Hand Sign Deduction

For example, it only deducts thumbs up. Add all signs based on your requirement.

import cv2

import mediapipe as mp

# Initialize video capture and Mediapipe Hands

cap = cv2.VideoCapture(0)

mp_hands = mp.solutions.hands

hands = mp_hands.Hands(min_detection_confidence=0.7, min_tracking_confidence=0.7)

mp_draw = mp.solutions.drawing_utils

while cap.isOpened():

    success, img = cap.read()

    if not success:

        print("Failed to capture video")

        break

    # Convert the BGR image to RGB for Mediapipe processing

    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

    results = hands.process(imgRGB)

    # Check if any hands are detected

    if results.multi_hand_landmarks:

        for hand_landmarks in results.multi_hand_landmarks:

            height, width, _ = img.shape

            # Get coordinates of relevant landmarks

            thumb_tip = hand_landmarks.landmark[4]  # Thumb tip

            thumb_base = hand_landmarks.landmark[1]  # Thumb base (near wrist)

            wrist = hand_landmarks.landmark[0]  # Wrist

            # Convert normalized coordinates to pixel coordinates

            thumb_tip_coords = (int(thumb_tip.x * width), int(thumb_tip.y * height))

            thumb_base_coords = (int(thumb_base.x * width), int(thumb_base.y * height))

            wrist_coords = (int(wrist.x * width), int(wrist.y * height))

            # Check for thumbs-up or thumbs-down

            thumb_tip_y = thumb_tip.y * height

            wrist_y = wrist.y * height

            if thumb_tip_y < wrist_y:  # Thumb tip above wrist: Thumbs up

                cv2.putText(img, "Thumbs Up!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)

            elif thumb_tip_y > wrist_y:  # Thumb tip below wrist: Thumbs down

                cv2.putText(img, "Thumbs Down!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)

            # Draw landmarks and connections

            mp_draw.draw_landmarks(img, hand_landmarks, mp_hands.HAND_CONNECTIONS)

    # Display the image

    cv2.imshow("Thumbs Up/Down Detection", img)

    # Exit on pressing 'q'

    if cv2.waitKey(1) & 0xFF == ord('q'):

        break

# Release resources

cap.release()

cv2.destroyAllWindows()

For more information please read:

https://ai.google.dev/edge/mediapipe/solutions/vision/gesture_recognizer