main.py

import cv2
import numpy as np
import mediapipe as mp
import tensorflow as tf
import keras
#from keras.src.saving import load_model
import pyautogui

# initialize mediapipe
mpHands = mp.solutions.hands
hands = mpHands.Hands(max_num_hands=1, min_detection_confidence=0.7)
mpDraw = mp.solutions.drawing_utils
 
# Load the gesture recognizer model

path_to_mp_hand_gesture= 0 #add path instead of 0
model = keras.layers.TFSMLayer(path_to_mp_hand_gesture, call_endpoint='serving_default')
# Load class names
f = open('gesture.names', 'r')
classNames = f.read().split('\n')
f.close()
print(classNames)

# Initialize the webcam
cap = cv2.VideoCapture(0)

while True:
    # Read each frame from the webcam
    _, frame = cap.read()

    x, y, c = frame.shape

    # Flip the frame vertically
    frame = cv2.flip(frame, 1)
    framergb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    # Get hand landmark prediction
    result = hands.process(framergb)

    # print(result)

    className = ''

    # post process the result
    if result.multi_hand_landmarks:
        landmarks = []
        for handslms in result.multi_hand_landmarks:
            for lm in handslms.landmark:
                # print(id, lm)
                lmx = int(lm.x * x)
                lmy = int(lm.y * y)

                landmarks.append([lmx, lmy])

            # Drawing landmarks on frames
            mpDraw.draw_landmarks(frame, handslms, mpHands.HAND_CONNECTIONS)

            # Predict gesture
            prediction = model.predict([landmarks])
            # print(prediction)
            classID = np.argmax(prediction)
            className = classNames[classID]

    # show the prediction on the frame
    cv2.putText(frame, className, (10, 50), cv2.FONT_HERSHEY_SIMPLEX,
                1, (0, 0, 255), 2, cv2.LINE_AA)

    # Show the final output
    cv2.imshow("Output", frame)
    if className == "stop":
        pyautogui.press('space')
    if className == "thumbs up":
        pyautogui.press('up')
    if className == "thumbs down":
        pyautogui.press('down')
    if cv2.waitKey(1) == ord('q'):
        break

# release the webcam and destroy all active windows
cap.release()

cv2.destroyAllWindows()