# 원본 코드 https://google.github.io/mediapipe/solutions/hands.html
"""The 21 hand landmarks."""
# 손가락 위치 정의 참고 https://google.github.io/mediapipe/images/mobile/hand_landmarks.png
#
# WRIST = 0
# THUMB_CMC = 1
# THUMB_MCP = 2
# THUMB_IP = 3
# THUMB_TIP = 4 엄지
# INDEX_FINGER_MCP = 5
# INDEX_FINGER_PIP = 6
# INDEX_FINGER_DIP = 7
# INDEX_FINGER_TIP = 8 검지
# MIDDLE_FINGER_MCP = 9
# MIDDLE_FINGER_PIP = 10
# MIDDLE_FINGER_DIP = 11
# MIDDLE_FINGER_TIP = 12 중지
# RING_FINGER_MCP = 13
# RING_FINGER_PIP = 14
# RING_FINGER_DIP = 15
# RING_FINGER_TIP = 16 약지
# PINKY_MCP = 17
# PINKY_PIP = 18
# PINKY_DIP = 19
# PINKY_TIP = 20 새끼
# 필요한 라이브러리
# pip install opencv-python mediapipe pillow numpy
import cv2
import mediapipe as mp
from PIL import ImageFont, ImageDraw, Image
import numpy as np
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
mp_drawing_styles = mp.solutions.drawing_styles
# For webcam input:
cap = cv2.VideoCapture(0)
with mp_hands.Hands(
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.")
# If loading a video, use 'break' instead of 'continue'.
continue
# Flip the image horizontally for a later selfie-view display, and convert
# the BGR image to RGB.
image = cv2.cvtColor(cv2.flip(image, 1), cv2.COLOR_BGR2RGB)
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
results = hands.process(image)
# Draw the hand annotations on the image.
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
image_height, image_width, _ = image.shape
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
# 엄지를 제외한 나머지 4개 손가락의 마디 위치 관계를 확인하여 플래그 변수를 설정합니다. 손가락을 일자로 편 상태인지 확인합니다.
thumb_finger_state = 0
if hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_CMC].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_MCP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_MCP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_IP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_IP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP].y * image_height:
thumb_finger_state = 1
index_finger_state = 0
if hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_MCP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_PIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_DIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_DIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP].y * image_height:
index_finger_state = 1
middle_finger_state = 0
if hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_MCP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_PIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_DIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_DIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP].y * image_height:
middle_finger_state = 1
ring_finger_state = 0
if hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_MCP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_PIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_PIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_DIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_DIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_TIP].y * image_height:
ring_finger_state = 1
pinky_finger_state = 0
if hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_MCP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_PIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_PIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_DIP].y * image_height:
if hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_DIP].y * image_height > hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_TIP].y * image_height:
pinky_finger_state = 1
# 손가락 위치 확인한 값을 사용하여 가위,바위,보 중 하나를 출력 해줍니다.
font = ImageFont.truetype("fonts/gulim.ttc", 80)
image = Image.fromarray(image)
draw = ImageDraw.Draw(image)
text = ""
if thumb_finger_state == 1 and index_finger_state == 1 and middle_finger_state == 1 and ring_finger_state == 1 and pinky_finger_state == 1:
text = "보"
elif thumb_finger_state == 1 and index_finger_state == 1 and middle_finger_state == 0 and ring_finger_state == 0 and pinky_finger_state == 0:
text = "가위"
elif index_finger_state == 0 and middle_finger_state == 0 and ring_finger_state == 0 and pinky_finger_state == 0:
text = "주먹"
w, h = font.getsize(text)
x = 50
y = 50
draw.rectangle((x, y, x + w, y + h), fill='black')
draw.text((x, y), text, font=font, fill=(255, 255, 255))
image = np.array(image)
# 손가락 뼈대를 그려줍니다.
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())
cv2.imshow('MediaPipe Hands', image)
if cv2.waitKey(5) & 0xFF == 27:
break
cap.release()
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