96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
|
import cv2
|
||
|
|
import numpy as np
|
||
|
|
import mediapipe as mp
|
||
|
|
|
||
|
|
# Initialize MediaPipe hand detection
|
||
|
|
mp_hands = mp.solutions.hands
|
||
|
|
hands = mp_hands.Hands()
|
||
|
|
|
||
|
|
# Initialize MediaPipe drawing utilities
|
||
|
|
mp_drawing = mp.solutions.drawing_utils
|
||
|
|
|
||
|
|
# Initialize camera capture
|
||
|
|
cap = cv2.VideoCapture(0)
|
||
|
|
|
||
|
|
# Define the lower and upper bounds of the green color in HSV
|
||
|
|
lower_green = np.array([35, 100, 100])
|
||
|
|
upper_green = np.array([85, 255, 255])
|
||
|
|
|
||
|
|
# Loop through camera frames
|
||
|
|
while True:
|
||
|
|
# Read frame from camera
|
||
|
|
ret, frame = cap.read()
|
||
|
|
|
||
|
|
# Convert frame to RGB for MediaPipe
|
||
|
|
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
||
|
|
|
||
|
|
# Convert frame to HSV for color detection
|
||
|
|
frame_hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
|
||
|
|
|
||
|
|
# Detect hand landmarks with MediaPipe
|
||
|
|
results = hands.process(frame_rgb)
|
||
|
|
|
||
|
|
# Draw landmarks for the first detected hand with palm facing up
|
||
|
|
if results.multi_hand_landmarks:
|
||
|
|
for hand_landmarks in results.multi_hand_landmarks:
|
||
|
|
wrist_y = hand_landmarks.landmark[mp_hands.HandLandmark.WRIST].y
|
||
|
|
mcp_y = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_MCP].y
|
||
|
|
if wrist_y < mcp_y:
|
||
|
|
mp_drawing.draw_landmarks(
|
||
|
|
frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
|
||
|
|
|
||
|
|
# Check if green color is detected near hand landmarks
|
||
|
|
landmarks_near = False
|
||
|
|
landmarks_touched = []
|
||
|
|
|
||
|
|
for landmark in mp_hands.HandLandmark:
|
||
|
|
x = int(hand_landmarks.landmark[landmark].x * frame.shape[1])
|
||
|
|
y = int(hand_landmarks.landmark[landmark].y * frame.shape[0])
|
||
|
|
distance = np.sqrt((x - x_green_center)**2 + (y - y_green_center)**2)
|
||
|
|
if distance < 100:
|
||
|
|
landmarks_near = True
|
||
|
|
landmarks_touched.append(landmark)
|
||
|
|
|
||
|
|
# Display text based on whether the green color is near the landmarks
|
||
|
|
if landmarks_near:
|
||
|
|
# print landmarks touched length
|
||
|
|
print(len(landmarks_touched))
|
||
|
|
# text = ', '.join(str(landmark) for landmark in landmarks_touched)
|
||
|
|
# dont show many, just show one
|
||
|
|
text = str(landmarks_touched[0])
|
||
|
|
cv2.putText(frame, f'Green Detected Near: {text}', (10, 30),
|
||
|
|
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
|
||
|
|
|
||
|
|
# Create a mask for the green color
|
||
|
|
green_mask = cv2.inRange(frame_hsv, lower_green, upper_green)
|
||
|
|
|
||
|
|
# Find contours in the green mask
|
||
|
|
contours, _ = cv2.findContours(
|
||
|
|
green_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
|
||
|
|
|
||
|
|
# Calculate the center of the largest contour
|
||
|
|
largest_contour = max(contours, key=cv2.contourArea, default=None)
|
||
|
|
if largest_contour is not None:
|
||
|
|
moments = cv2.moments(largest_contour)
|
||
|
|
if moments["m00"] != 0:
|
||
|
|
x_green_center = int(moments["m10"] / moments["m00"])
|
||
|
|
y_green_center = int(moments["m01"] / moments["m00"])
|
||
|
|
else:
|
||
|
|
x_green_center, y_green_center = -1, -1
|
||
|
|
else:
|
||
|
|
x_green_center, y_green_center = -1, -1
|
||
|
|
|
||
|
|
# Draw green contours on frame
|
||
|
|
cv2.drawContours(frame, contours, -1, (0, 255, 0), 2)
|
||
|
|
|
||
|
|
# Show frame with landmarks and green color
|
||
|
|
cv2.imshow('Hand Landmarks and Green Color Detection', frame)
|
||
|
|
|
||
|
|
# Exit on 'q' key press
|
||
|
|
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||
|
|
break
|
||
|
|
|
||
|
|
# Release camera and destroy windows
|
||
|
|
cap.release()
|
||
|
|
cv2.destroyAllWindows()
|