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main.py
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main.py
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import cv2
import numpy as np
import mediapipe as mp
# Set camera image resolution
cam_width, cam_height = 1024, 768
def initialize_camera(cam_width, cam_height):
cap = cv2.VideoCapture(0)
cap.set(3, cam_width)
cap.set(4, cam_height)
return cap
def air_draw(cap):
mphands = mp.solutions.hands # 使用medidapipe裡的手部辨識功能
hands = mphands.Hands(min_detection_confidence=0.5, min_tracking_confidence=0.5) # 設定手部辨識模型
mpDraw = mp.solutions.drawing_utils # 繪畫工具
# 手部骨架樣式設定
handLms_style = mpDraw.DrawingSpec(color=(73, 93, 70), thickness=6) # 手座標樣式
handCon_style = mpDraw.DrawingSpec(color=(255, 250, 240), thickness=3) # 手連接樣式
trail_image = np.zeros((cam_height, cam_width, 3), np.uint8) # 記錄軌跡並創建一個黑色背景
# 軌跡顏色 (BGR) https://www.rapidtables.com/web/color/RGB_Color.html
trail_color_1 = (255, 255, 0) # Cyan
trail_color_2 = (0, 0, 255) # Red
trail_color_3 = (0, 255, 255) # Yellow
trail_color_4 = (0, 255, 0) # Green
trail_color_5 = (255, 0, 255) # Pink
trail_color_6 = (255, 0, 0) # Blue
trail_color_7 = (0, 128, 255) # Orange
trail_color_8 = (255, 0, 127) # Purple
trail_color_9 = (128, 128, 128) # Grey
trail_color_0 = (255, 255, 255) # White
# 預設值
selected_color = trail_color_0 # 軌跡顏色
drawing = False # 關閉繪圖模式
show_skeleton = True # 顯示骨架
blank_mode = False # 顯示攝影機畫面
while True:
key = cv2.waitKey(1) # 等待1毫秒
# 按空白鍵開啟/關閉繪畫模式
if key == 32:
drawing = not drawing
show_skeleton = not show_skeleton
print("Drawing mode is", "ON" if drawing else "OFF")
# 按B鍵關閉攝影機畫面
if key == ord("b"):
blank_mode = not blank_mode
print("Camera is", "OFF" if blank_mode else "ON")
# 按C鍵清除畫布
if key == ord("c"):
trail_image = np.zeros((cam_height, cam_width, 3), np.uint8)
print("Canvas cleared")
# 按S鍵儲存畫布
if key == ord("s"):
cv2.imwrite("trail_image.png", trail_image)
print("Canvas saved")
# 按Q鍵離開程式
if key == ord("q"):
break
# 按數字鍵選顏色
if key == ord("1"):
print("Cyan")
selected_color = trail_color_1
elif key == ord("2"):
print("Red")
selected_color = trail_color_2
elif key == ord("3"):
print("Yellow")
selected_color = trail_color_3
elif key == ord("4"):
print("Green")
selected_color = trail_color_4
elif key == ord("5"):
print("Pink")
selected_color = trail_color_5
elif key == ord("6"):
print("Blue")
selected_color = trail_color_6
elif key == ord("7"):
print("Orange")
selected_color = trail_color_7
elif key == ord("8"):
print("Purple")
selected_color = trail_color_8
elif key == ord("9"):
print("Grey")
selected_color = trail_color_9
elif key == ord("0"):
print("White (default)")
selected_color = trail_color_0
ret, img = cap.read()
# hand_detection
if ret:
img = cv2.flip(img, 1) # 翻轉圖像
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) # BGR轉RGB
result = hands.process(img_rgb)
img_height = img.shape[0]
img_width = img.shape[1]
if result.multi_hand_landmarks:
for handLms in result.multi_hand_landmarks:
if show_skeleton:
# 顯示每個手的座標及連線、設定樣式
mpDraw.draw_landmarks(img, handLms, mphands.HAND_CONNECTIONS, handLms_style, handCon_style)
for i, lm in enumerate(handLms.landmark): # 輸出每個手的座標點
xPos = int(lm.x * img_width) # 比例乘上寬度
yPos = int(lm.y * img_height) # 比例乘上高度
# 記錄拇指與食指座標
if i == 8:
x8, y8 = xPos, yPos
if ("drawing" in locals() and drawing):
cv2.circle(trail_image, (xPos, yPos), 9, selected_color, cv2.FILLED)
# 確保trail_image與img大小一致
trail_image = cv2.resize(trail_image, (img.shape[1], img.shape[0]))
# 疊加影像
img = cv2.addWeighted(img, 1, trail_image, 1, 0)
if not blank_mode:
cv2.imshow("AirDraw", img)
else:
cv2.imshow("AirDraw", trail_image)
cap.release()
cv2.destroyAllWindows()
def face_detect(cap, file="haarcascade_frontalface_default.xml"):
detector = cv2.CascadeClassifier(file)
while True:
ret, img = cap.read()
img = cv2.flip(img, 1) # 翻轉圖像
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # 將鏡頭影像轉換成灰階
try:
faces = detector.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=4) # 偵測人臉
except cv2.error:
print("找不到XML模型文件，請下載\nhttps://raw.githubusercontent.com/opencv/opencv/4.x/data/haarcascades/haarcascade_frontalface_default.xml\n")
break
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 2) # 使用綠框標記人臉
cv2.imshow('Face detection', img)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
while True:
option = input("[1] 空氣繪圖 [2] 臉部偵測 [Q] 離開\n")
if option == "1":
cap = initialize_camera(cam_width, cam_height)
air_draw(cap)
elif option == "2":
cap = initialize_camera(cam_width, cam_height)
face_detect(cap)
elif option.upper() == "Q":
break
else:
continue