yolov5只显示标签

YoloV5 是一种目标检测模型，它可以在图像或视频中识别和定位不同的物体。如果你只看到了标签而没有看到物体框，这可能是因为你的代码中没有将物体框绘制出来。可以在代码中添加绘制物体框的功能，以便更清楚地展示检测结果。下面是一个绘制物体框的示例代码：

import cv2
import torch
from models.experimental import attempt_load
from utils.general import non_max_suppression


def detect(model, img, conf_thres=0.5, iou_thres=0.5, device='cpu'):
    # Convert image to Tensor
    img = torch.from_numpy(img).to(device)
    img = img.float()
    img /= 255.0
    if img.ndimension() == 3:
        img = img.unsqueeze(0)

    # Inference
    model.eval()
    with torch.no_grad():
        pred = model(img)

    # Apply NMS
    pred = non_max_suppression(pred, conf_thres, iou_thres)

    # Draw bounding boxes
    for det in pred[0]:
        x1, y1, x2, y2, conf, cls = det.tolist()
        x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
        label = f'{classes[int(cls)]} {conf:.2f}'
        cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)
        cv2.putText(img, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)

    return img


if __name__ == '__main__':
    # Load model
    weights = 'yolov5s.pt'
    model = attempt_load(weights, map_location=torch.device('cpu'))

    # Load image
    img = cv2.imread('image.jpg')

    # Detect objects
    result = detect(model, img)

    # Show result
    cv2.imshow('result', result)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

在上面的代码中，我们将物体框和标签绘制在了图片上。如果你想只显示标签，可以将 `cv2.rectangle()` 函数和 `cv2.putText()` 函数中的绘制物体框的代码注释掉即可。