yolo截取卡车图片

yolo截取卡车图片

truck_crop = img[y1:y2, x1:x2] # 裁剪卡车区域
crop_output_path = f'path/to/your/truck_crop_{x1}_{y1}.jpg' # 生成一个唯一的文件名
cv2.imwrite(crop_output_path, truck_crop)
print(f"Cropped truck image saved to: {crop_output_path}")

from ultralytics import YOLO
import cv2
# 加载模型并进行推理
results = YOLO('yolo12n.pt')('1.jpg')

# 查找所有卡车并获取置信度最高的
trucks = [box for result in results for box in result.boxes 
          if result.names[int(box.cls)] == 'truck']

if trucks:
    best_truck = max(trucks, key=lambda box: box.conf.item())
    conf = best_truck.conf.item()
    x1, y1, x2, y2 = map(int, best_truck.xyxy[0].tolist())
    img = cv2.imread('1.jpg')
    truck_crop = img[y1:y2, x1:x2]  # 裁剪卡车区域
	crop_output_path = f'1_{x1}_{y1}.jpg'  # 生成一个唯一的文件名
	cv2.imwrite(crop_output_path, truck_crop)
    
    print(f"最高置信度卡车: {conf:.2%}")
    print(f"位置: ({x1}, {y1}) 到 ({x2}, {y2})")
else:
    print("未检测到卡车")