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cam_command.py
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import cv2
import mediapipe as mp
import math
import pyautogui
import time
# 初始化 MediaPipe 手部追蹤器
mp_hands = mp.solutions.hands
mp_drawing = mp.solutions.drawing_utils
# 門檻值
OK_THRESHOLD = 0.05 # OK 手勢的距離閾值
FIVE_THUMBINDEX = 0.15 # 食指和拇指間距的閾值
FIST_THRESHOLD = 0.07 # 握拳手勢的距離閾值
# 開啟攝影機
cap = cv2.VideoCapture(0)
def is_not_both_hands(hand_landmarks_list):
return len(hand_landmarks_list) < 2
# 判斷 OK 手勢
def is_ok_gesture(thumb_tip, index_tip, other_fingers):
thumb_index_distance = math.sqrt((thumb_tip.x - index_tip.x)**2 + (thumb_tip.y - index_tip.y)**2)
other_finger_distances = [
math.sqrt((finger.x - thumb_tip.x)**2 + (finger.y - thumb_tip.y)**2)
for finger in other_fingers
]
return thumb_index_distance < OK_THRESHOLD and all(dist > 0.1 for dist in other_finger_distances)
# 判斷 握拳 手勢
def is_fist_gesture(hand_landmarks):
wrist = hand_landmarks.landmark[mp_hands.HandLandmark.WRIST]
thumb_tip = hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP]
index_tip = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
middle_tip = hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP]
ring_tip = hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_TIP]
pinky_tip = hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_TIP]
palm_center_x = (wrist.x + hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_MCP].x) / 2
palm_center_y = (wrist.y + hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_MCP].y) / 2
palm_center = type('Point', (object,), {'x': palm_center_x, 'y': palm_center_y})
# 判斷所有手指尖端是否靠近手掌中心
finger_distances = [
math.sqrt((thumb_tip.x - palm_center.x)**2 + (thumb_tip.y - palm_center.y)**2),
math.sqrt((index_tip.x - palm_center.x)**2 + (index_tip.y - palm_center.y)**2),
math.sqrt((middle_tip.x - palm_center.x)**2 + (middle_tip.y - palm_center.y)**2),
math.sqrt((ring_tip.x - palm_center.x)**2 + (ring_tip.y - palm_center.y)**2),
math.sqrt((pinky_tip.x - palm_center.x)**2 + (pinky_tip.y - palm_center.y)**2),
]
# 判斷手指是否彎曲（全部指尖接近手掌中心）
is_fist = all(distance < FIST_THRESHOLD for distance in finger_distances)
# 檢測手背朝向攝像頭
middle_mcp = hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_MCP]
hand_direction = middle_mcp.y < wrist.y # MCP 在手腕上方表示手背向上
return is_fist and hand_direction
# 計算兩個向量的內積
def dot_product(v1, v2):
return v1[0] * v2[0] + v1[1] * v2[1]
# 計算向量的模長
def magnitude(v):
return math.sqrt(v[0]**2 + v[1]**2)
# 偵測拇指是否與其他四指垂直
def check_thumb_perpendicular(thumb_ip, thumb_tip, index_tip):
# 計算拇指指根到指尖的向量
thumb_to_tip = (thumb_tip.x - thumb_ip.x, thumb_tip.y - thumb_ip.y)
# 計算拇指指根到食指指尖的向量
thumb_to_index = (index_tip.x - thumb_ip.x, index_tip.y - thumb_ip.y)
# 計算內積
dot = dot_product(thumb_to_tip, thumb_to_index)
# 計算兩個向量的模長
dist_A = magnitude(thumb_to_tip)
dist_B = magnitude(thumb_to_index)
# 計算兩向量的夾角
if dist_A == 0 or dist_B == 0:
return False # 防止除零錯誤
angle = math.acos(dot / (dist_A * dist_B))
# 判斷兩個向量是否垂直
if 75 <= math.degrees(angle) <= 115:
return True
return False
def is_bird_gesture(hand_landmarks_list):
hand1 = hand_landmarks_list[0]
hand2 = hand_landmarks_list[1]
# 提取第一隻手的節點
thumb_ip_1 = hand1.landmark[mp_hands.HandLandmark.THUMB_IP]
thumb_tip_1 = hand1.landmark[mp_hands.HandLandmark.THUMB_TIP]
index_tip_1 = hand1.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
# 提取第二隻手的節點
thumb_ip_2 = hand2.landmark[mp_hands.HandLandmark.THUMB_IP]
thumb_tip_2 = hand2.landmark[mp_hands.HandLandmark.THUMB_TIP]
index_tip_2 = hand2.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP]
return (
check_thumb_perpendicular(thumb_ip_1, thumb_tip_1, index_tip_1) and
check_thumb_perpendicular(thumb_ip_2, thumb_tip_2, index_tip_2)
)
# 初始化手部追蹤器
with mp_hands.Hands(min_detection_confidence=0.2, min_tracking_confidence=0.5) as hands:
trigger_time = 0
while True:
# 讀取每一幀影像
ret, frame = cap.read()
if not ret:
print("無法讀取影像，請確認攝影機是否開啟")
break
# 轉換顏色從 BGR 到 RGB
rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# 偵測手部
results = hands.process(rgb_frame)
# 如果偵測到手部
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
# 畫出手部關節點和連線
mp_drawing.draw_landmarks(frame, hand_landmarks, mp_hands.HAND_CONNECTIONS)
# 手部節點
thumb_tip = hand_landmarks.landmark[mp_hands.HandLandmark.THUMB_TIP] # 拇指尖端
index_tip = hand_landmarks.landmark[mp_hands.HandLandmark.INDEX_FINGER_TIP] # 食指尖端
middle_tip = hand_landmarks.landmark[mp_hands.HandLandmark.MIDDLE_FINGER_TIP] # 中指尖端
ring_tip = hand_landmarks.landmark[mp_hands.HandLandmark.RING_FINGER_TIP] # 無名指尖端
pinky_tip = hand_landmarks.landmark[mp_hands.HandLandmark.PINKY_TIP] # 小指尖端
if is_not_both_hands(results.multi_hand_landmarks):
# 比 OK 觸發
if is_ok_gesture(thumb_tip, index_tip, [middle_tip, ring_tip, pinky_tip]) and trigger_time < 1:
cv2.putText(frame, "send command!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
trigger_time += 1
pyautogui.press("enter") # 模擬按下 Enter 鍵
print("OK 手勢觸發：Enter")
continue
# 比握拳觸發
if is_fist_gesture(hand_landmarks) and trigger_time < 1:
cv2.putText(frame, "Ping pong!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
trigger_time += 1
pyautogui.write("xdg-open https://www.pingpong.leafish.xyz/") # 模擬輸入 "sudo"
pyautogui.press("enter")
print("Ping pong started!")
continue
else:
# 檢查是否符合雙手 "鳥" 手勢條件
if is_bird_gesture(results.multi_hand_landmarks) and trigger_time < 1:
cv2.putText(frame, "Bird!", (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
trigger_time += 1
pyautogui.write("xdg-open https://www.flappybird.leafish.xyz") # 模擬輸入啟動指令
pyautogui.press("enter")
print("Flappy Bird started!")
continue
else:
trigger_time = 0 # 若未偵測到手部，重置觸發時間
# 顯示攝影機畫面
cv2.imshow("Hand Gesture Detection", frame)
# 按 'q' 鍵退出
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# 釋放攝影機並關閉視窗
cap.release()
cv2.destroyAllWindows()