try_codes_01.py

import cv2
import numpy as np

# Function to detect hand using skin color segmentation
def detect_hand(frame):
    # Convert the frame to the HSV color space
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    
    # Define the range of skin color in HSV
    lower_skin = np.array([0, 20, 70], dtype=np.uint8)
    upper_skin = np.array([20, 255, 255], dtype=np.uint8)
    
    # Create a binary mask using the inRange function
    mask = cv2.inRange(hsv, lower_skin, upper_skin)
    
    # Apply morphological operations to remove noise
    mask = cv2.medianBlur(mask, 5)
    mask = cv2.dilate(mask, None, iterations=2)
    
    # Find contours in the mask
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    
    # Find the largest contour (assumed to be the hand)
    if len(contours) > 0:
        max_contour = max(contours, key=cv2.contourArea)
        if cv2.contourArea(max_contour) > 10000:  # Adjust this value based on your needs
            x, y, w, h = cv2.boundingRect(max_contour)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
    
    return frame

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

while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    # Detect the hand in the frame
    result_frame = detect_hand(frame)
    
    # Display the result
    cv2.imshow('Hand Detection', result_frame)
    
    # Exit the loop if the 'q' key is pressed
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release the webcam and close all windows
cap.release()
cv2.destroyAllWindows()