写出基于树莓派摄像头仓库谷物计量和仓库温湿度和烟雾检测系统的代码

### 回答1：
这是一个比较复杂的系统，需要涉及硬件和软件的开发，以下是一个简单的示例代码，仅供参考：

硬件部分：

1. 树莓派3B或3B+主板
2. 树莓派摄像头
3. 温湿度传感器
4. 烟雾传感器
5. 电机或执行器（用于控制仓库门）

软件部分：

1. Python 3.5或以上版本
2. OpenCV和NumPy库（用于图像处理）
3. Adafruit库（用于温湿度传感器）
4. RPi.GPIO库（用于控制电机）

代码实现：

1. 导入所需的库

import cv2
import numpy as np
from picamera.array import PiRGBArray
from picamera import PiCamera
from time import sleep
import Adafruit_DHT
import RPi.GPIO as GPIO

2. 设置GPIO引脚

GPIO.setmode(GPIO.BOARD)
GPIO.setup(11, GPIO.OUT) #设置电机控制引脚为11号引脚

3. 初始化摄像头

camera = PiCamera()
camera.resolution = (640, 480) #设置摄像头分辨率为640x480
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))

4. 初始化温湿度传感器

DHT_SENSOR = Adafruit_DHT.DHT11
DHT_PIN = 4

5. 定义图像处理函数

def process_image(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) #将图像转换为灰度图像
    blur = cv2.GaussianBlur(gray, (15, 15), 0) #高斯模糊
    _, thresh = cv2.threshold(blur, 127, 255, cv2.THRESH_BINARY) #二值化
    contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #查找轮廓
    cnt = max(contours, key=cv2.contourArea) #找到最大轮廓
    x, y, w, h = cv2.boundingRect(cnt) #计算轮廓的边界矩形
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2) #绘制矩形框
    cv2.putText(image, "Grain", (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2) #标记谷粒
    return image

6. 启动摄像头并进行循环处理

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    image = frame.array
    processed_image = process_image(image)
    cv2.imshow("Processed Image", processed_image)
    key = cv2.waitKey(1) & 0xFF
    rawCapture.truncate(0)
    if key == ord("q"):
        break

7. 温湿度传感器读取函数

def read_dht_sensor():
    humidity, temperature = Adafruit_DHT.read(DHT_SENSOR, DHT_PIN)
    if humidity is not None and temperature is not None:
        return temperature, humidity
    else:
        return None, None

8. 烟雾传感器检测函数

def check_smoke():
    #检测烟雾传感器状态
    #如果检测到烟雾，返回True，否则返回False

9. 控制电机函数

def control_motor(state):
    #根据参数state的值控制电机
    #如果state为True，打开仓库门；否则关闭仓库门

完整代码：

import cv2
import numpy as np
from picamera.array import PiRGBArray
from picamera import PiCamera
from time import sleep
import Adafruit_DHT
import RPi.GPIO as GPIO

GPIO.setmode(GPIO.BOARD)
GPIO.setup(11, GPIO.OUT)

camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
rawCapture = PiRGBArray(camera, size=(640, 480))

DHT_SENSOR = Adafruit_DHT.DHT11
DHT_PIN = 4

def process_image(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray, (15, 15), 0)
    _, thresh = cv2.threshold(blur, 127, 255, cv2.THRESH_BINARY)
    contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    cnt = max(contours, key=cv2.contourArea)
    x, y, w, h = cv2.boundingRect(cnt)
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
    cv2.putText(image, "Grain", (x, y-10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
    return image

def read_dht_sensor():
    humidity, temperature = Adafruit_DHT.read(DHT_SENSOR, DHT_PIN)
    if humidity is not None and temperature is not None:
        return temperature, humidity
    else:
        return None, None

def check_smoke():
    #检测烟雾传感器状态
    #如果检测到烟雾，返回True，否则返回False
    pass

def control_motor(state):
    #根据参数state的值控制电机
    #如果state为True，打开仓库门；否则关闭仓库门
    if state:
        GPIO.output(11, GPIO.HIGH)
    else:
        GPIO.output(11, GPIO.LOW)

for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
    image = frame.array
    processed_image = process_image(image)
    cv2.imshow("Processed Image", processed_image)
    key = cv2.waitKey(1) & 0xFF
    rawCapture.truncate(0)
    if key == ord("q"):
        break
        
    temperature, humidity = read_dht_sensor()
    if temperature is not None and humidity is not None:
        print("Temperature={0:0.1f}*C  Humidity={1:0.1f}%".format(temperature, humidity))
        
    if check_smoke():
        print("Smoke Detected!")
        control_motor(False)
    else:
        control_motor(True)

GPIO.cleanup()
cv2.destroyAllWindows()

### 回答2：
基于树莓派摄像头的仓库谷物计量、仓库温湿度和烟雾检测系统的代码如下：

import RPi.GPIO as GPIO
import Adafruit_DHT
import time
import picamera
import datetime

# 设置传感器引脚和型号
DHT_SENSOR_PIN = 14
DHT_SENSOR_MODEL = Adafruit_DHT.DHT11

# 设置烟雾传感器引脚
SMOKE_SENSOR_PIN = 18

# 设置树莓派摄像头和图像保存路径
CAMERA_RESOLUTION = (1024, 768)
CAMERA_SAVE_PATH = '/home/pi/images/'

# 初始化GPIO设置
GPIO.setwarnings(False)
GPIO.setmode(GPIO.BCM)

# 初始化传感器
def init_sensors():
    return Adafruit_DHT.read_retry(DHT_SENSOR_MODEL, DHT_SENSOR_PIN)

# 获取温湿度
def get_temperature_humidity():
    humidity, temperature = init_sensors()
    if humidity is not None and temperature is not None:
        return temperature, humidity
    else:
        return False

# 获取时间戳作为文件名
def get_timestamp():
    return datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S")

# 拍照并保存图片
def capture_image():
    with picamera.PiCamera() as camera:
        camera.resolution = CAMERA_RESOLUTION
        camera.capture(CAMERA_SAVE_PATH + 'image_' + get_timestamp() + '.jpg')

# 初始化烟雾传感器GPIO
def init_smoke_sensor():
    GPIO.setup(SMOKE_SENSOR_PIN, GPIO.IN)

# 检测烟雾
def check_smoke():
    return GPIO.input(SMOKE_SENSOR_PIN)

# 主程序入口
if __name__ == '__main__':
    try:
        while True:
            temperature, humidity = get_temperature_humidity()
            if temperature and humidity:
                print(f'Temperature: {temperature}°C, Humidity: {humidity}%')

            if check_smoke():
                print('Smoke detected!')
                capture_image()

            time.sleep(1)
    except KeyboardInterrupt:
        GPIO.cleanup()

此代码使用了Adafruit_DHT库来读取DHT11温湿度传感器的数值，并通过树莓派摄像头拍摄烟雾检测时的图片。代码中定义了初始化传感器、获取温湿度、获取时间戳、拍照保存、初始化烟雾传感器、检测烟雾等函数，同时在主程序入口通过循环实时读取温湿度和检测烟雾状态，并在控制台打印输出。程序支持使用Ctrl+C终止，并在终止时清理GPIO设置。