安全帽检测python算法
时间: 2023-10-26 13:20:52 浏览: 44
安全帽检测是一种常见的计算机视觉应用。下面是一种基于Python的安全帽检测算法:
1. 导入必要的库
```python
import cv2
import numpy as np
```
2. 加载模型和数据
```python
model = cv2.dnn.readNetFromCaffe("deploy.prototxt", "res10_300x300_ssd_iter_140000.caffemodel")
```
3. 读取图像并进行预处理
```python
image = cv2.imread("image.jpg")
(h, w) = image.shape[:2]
blob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0))
```
4. 进行检测并绘制边界框
```python
model.setInput(blob)
detections = model.forward()
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
label = "Helmet" if detections[0, 0, i, 1] == 0 else "No Helmet"
color = (0, 255, 0) if label == "Helmet" else (0, 0, 255)
cv2.rectangle(image, (startX, startY), (endX, endY), color, 2)
cv2.putText(image, label, (startX, startY - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
```
5. 显示结果
```python
cv2.imshow("Output", image)
cv2.waitKey(0)
```
这是一个简单的安全帽检测算法,可以根据实际情况进行调整和优化。