Difficulty Level: Intermediate
In this tutorial, you will learn how to set up the ESP32-CAM module to perform object detection using OpenCV. This project combines the power of the ESP32 microcontroller with the image processing capabilities of OpenCV.
1. Connect the ESP32-CAM to your FTDI programmer:
2. Open the Arduino IDE and install the necessary board libraries for ESP32.
3. Load the following example code to set up the camera:
#include "esp_camera.h" void setup() { Serial.begin(115200); camera_config_t config; config.ledc_channel = LEDC_CHANNEL; config.ledc_freq = 5000; config.ledc_timer = LEDC_TIMER; config.pin_d0 = 0; // Adjust as necessary for your board config.pin_d1 = 26; // Adjust as necessary config.pin_d2 = 27; // Adjust as necessary config.pin_d3 = 25; // Adjust as necessary config.pin_d4 = 33; // Adjust as necessary config.pin_d5 = 32; // Adjust as necessary config.pin_d6 = 35; // Adjust as necessary config.pin_d7 = 34; // Adjust as necessary config.pin_xclk = 0; // Adjust as necessary config.pin_pclk = 22; // Adjust as necessary config.pin_vsync = 25; // Adjust as necessary config.pin_href = 23; // Adjust as necessary config.pin_sscb_sda = 26; // Adjust as necessary config.pin_sscb_scl = 27; // Adjust as necessary config.pin_pwdn = 32; // Adjust as necessary config.pin_reset = -1; // Reset pin config.xclk_freq_hz = 20000000; config.pixel_format = PIXFORMAT_JPEG; // Initialize the camera esp_err_t err = esp_camera_init(&config); } void loop() { // Your code to capture images and send them to OpenCV }
1. Make sure you have OpenCV installed on your computer. You can install it via pip:
pip install opencv-python
2. Use the following Python script to capture video from the ESP32-CAM and perform object detection:
import cv2 import numpy as np url = 'http:///stream' # Replace with your ESP32-CAM IP cap = cv2.VideoCapture(url) while True: ret, frame = cap.read() if not ret: break # Perform object detection (e.g., using Haar cascades) # haar_cascade = cv2.CascadeClassifier('path/to/haarcascade.xml') # objects = haar_cascade.detectMultiScale(frame, scaleFactor=1.1, minNeighbors=5) # Display the results cv2.imshow('Object Detection', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
In this section, we explain the code:
By following this tutorial, you have learned how to set up an ESP32-CAM for object detection using OpenCV. This integration allows you to create powerful IoT applications that utilize computer vision capabilities.