Gesture Recognition

gesturercog.py

import cv2
import mediapipe as mp

# Initialize MediaPipe Hands model
mp_hands = mp.solutions.hands
hands = mp_hands.Hands()

# Initialize MediaPipe drawing utilities
mp_drawing = mp.solutions.drawing_utils

def identify_gesture(hand_landmarks):
    thumb_tip = hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP]
    index_tip = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
    middle_tip = hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
    ring_tip = hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_TIP]
    pinky_tip = hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_TIP]
    wrist = hand_landmarks.landmark[mp_hands.HandLandmark.WRIST]

    # Thumbs Up: Check if thumb is above other fingers and wrist
    if thumb_tip.y < wrist.y and all(finger.y > wrist.y for finger in [index_tip, middle_tip, ring_tip, pinky_tip]):
        return "Thumbs Up"

    # Victory / Peace Sign: Check if index and middle fingers are up, others are down
    if all(finger.y < wrist.y for finger in [index_tip, middle_tip]) and all(finger.y > wrist.y for finger in [ring_tip, pinky_tip]):
        return "Victory / Peace"

    # Hand Open: Check if all finger tips are above the wrist
    if all(finger.y < wrist.y for finger in [thumb_tip, index_tip, middle_tip, ring_tip, pinky_tip]):
        return "Hand Open"

    # Hand Closed: If none of the above
    return "Hand Closed"


# Capture video from the webcam
cap = cv2.VideoCapture(0)

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        continue

    # Convert the frame to RGB
    frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    results = hands.process(frame_rgb)

    # Draw hand landmarks and analyze gestures
    if results.multi_hand_landmarks:
        for hand_landmarks in results.multi_hand_landmarks:
            mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)

            # Gesture analysis
            gesture = identify_gesture(hand_landmarks)
            print(gesture)  # Print the recognized gesture

    # Display the frame
    cv2.imshow('Gesture Recognition', frame)

    # Break the loop with 'q'
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the webcam and close OpenCV window
cap.release()
cv2.destroyAllWindows()