YOLOv4口罩佩戴识别代码
时间: 2023-09-07 17:18:02 浏览: 35
以下是使用YOLOv4实现口罩佩戴识别的代码示例:
```python
import cv2
import numpy as np
# 加载模型和标签
net = cv2.dnn.readNet("yolov4-tiny-mask.weights", "yolov4-tiny-mask.cfg")
classes = []
with open("mask.names", "r") as f:
classes = [line.strip() for line in f.readlines()]
# 读取测试图片
img = cv2.imread("test.jpg")
# 图片预处理
blob = cv2.dnn.blobFromImage(img, 1/255.0, (416, 416), swapRB=True, crop=False)
# 输入模型进行推理
net.setInput(blob)
outs = net.forward(net.getUnconnectedOutLayersNames())
# 处理输出结果
class_ids = []
confidences = []
boxes = []
for out in outs:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
center_x = int(detection[0] * img.shape[1])
center_y = int(detection[1] * img.shape[0])
w = int(detection[2] * img.shape[1])
h = int(detection[3] * img.shape[0])
x = int(center_x - w / 2)
y = int(center_y - h / 2)
boxes.append([x, y, w, h])
confidences.append(float(confidence))
class_ids.append(class_id)
# 非极大抑制
indices = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
# 绘制结果
for i in indices:
i = i[0]
box = boxes[i]
x, y, w, h = box
label = f"{classes[class_ids[i]]}: {confidences[i]:.2f}"
color = (0, 255, 0) if class_ids[i] == 0 else (0, 0, 255)
cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
cv2.putText(img, label, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
# 显示结果
cv2.imshow("Image", img)
cv2.waitKey(0)
```
需要注意的是,代码中的模型文件、配置文件和标签文件需要自行下载或生成。模型文件和配置文件可以在YOLO官网上下载,标签文件应该包含两个类别:mask和no_mask。