基于树莓派csi摄像头实时仓库谷物计数和仓库温湿度和烟雾检测系统的代码
时间: 2023-06-18 18:05:36 浏览: 141
这个项目涉及到多个模块,需要分别进行开发。以下是基本的代码结构和思路:
1. 树莓派连接CSI摄像头:
```python
import cv2
# 初始化摄像头
cap = cv2.VideoCapture(0)
# 设置分辨率
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
while True:
# 读取摄像头画面
ret, frame = cap.read()
if not ret:
break
# 显示画面
cv2.imshow("CSI Camera", frame)
# 按下q键退出
if cv2.waitKey(1) == ord('q'):
break
# 释放摄像头资源
cap.release()
cv2.destroyAllWindows()
```
2. 图像处理和物体计数:
```python
import cv2
# 初始化摄像头
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# 初始化背景
bg_subtractor = cv2.createBackgroundSubtractorMOG2()
# 初始化计数器
count = 0
while True:
ret, frame = cap.read()
if not ret:
break
# 背景差分
fg_mask = bg_subtractor.apply(frame)
# 二值化
_, binary = cv2.threshold(fg_mask, 40, 255, cv2.THRESH_BINARY)
# 轮廓检测
contours, _ = cv2.findContours(binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# 绘制轮廓
for contour in contours:
x, y, w, h = cv2.boundingRect(contour)
if w > 30 and h > 30:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255), 2)
count += 1
# 显示画面和计数
cv2.putText(frame, "Count: {}".format(count), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
cv2.imshow("CSI Camera", frame)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
```
3. 温湿度检测:
```python
import Adafruit_DHT
# 温湿度传感器型号和引脚
sensor = Adafruit_DHT.DHT11
pin = 4
while True:
# 读取温湿度
humidity, temperature = Adafruit_DHT.read_retry(sensor, pin)
if humidity is not None and temperature is not None:
print('Temperature: {:.1f} C\tHumidity: {:.1f} %'.format(temperature, humidity))
else:
print('Failed to read temperature and humidity!')
# 等待1秒
time.sleep(1)
```
4. 烟雾检测:
```python
import RPi.GPIO as GPIO
import time
# 烟雾传感器引脚
detection_pin = 17
# 初始化GPIO
GPIO.setmode(GPIO.BCM)
GPIO.setup(detection_pin, GPIO.IN)
while True:
# 读取烟雾状态
smoke_detected = GPIO.input(detection_pin)
if smoke_detected:
print('Smoke detected!')
else:
print('No smoke detected.')
# 等待1秒
time.sleep(1)
```
以上是基本的代码结构和思路,具体的实现需要根据硬件和传感器的具体情况进行调整和优化。
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