帮我用yolv5算法写一个交通标志识别程序,用python语言
时间: 2024-05-15 11:19:24 浏览: 7
好的,以下是一个简单的交通标志识别程序,使用yolov5算法和Python语言:
1. 安装yolov5库
首先需要安装yolov5库,可以使用以下命令:
```
pip install yolov5
```
2. 下载预训练模型
在yolov5官方网站下载预训练模型,例如yolov5s.pt。
3. 导入必要的库
```
import torch
import cv2
from PIL import Image
from yolov5 import detect
```
4. 加载预训练模型
```
model = torch.hub.load('ultralytics/yolov5', 'custom', path_or_model='yolov5s.pt')
```
5. 加载交通标志图片
```
img_path = 'traffic_sign.jpg'
img = cv2.imread(img_path)
```
6. 进行交通标志识别
```
results = detect.detect_image(model, img)
```
7. 输出识别结果
```
for result in results.xyxy[0]:
label = result[-1]
confidence = result[-2]
print('Label: {}, Confidence: {}'.format(label, confidence))
```
完整代码如下:
```
import torch
import cv2
from PIL import Image
from yolov5 import detect
# Load model
model = torch.hub.load('ultralytics/yolov5', 'custom', path_or_model='yolov5s.pt')
# Load image
img_path = 'traffic_sign.jpg'
img = cv2.imread(img_path)
# Detect traffic signs
results = detect.detect_image(model, img)
# Print results
for result in results.xyxy[0]:
label = result[-1]
confidence = result[-2]
print('Label: {}, Confidence: {}'.format(label, confidence))
```