✋ Hand Gesture Controlled Servo Using Python & Arduino 🤖
Component | Description |
Arduino Uno | The microcontroller board for processing data. |
Servo Motor | Rotates based on hand gestures. |
Computer | Runs the Python script. |
USB Cable | Connects Arduino to the computer. |
Library | Installation Command | Purpose |
OpenCV | pip install opencv-python | Used for image processing. |
MediaPipe | pip install mediapipe | Detects hand gestures. |
PySerial | pip install pyserial | Enables communication between Python & Arduino. |
| Software | Installation Link | Purpose |
| Python (pip) | Download Python | Runs the hand tracking script. |
| Arduino IDE | Download Arduino IDE | Uploads code to the Arduino board. |
| VS Code | Download VS Code | Code editor for Python and Arduino. |
pip install opencv-python mediapipe pyserial
#include <Servo.h>
Servo myServo;
int angle;
void setup() {
myServo.attach(9); // Servo connected to pin 9
Serial.begin(9600); // Begin serial communication
}
void loop() {
if (Serial.available() > 0) {
angle = Serial.parseInt(); // Read the angle from Python
if (angle >= 0 && angle <= 180) {
myServo.write(angle); // Set the servo angle
}
}
}
import cv2
import mediapipe as mp
import serial
import time
import math
# Set up serial communication (update the COM port as per your system)
arduino = serial.Serial('COM9', 9600) # Replace 'COM4' with your Arduino's COM port
time.sleep(2) # Wait for Arduino to initialize
# Initialize MediaPipe Hand Detection
mp_hands = mp.solutions.hands
hands = mp_hands.Hands(max_num_hands=1, min_detection_confidence=0.7)
mp_draw = mp.solutions.drawing_utils
# Function to map distance to servo angle
def map_distance_to_angle(distance, min_dist, max_dist, min_angle, max_angle):
return int((distance - min_dist) * (max_angle - min_angle) / (max_dist - min_dist) + min_angle)
# OpenCV video capture
cap = cv2.VideoCapture(0)
while True:
success, img = cap.read()
if not success:
break
# Convert to RGB for MediaPipe
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
results = hands.process(img_rgb)
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
# Get thumb tip and index finger tip coordinates
thumb_tip = hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP]
index_tip = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
h, w, _ = img.shape
thumb_x, thumb_y = int(thumb_tip.x * w), int(thumb_tip.y * h)
index_x, index_y = int(index_tip.x * w), int(index_tip.y * h)
# Draw a line between the thumb and index finger
cv2.line(img, (thumb_x, thumb_y), (index_x, index_y), (255, 0, 0), 3)
cv2.circle(img, (thumb_x, thumb_y), 5, (0, 255, 0), cv2.FILLED)
cv2.circle(img, (index_x, index_y), 5, (0, 255, 0), cv2.FILLED)
# Calculate distance
distance = math.hypot(index_x - thumb_x, index_y - thumb_y)
# Map the distance to servo angle (0-90 degrees)
angle = map_distance_to_angle(distance, min_dist=50, max_dist=200, min_angle=0, max_angle=180)
angle = max(0, min(180, angle)) # Ensure angle is within bounds
# Send angle to Arduino
arduino.write(f"{angle}\n".encode())
# Display distance and angle
cv2.putText(img, f"Angle: {angle} deg", (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
# Draw landmarks
mp_draw.draw_landmarks(img, hand_landmarks, mp_hands.HAND_CONNECTIONS)
# Display the image
cv2.imshow("Hand Tracking", img)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Cleanup
cap.release()
cv2.destroyAllWindows()
arduino.close()
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