media_pipe_hands.py

import json

import cv2
import mediapipe as mp
import redis

mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_hands = mp.solutions.hands

r = redis.StrictRedis(host='localhost', port=6380, db=0)

cap = cv2.VideoCapture(0)
with mp_hands.Hands(
        model_complexity=0,
        min_detection_confidence=0.5,
        min_tracking_confidence=0.5) as hands:
    while cap.isOpened():
        success, image = cap.read()
        if not success:
            print("Ignoring empty camera frame.")
            continue

        image.flags.writeable = False
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
        results = hands.process(image)

        image.flags.writeable = True
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
        if results.multi_hand_landmarks:
            X = results.multi_hand_landmarks[0].landmark[4]
            Y = results.multi_hand_landmarks[0].landmark[8]

            r.set('media_pipe', json.dumps([[X.x, X.y, X.z], [Y.x, Y.y, Y.z]]))

            for hand_landmarks in results.multi_hand_landmarks:
                mp_drawing.draw_landmarks(
                    image,
                    hand_landmarks,
                    mp_hands.HAND_CONNECTIONS,
                    mp_drawing_styles.get_default_hand_landmarks_style(),
                    mp_drawing_styles.get_default_hand_connections_style())
        # Flip the image horizontally for a selfie-view display.
        cv2.imshow('MediaPipe Hands', cv2.flip(image, 1))
        if cv2.waitKey(5) & 0xFF == 27:
            break
            
cap.release()