30 lines
755 B
Python
30 lines
755 B
Python
|
from ultralytics import YOLO
|
||
|
|
import os
|
||
|
|
|
||
|
|
|
||
|
|
def main():
|
||
|
|
# 加载训练后的模型
|
||
|
|
model = YOLO("runs/detect/final_model3/weights/best.pt")
|
||
|
|
|
||
|
|
# 在验证集上评估模型性能（添加 workers=0 参数）
|
||
|
|
results2 = model.val(data="data.yaml", workers=0)
|
||
|
|
|
||
|
|
# 推理指定图像或目录（添加 workers=0 参数）
|
||
|
|
results = model.predict(
|
||
|
|
source="datasets/train/images/1_jpeg.rf.7bb68b0df8cd88542b4d9cd83a9a0457.jpg",
|
||
|
|
imgsz=640,
|
||
|
|
conf=0.25,
|
||
|
|
save=True,
|
||
|
|
#device=0,
|
||
|
|
workers=0 # 关键参数
|
||
|
|
)
|
||
|
|
|
||
|
|
# 遍历并打印预测结果
|
||
|
|
for result in results:
|
||
|
|
print(result.names)
|
||
|
|
print(result.boxes)
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == '__main__':
|
||
|
|
main() # Windows必须的入口保护
|