 'CatchImage'
else:
if not os.path.exists("RunImage"):
os.mkdir("RunImage")
dirName = 'RunImage'
catchTime = time.strftime("%Y%m%d%H%M%S")
status = mvsdk.CameraSaveImage(self.camera_thread.mCamera,
"./{}/grab_{}.jpg".format(dirName, catchTime),
pFrameBuffer,
FrameHead, mvsdk.FILE_JPG, 100)
if os.path.exists("./{}/grab_{}.jpg".format(dirName, catchTime)):
# 进行目标检测
results = self.camera_thread.model.predict('./{}/grab_{}.jpg'.format(dirName, catchTime))
annotated_frame = results[0].plot()
# 保存处理后带标签的图片
cv2.imwrite("./{}/process_{}.jpg".format(dirName, catchTime), annotated_frame)
# 将图像数据转换为QImage格式
height, width, channel = annotated_frame.shape
bytes_per_line = 3 * width
qimage = QtGui.QImage(annotated_frame.data, width, height, bytes_per_line,
QtGui.QImage.Format_RGB888)
# 将QImage转换为QPixmap
pixmap = QtGui.QPixmap.fromImage(qimage)
self.label_show.setPixmap(pixmap)
self.label_show.setScaledContents(True)
# 提取检测结果
self.textBrowser.append(
"*********************************{}*************************************".format(
time.strftime("%Y-%m-%d %H:%M:%S")))
find_labels = []
for result in results:
boxes = result.boxes.xyxy # 边界框坐标
scores = result.boxes.conf # 置信度分数
classes = result.boxes.cls # 类别索引
# 如果有类别名称，可以通过类别索引获取
class_names = [self.camera_thread.model.names[int(cls)] for cls in classes]
# 打印检测结果
for box, score, class_name in zip(boxes, scores, class_names):
self.textBrowser.append(f"检测标签: {class_name}, 置信度: {score:.2f}")
if score >= self.yamlData['threshold']:
find_labels.append(class_name)
if len(find_labels) == 2 and 'pin-left-pass' in find_labels and 'pin-right-pass' in find_labels:
self.label_result.setText("PASS")
self.label_result.setStyleSheet("background-color: #55ff7f")
# TODO 给出PASS信号
else:
self.label_result.setText("FAIL")
self.label_result.setStyleSheet("background-color: #d80000")
# TODO 给出FAIL信号
self.textBrowser.append(
"*****************************************************************************************")
except mvsdk.CameraException as e:
QMessageBox.critical(self, "错误", "抓图失败({}): {}".format(e.error_code, e.message), QMessageBox.Yes,
QMessageBox.Yes)
def drawLine(self):
"""
添加网格线
:return:
"""
if self.pushButton_addline.text() == "添加网格线":
self.camera_thread.drawLine = True
self.pushButton_addline.setText("去除网格线")
else:
self.camera_thread.drawLine = False
self.pushButton_addline.setText("添加网格线")
def showVideo(self, showImage):
"""
显示视频
:param showImage:
:return:
"""
self.label_display.setPixmap(QtGui.QPixmap.fromImage(showImage))
def showStatus(self, info):
"""
显示状态
:param info:
:return:
"""
self.statusbar.showMessage(info)
def selectMode(self, mode):
"""
选择抓图模式
:param mode:
:return:
"""
if mode == 0:
self.yamlTool.update_yaml('config.yaml', 'runMode', 'mark')
else:
self.yamlTool.update_yaml('config.yaml', 'runMode', 'run')
self.yamlData = self.yamlTool.read_yaml('config.yaml')
def thresholdChange(self, value):
"""
置信阈值改变事件
:param value:
:return:
"""
self.yamlTool.update_yaml('config.yaml', 'threshold', value)
self.yamlData = self.yamlTool.read_yaml('config.yaml')
if __name__ == '__main__':
app = QtWidgets.QApplication(sys.argv)
main_window = MainWindow()
main_window.show()
sys.exit(app.exec_())
动态效果展示
yolov8视觉框架动态检测产品缺陷
![[OS] 编译 Linux 内核](https://i-blog.csdnimg.cn/direct/7f70489eb6774f9fa55ba5660b652c3e.png)
