下面是一个使用Pyside6编写YOLOv8模型进行目标检测、样本采集和保存的示例代码:
import sys
import cv2
from PySide6.QtCore import Qt
from PySide6.QtGui import QImage, QPixmap
from PySide6.QtWidgets import QApplication, QMainWindow, QLabel, QPushButton
class MainWindow(QMainWindow):
def __init__(self):
super().__init__()
self.setWindowTitle("YOLOv8 Sample Collection")
self.setFixedSize(800, 600)
self.image_label = QLabel(self)
self.image_label.setAlignment(Qt.AlignCenter)
self.image_label.setFixedSize(640, 480)
self.capture_button = QPushButton("Capture", self)
self.capture_button.setGeometry(350, 520, 100, 40)
self.capture_button.clicked.connect(self.capture_sample)
def capture_sample(self):
image = self.image_label.pixmap().toImage()
# 将QImage转换为OpenCV图像
cv_image = cv2.cvtColor(np.array(image), cv2.COLOR_RGBA2BGR)
# 使用YOLOv8模型预测目标检测结果
detections = yolo_inference(cv_image) # 替换为你的YOLOv8模型推理函数
# 在图像上绘制边界框和类别信息,并保存样本图像及相关信息
for detection in detections:
class_name = detection['class_name']
confidence = detection['confidence']
bbox = detection['bbox'] # (x, y, width, height)
# 绘制边界框和类别信息
x, y, w, h = bbox
cv2.rectangle(cv_image, (x, y), (x+w, y+h), (255, 0, 0), 2)
cv2.putText(cv_image, f"{class_name}: {confidence:.2f}", (x, y-10),
cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0 ,0), 2)
# 保存样本图像及相关信息(这里仅作示例,可以根据需要自定义保存格式)
sample_file = f"{class_name}_{confidence:.2f}.jpg"
annotation_file = "annotation.txt"
cv2.imwrite(sample_file, cv_image)
with open(annotation_file, "a") as f:
line = f"{sample_file} {class_name} {x} {y} {w} {h}\n"
f.write(line)
# 显示带有标注的图像在界面上
q_image_with_annotation = QImage(cv_image.data,
cv_image.shape[1],
cv_image.shape[0],
QImage.Format_RGB888)
self.image_label.setPixmap(QPixmap.fromImage(q_image_with_annotation))
if __name__ == "__main__":
app = QApplication(sys.argv)
window = MainWindow()
window.show()
sys.exit(app.exec())
请注意,以上代码仅为示例,你需要替换yolo_inference
函数为你实际使用的YOLOv8模型推理函数,并根据需要进行相应的修改。同时,请确保YOLOv8模型和权重文件已正确加载,并能够返回目标检测结果。
此示例代码创建了一个窗口,在窗口中显示采集到的图像并提供一个按钮用于触发样本采集。在采集过程中,使用YOLOv8模型进行目标检测,并绘制边界框和类别信息。同时,将样本图像及相关信息保存到文件中。
希望对你有所帮助!
内容由零声教学AI助手提供,问题来源于学员提问