使用ESP32-CAM和OpenCV实现图片获取

我觉得这是一种廉价并且较为可靠的图像获取方案，目前无法输出视频流，因为我还不知道怎么提升传输速度…
进入正题-- ESP32-CAM模组在某宝上面差不多25块一个（不是M5STACK）我的图像传输方案是先在esp32上面获取图像的16进制字符串，再publish到MQTT服务器上面，接着电脑的客户端把这个hexchar下载下来以后转成2进制，用opencv decode成图像再打开。
ESP32用Arduino IDE编程，电脑上面是用python写的一个小程序来读图像的。
python需要安装opencv。安装方法是在电脑的命令行，或者bash，或者ps里面输入pip install opencv-contrib-python 来安装，推荐把python的pip源换成清华的国内源，这样下载速度会比较快。

#include 
#include 
#include 
#include 
#include "PubSubClient.h"
#include "CamConfig.h"

WiFiClient Wclient;
PubSubClient client(Wclient);
const char *hostA = "esp32";
const char *ssid = "***********";
const char *password = "***********";
const char *mqtt_server = "************";
boolean shotflag = false;
boolean WiFiDisconnect = false;
String msg;
int timeCount = 0;
void callback(char *topic, byte *message, unsigned int length);
void getimg();
void reconnect();
void setupCamera();
void WiFiEvent(WiFiEvent_t event);
void setup()
{
    Serial.begin(115200);
    WiFi.begin(ssid, password);
    while (WiFi.status() != WL_CONNECTED)
    {
    }
    Serial.println("WiFi connected");
    Serial.println(WiFi.localIP());
    WiFi.onEvent(WiFiEvent);
    client.setServer(mqtt_server, 1883);
    client.setCallback(callback);
    setupCamera();
    Serial.println("Ready");
}

void loop()
{
    reconnect();
    client.loop();
    if (shotflag == true)
    {
        getimg();
        shotflag = false;
    }
}

void getimg()
{

    camera_fb_t *fb = esp_camera_fb_get();
    // int tranCount = (fb->len * 2 + (1000 - 1)) / 1000;
    if (fb)
    {
        Serial.printf("width: %d, height: %d, buf: 0x%x, len: %d\n", fb->width, fb->height, fb->buf, fb->len);
        char data[4104];
        for (int i = 0; i < fb->len; i++)
        {
            sprintf(data, "%02X", *((fb->buf + i)));
            msg += data;
            if (msg.length() == 4096)
            {
                timeCount += 1;
                client.beginPublish("img", msg.length(), 0);
                client.print(msg);
                client.endPublish();
                msg = "";
                // Serial.println(timeCount);
            }
        }
        if (msg.length() > 0)
        {
            client.beginPublish("img", msg.length(), 0);
            client.print(msg);
            client.endPublish();
            msg = "";
        }
        client.publish("img", "1");
        timeCount = 0;
        esp_camera_fb_return(fb);
    }
}

void callback(char *topic, byte *payload, unsigned int length)
{
    // Serial.print("Message arrived [");
    // Serial.print(topic); // 打印主题信息
    // Serial.print("] ");
    // for (int i = 0; i < length; i++)
    // {
    //     Serial.print((char)payload[i]); // 打印主题内容
    // }
    // Serial.println();
    if ((char)payload[0] == '1')
    {
        shotflag = true;
    }
    if ((char)payload[0] == '0')
    {
        shotflag = false;
    }
}
void reconnect()
{
    if (WiFiDisconnect)
    {
        WiFi.reconnect();
    }
    while (!client.connected())
    {
        client.connect("EspClient");
        client.subscribe("CAMcontrol");
    }
}

void setupCamera()
{
    const camera_config_t config = {
        .pin_pwdn = PWDN_GPIO_NUM,
        .pin_reset = RESET_GPIO_NUM,
        .pin_xclk = XCLK_GPIO_NUM,
        .pin_sscb_sda = SIOD_GPIO_NUM,
        .pin_sscb_scl = SIOC_GPIO_NUM,
        .pin_d7 = Y9_GPIO_NUM,
        .pin_d6 = Y8_GPIO_NUM,
        .pin_d5 = Y7_GPIO_NUM,
        .pin_d4 = Y6_GPIO_NUM,
        .pin_d3 = Y5_GPIO_NUM,
        .pin_d2 = Y4_GPIO_NUM,
        .pin_d1 = Y3_GPIO_NUM,
        .pin_d0 = Y2_GPIO_NUM,
        .pin_vsync = VSYNC_GPIO_NUM,
        .pin_href = HREF_GPIO_NUM,
        .pin_pclk = PCLK_GPIO_NUM,
        .xclk_freq_hz = 20000000,
        .ledc_timer = LEDC_TIMER_0,
        .ledc_channel = LEDC_CHANNEL_0,
        .pixel_format = PIXFORMAT_JPEG,
        .frame_size = FRAMESIZE_SVGA,
        .jpeg_quality = 10,
        .fb_count = 2,
    };

    esp_err_t err = esp_camera_init(&config);
    Serial.printf("esp_camera_init: 0x%x\n", err);

    sensor_t *s = esp_camera_sensor_get();
    s->set_framesize(s, FRAMESIZE_XGA);
}

void WiFiEvent(WiFiEvent_t event)
{
    switch (event)
    {
    case SYSTEM_EVENT_STA_DISCONNECTED:
        WiFiDisconnect = true;
    case SYSTEM_EVENT_STA_CONNECTED:
        WiFiDisconnect = false;
    }
}

这是ESP32部分的程序，我把相机设定的那一部分放到独立的头文件那里了，都是引脚的宏定义，如果你也用的是ESP32-CAM的话可以在Arduino IDE的示例代码里面找到，在这之前只需要导入一下ESP32的开发板包，因为Arduino IDE本身是不带ESP32这个开发板型号的。

void getimg()
{

    camera_fb_t *fb = esp_camera_fb_get();
    // int tranCount = (fb->len * 2 + (1000 - 1)) / 1000;
    if (fb)
    {
        Serial.printf("width: %d, height: %d, buf: 0x%x, len: %d\n", fb->width, fb->height, fb->buf, fb->len);
        char data[4104];
        for (int i = 0; i < fb->len; i++)
        {
            sprintf(data, "%02X", *((fb->buf + i)));
            msg += data;
            if (msg.length() == 4096)
            {
                timeCount += 1;
                client.beginPublish("img", msg.length(), 0);
                client.print(msg);
                client.endPublish();
                msg = "";
                // Serial.println(timeCount);
            }
        }
        if (msg.length() > 0)
        {
            client.beginPublish("img", msg.length(), 0);
            client.print(msg);
            client.endPublish();
            msg = "";
        }
        client.publish("img", "1");
        timeCount = 0;
        esp_camera_fb_return(fb);
    }
}

getimg子程序是发送图片信息的部分，这个图片必须分段发送，要不然32会崩溃，同时这个 data[4104];数组已经差不多是esp32内存的极限了，再大就有可能爆stack。这个分段发送我想了好久，也查了不少资料，所以能发送成功我也是挺开心的。
下面就是python的接收部分。要成功接收到消息，首先我们需要建立一个MQTT服务器，我这里用的是mosquitto，因为这个比较方便，不同的服务端程序是对客户端没有影响的。

import paho.mqtt.client as mqtt
import threading
import time
import cv2.cv2 as cv2
import numpy as np
import binascii

mqttclient = mqtt.Client()
HOST = "*******"
PORT = 1883


class GlobalValue:
    data = [""]


def on_client_connect(client, userdata, flags, rc):
    if rc == 0:
        print('connected!!!')
    elif rc == 3:
        print("Server can't be used")
    else:
        print('Other errors')


def connect():
    mqttclient.connect(HOST, PORT, 60)


def publish(topic, payload, qos):
    mqttclient.publish(topic, payload, qos)


def on_rec(client, userdata, message):
    if message.topic == "img":
        # print(str(message.payload.decode()))
        GlobalValue.data.append(str(message.payload.decode()))


def subscribe(topic, qos):
    mqttclient.subscribe(topic, qos)


def main():
    mqttclient.on_message = on_rec
    mqttclient.on_connect = on_client_connect
    connect()
    subscribe('img', 0)
    subscribe('control', 0)
    publish('control', "1", 0)
    imgcount = 0
    # data2 = ""
    while True:
        mqttclient.loop_start()
        if (GlobalValue.data[len(GlobalValue.data) - 1]) == "1":
            # print("Reached EOF")
            data1 = "".join(GlobalValue.data[0:(len(GlobalValue.data) - 1)])
            GlobalValue.data = [""]
            data1 = binascii.a2b_hex(data1)
            # label = "img/image" + str(imgcount) + ".jpg"
            # with open(label, "wb") as image_file:
            #     image_file.write(data1)
            data1 = np.frombuffer(data1, dtype=np.uint8)
            img = cv2.imdecode(data1, 1)
            cv2.imshow("Door", img)
            cv2.waitKey(1)
            # if imgcount >= 40:
            #     exit(0)
            # else:
            imgcount += 1
            publish('CAMcontrol', "1", 0)


if __name__ == '__main__':
    main()

这里比较有趣的是几个回调函数，和一个全局的数组。Python写起程序来是挺舒服的，至少对于我这个初学者而言，但是在我看来也有两个比较难以处理的问题–第一个是全局变量的问题，这个作用域有时候让人摸不清楚头脑，对于定义全局变量，我的解决方式是在开头定义一个class，把全局变量写到class里面，个人觉得是方便多了，而且比较好管理。

class GlobalValue:
    data = [""]
#比如说这样

第二个问题是python的解释方式，他是从上到下解释的，就让我一开始非常难写回调函数，特别容易出现unresolved referance 这个问题只能自己注意，知错就改了。
开头的这个import cv2.cv2 as cv2写成这样是因为普通的import方法pylint没办法显示代码提示，好像是因为opencv的包结构的问题，多了一个cv2文件夹，导致pylint找不到。
就先写到这里吧，之后的任务还有物体识别和追踪，deadline是下周一。