import cv2  
import mediapipe as mp   
from PIL import ImageFont, ImageDraw, Image 
import matplotlib.pyplot as plt
import numpy as np
import time


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", 60)
        capture = image
        image = Image.fromarray(image)
        draw = ImageDraw.Draw(image)

        text = ""
        if middle_finger_state == 1 and ring_finger_state == 0 and pinky_finger_state == 0:
            text = "fuck you"
        
        if index_finger_state == 1 and middle_finger_state == 1:
            text = "가위"
            time.sleep(0.2)
            cv2.imwrite('frame.png', capture)
            cap.release()
            cv2.destroyAllWindows()

        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"

        if index_finger_state == 0 and middle_finger_state == 0 and ring_finger_state == 0 and pinky_finger_state == 0:
            text = "주먹"

        l,t,r,b = font.getbbox(text)
        w,h = r-l, b-t

        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)

        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()
cv2.destroyAllWindows()