Streaming FireBeetle ESP32 Camera Video to Home Assistance

Auteur avatarCETECH11 | Dernière modification 19/03/2024 par CETECH11

Will guide you to stream ESP32 Cam footage to Home Assistant.

Introduction

Streaming ESP32-CAM Video to Home Assistant

The ESP32-CAM is a versatile and affordable camera module that can be used for various projects. In this tutorial, we’ll explore how to set up video streaming from the ESP32-CAM to Home Assistant, allowing you to monitor your surroundings remotely.

Matériaux

Outils

Étape 1 - Setting Up Video Streaming Web Server

Open the Arduino IDE and navigate to the ESP32 examples.

1. Select File->Examples->ESP32->Camera->CameraWebServer example in Arduino IDE.

2. Replace the codes in CameraWebServer with the code below (Note: please fill in your WiFi account and password)
#include "esp_camera.h"
#include <WiFi.h>

//
// WARNING!!! PSRAM IC required for UXGA resolution and high JPEG quality
//            Ensure ESP32 Wrover Module or other board with PSRAM is selected
//            Partial images will be transmitted if image exceeds buffer size
//
//            You must select partition scheme from the board menu that has at least 3MB APP space.
//            Face Recognition is DISABLED for ESP32 and ESP32-S2, because it takes up from 15 
//            seconds to process single frame. Face Detection is ENABLED if PSRAM is enabled as well

// ===================
// Select camera model
// ===================
#define PWDN_GPIO_NUM     -1
#define RESET_GPIO_NUM    -1
#define XCLK_GPIO_NUM     45
#define SIOD_GPIO_NUM     1
#define SIOC_GPIO_NUM     2

#define Y9_GPIO_NUM       48
#define Y8_GPIO_NUM       46
#define Y7_GPIO_NUM       8
#define Y6_GPIO_NUM       7
#define Y5_GPIO_NUM       4
#define Y4_GPIO_NUM       41
#define Y3_GPIO_NUM       40
#define Y2_GPIO_NUM       39
#define VSYNC_GPIO_NUM    6
#define HREF_GPIO_NUM     42
#define PCLK_GPIO_NUM     5

#include "DFRobot_AXP313A.h"

DFRobot_AXP313A axp;

// ===========================
// Enter your WiFi credentials
// ===========================
const char* ssid = "*****";
const char* password = "******";

void startCameraServer();

void setup() {
  Serial.begin(115200);
  Serial.setDebugOutput(true);
  Serial.println();
  while(axp.begin() != 0){
    Serial.println("init error");
    delay(1000);
  }
  axp.enableCameraPower(axp.eOV2640);//Enable the power for camera
  camera_config_t config;
  config.ledc_channel = LEDC_CHANNEL_0;
  config.ledc_timer = LEDC_TIMER_0;
  config.pin_d0 = Y2_GPIO_NUM;
  config.pin_d1 = Y3_GPIO_NUM;
  config.pin_d2 = Y4_GPIO_NUM;
  config.pin_d3 = Y5_GPIO_NUM;
  config.pin_d4 = Y6_GPIO_NUM;
  config.pin_d5 = Y7_GPIO_NUM;
  config.pin_d6 = Y8_GPIO_NUM;
  config.pin_d7 = Y9_GPIO_NUM;
  config.pin_xclk = XCLK_GPIO_NUM;
  config.pin_pclk = PCLK_GPIO_NUM;
  config.pin_vsync = VSYNC_GPIO_NUM;
  config.pin_href = HREF_GPIO_NUM;
  config.pin_sscb_sda = SIOD_GPIO_NUM;
  config.pin_sscb_scl = SIOC_GPIO_NUM;
  config.pin_pwdn = PWDN_GPIO_NUM;
  config.pin_reset = RESET_GPIO_NUM;
  config.xclk_freq_hz = 20000000;
  config.frame_size = FRAMESIZE_UXGA;
  config.pixel_format = PIXFORMAT_JPEG; // for streaming
  //config.pixel_format = PIXFORMAT_RGB565; // for face detection/recognition
  config.grab_mode = CAMERA_GRAB_WHEN_EMPTY;
  config.fb_location = CAMERA_FB_IN_PSRAM;
  config.jpeg_quality = 12;
  config.fb_count = 1;

  // if PSRAM IC present, init with UXGA resolution and higher JPEG quality
  //                      for larger pre-allocated frame buffer.
  if(config.pixel_format == PIXFORMAT_JPEG){
    if(psramFound()){
      config.jpeg_quality = 10;
      config.fb_count = 2;
      config.grab_mode = CAMERA_GRAB_LATEST;
    } else {
      // Limit the frame size when PSRAM is not available
      config.frame_size = FRAMESIZE_SVGA;
      config.fb_location = CAMERA_FB_IN_DRAM;
    }
  } else {
    // Best option for face detection/recognition
    config.frame_size = FRAMESIZE_240X240;
#if CONFIG_IDF_TARGET_ESP32S3
    config.fb_count = 2;
#endif
  }

#if defined(CAMERA_MODEL_ESP_EYE)
  pinMode(13, INPUT_PULLUP);
  pinMode(14, INPUT_PULLUP);
#endif

  // camera init
  esp_err_t err = esp_camera_init(&config);
  if (err != ESP_OK) {
    Serial.printf("Camera init failed with error 0x%x", err);
    return;
  }

  sensor_t * s = esp_camera_sensor_get();
  // initial sensors are flipped vertically and colors are a bit saturated
  if (s->id.PID == OV3660_PID) {
    s->set_vflip(s, 1); // flip it back
    s->set_brightness(s, 1); // up the brightness just a bit
    s->set_saturation(s, -2); // lower the saturation
  }
  // drop down frame size for higher initial frame rate
  if(config.pixel_format == PIXFORMAT_JPEG){
    s->set_framesize(s, FRAMESIZE_QVGA);
  }

#if defined(CAMERA_MODEL_M5STACK_WIDE) || defined(CAMERA_MODEL_M5STACK_ESP32CAM)
  s->set_vflip(s, 1);
  s->set_hmirror(s, 1);
#endif

#if defined(CAMERA_MODEL_ESP32S3_EYE)
  s->set_vflip(s, 1);
#endif

  WiFi.begin(ssid, password);
  WiFi.setSleep(false);

  while (WiFi.status() != WL_CONNECTED) {
    delay(500);
    Serial.print(".");
  }
  Serial.println("");
  Serial.println("WiFi connected");

  startCameraServer();

  Serial.print("Camera Ready! Use 'http://");
  Serial.print(WiFi.localIP());
  Serial.println("' to connect");
}

void loop() {
  // Do nothing. Everything is done in another task by the web server
  delay(10000);
}
Then upload the code to the FireBeetle ESP32 S3 board and look for the serial terminal response.



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Étape 3 - Setting Up Video Stream Properties

Next, open up the IP address that shows in the serial terminal and look for the camera web server properties.

Set up the resolution. Go with the lower one to get a high FPS.

Finally, add the:81/stream in the camera IP address.

Now it will directly show you the camera feed.


Étape 4 - Integrating with Home Assistant

  • Open Home Assistant.
  • Next, navigate to the overview and add a picture card.
  • Enter the IP address of your ESP32-CAM following:81/stream and click Finish.
  • And that’s it! You’ve successfully set up video streaming from the ESP32-CAM to Home Assistant.

Feel free to customize and enhance this project further. Happy monitoring! 📷🏠



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