sefakcmn00/servo-motor-control-in-ardunio-using-handcascade-tutorial-file-in-opencv

It is the Servo motor control project of our Computer Vision work with Opencv. In this project, an Ardunio Serial port-based servo motor control project was implemented using Opencv and Cvzone artificial intelligence libraries. Below I tried to explain the details of the project step by step.

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Servo-motor-control-in-Ardunio-using-HandCascade-tutorial-file-in-Opencv

It is the Servo motor control project of our Computer Vision work with Opencv. In this project, an Ardunio Serial port-based servo motor control project was implemented using Opencv and Cvzone artificial intelligence libraries. Below I tried to explain the details of the project step by step.

Download Library

First, we will download the libraries we will use.

import cv2
from cvzone.HandTrackingModule import HandDetector
import numpy as np
import pyfirmata
import random

Code block that we connect to Arduino

port = "COM5"
board = pyfirmata.Arduino(port)
servo_pinX = board.get_pin('d:5:s') #pin 5 Arduino
servo_pinY = board.get_pin('d:6:s') #pin 6 Arduino

We add the StandardFirmata project from the Arduino sample Firmata library. It is the library that allows Arduino to communicate with python.

We add the StandardFirmata project from the Arduino sample Firmata library. It is the library that allows Arduino to communicate with python.

Python Code Blog

cap = cv2.VideoCapture(0)
cap.set(3, 1280)
cap.set(4, 720)

detector = HandDetector(detectionCon=0.8, maxHands=2)

port = "COM5"
board = pyfirmata.Arduino(port)
servo_pinX = board.get_pin('d:5:s') #pin 5 Arduino
servo_pinY = board.get_pin('d:6:s') #pin 6 Arduino

posCircle = []
posCircleTarget = []

minHand, maxHand = 20, 220
minDeg, maxDeg = 0, 180
minBar, maxBar = 400, 150
xbox, ybox = 400, 500
wbox, hbox = 450, 450
x_rand = random.randint(xbox + 25, xbox + wbox - 25)
y_rand = random.randint(ybox - hbox + 25, ybox - 25)
score = 0
edgeBox = False

while True:
    success, img = cap.read()
    hands = detector.findHands(img, draw = False)


    if hands:

        hand_l = hands[0]
        lmList_l = hand_l["lmList"]  # List of 21 Landmark points
        length_l, info_l, img = detector.findDistance(lmList_l[8][0:2], lmList_l[4][0:2], img)


        # Hand 2 (Right)
        if len(hands) == 2:
            hand_r = hands[1]
            lmList_r = hand_r["lmList"]  # List of 21 Landmark points
            length_r, info_r, img = detector.findDistance(lmList_r[8][0:2], lmList_r[4][0:2], img)  # with draw


            xl = lmList_l[8][0]
            yl = lmList_l[8][1]
            xr = lmList_r[8][0]
            yr = lmList_r[8][1]

            # left x | right y
            circleX = np.interp(length_l, [minHand, maxHand], [xbox+25, xbox+wbox-25])
            circleY = np.interp(length_r, [minHand, maxHand], [ybox-25, ybox-hbox+25])

            servoX = np.interp(length_l, [minHand, maxHand], [minDeg, maxDeg])
            servoY = np.interp(length_r, [minHand, maxHand], [maxDeg, minDeg])

            barX = np.interp(length_l, [minHand, maxHand], [minBar, maxBar])
            barY = np.interp(length_r, [minHand, maxHand], [minBar, maxBar])

            # circle player
            posCircle = [int(circleX), int(circleY)]
            cv2.circle(img, posCircle, 25, (0, 0, 255), cv2.FILLED )

            if xbox+25 < posCircle[0] < xbox+wbox-25 and ybox-hbox+25 < posCircle[1] < hbox+25:
                colBox = [255, 0, 0]
                if edgeBox == False:
                    edgeBox = not edgeBox
            else:
                colBox = [0, 0, 255]
                if edgeBox:
                    score = 0
                    edgeBox = not edgeBox


            # box area
            cv2.rectangle(img, (xbox, ybox+50), (xbox+wbox, ybox-hbox), colBox, 3)
            cv2.rectangle(img, (xbox, ybox), (xbox+wbox, ybox+50), colBox, cv2.FILLED)
            cv2.putText(img, f'Score : {score}', (xbox+80, ybox+40), cv2.FONT_HERSHEY_PLAIN, 3, (255, 255, 255), 3)

            #circle target
            if x_rand-35 < posCircle[0] < x_rand+35 and y_rand-35 < posCircle[1] < y_rand+35   :
                x_rand = random.randint(xbox + 25, xbox + wbox - 25)
                y_rand = random.randint(ybox - hbox + 25, ybox - 25)
                score += 5
            cv2.circle(img, (x_rand, y_rand), 25, (0, 255, 255), cv2.FILLED)

            #bar
            cv2.rectangle(img, (1180, 150), (1215, 400), (255, 0, 0), 3)
            cv2.rectangle(img, (1180, int(barX)), (1215, 400), (0, 255, 0), cv2.FILLED)

            cv2.rectangle(img, (50, 150), (85, 400), (255, 0, 0), 3)
            cv2.rectangle(img, (50, int(barY)), (85, 400), (0, 255, 0), cv2.FILLED)

            # servo control
            servo_pinX.write(servoX)
            servo_pinY.write(servoY)

    cv2.imshow("Image", img)
    if cv2.waitKey(1) & 0xFF==ord('q'):
        break

Project Output