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main.py
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import cv2
import mediapipe as mp
import math
import numpy as np
import serial
import time
from ctypes import cast, POINTER
from comtypes import CLSCTX_ALL
from pycaw.pycaw import AudioUtilities, IAudioEndpointVolume
# 获取自己的音频设备及其参数
devices = AudioUtilities.GetSpeakers()
interface = devices.Activate(IAudioEndpointVolume._iid_, CLSCTX_ALL, None)
volume = cast(interface, POINTER(IAudioEndpointVolume))
# 由于vol_range与0-100这个不是对应的关系，不方便设置实际的声音，故需要进行装换，但是无法得知其转换关系，只能通过字典的形式查询：
def vol_tansfer(x):
dict = {0: -65.25, 1: -56.99, 2: -51.67, 3: -47.74, 4: -44.62, 5: -42.03, 6: -39.82, 7: -37.89, 8: -36.17,
9: -34.63, 10: -33.24,
11: -31.96, 12: -30.78, 13: -29.68, 14: -28.66, 15: -27.7, 16: -26.8, 17: -25.95, 18: -25.15, 19: -24.38,
20: -23.65,
21: -22.96, 22: -22.3, 23: -21.66, 24: -21.05, 25: -20.46, 26: -19.9, 27: -19.35, 28: -18.82, 29: -18.32,
30: -17.82,
31: -17.35, 32: -16.88, 33: -16.44, 34: -16.0, 35: -15.58, 36: -15.16, 37: -14.76, 38: -14.37, 39: -13.99,
40: -13.62,
41: -13.26, 42: -12.9, 43: -12.56, 44: -12.22, 45: -11.89, 46: -11.56, 47: -11.24, 48: -10.93, 49: -10.63,
50: -10.33,
51: -10.04, 52: -9.75, 53: -9.47, 54: -9.19, 55: -8.92, 56: -8.65, 57: -8.39, 58: -8.13, 59: -7.88,
60: -7.63,
61: -7.38, 62: -7.14, 63: -6.9, 64: -6.67, 65: -6.44, 66: -6.21, 67: -5.99, 68: -5.76, 69: -5.55, 70: -5.33,
71: -5.12, 72: -4.91, 73: -4.71, 74: -4.5, 75: -4.3, 76: -4.11, 77: -3.91, 78: -3.72, 79: -3.53, 80: -3.34,
81: -3.15, 82: -2.97, 83: -2.79, 84: -2.61, 85: -2.43, 86: -2.26, 87: -2.09, 88: -1.91, 89: -1.75,
90: -1.58,
91: -1.41, 92: -1.25, 93: -1.09, 94: -0.93, 95: -0.77, 96: -0.61, 97: -0.46, 98: -0.3, 99: -0.15, 100: 0.0}
return dict[x]
# 设置声音大小
volume.SetMasterVolumeLevel(vol_tansfer(60), None)
# Initialize Mediapipe Hand model and OpenCV camera capture
mp_hands = mp.solutions.hands
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
# Set up drawing tools
mp_drawing = mp.solutions.drawing_utils
draw_spec = mp_drawing.DrawingSpec(thickness=1, circle_radius=1)
# Initialize minimum and maximum degree values
min_degree = 180
max_degree = 0
activate_serial = False
ser = None
serial_port = "COM9"
serial_rate = 115200
if activate_serial:
# Initialize serial connection
ser = serial.Serial(serial_port, serial_rate)
def serial_write(d):
global ser, activate_serial
if activate_serial:
if ser is None:
ser = serial.Serial(serial_port, serial_rate)
ser.write(("%d\n" % int(d)).encode('utf-8'))
def switch_callback(event, x, y, flags, param):
global activate_serial
if event == cv2.EVENT_LBUTTONDOWN and 10 <= x <= 110 and 100 <= y <= 150:
activate_serial = not activate_serial
start_time = time.time()
# Start capturing video frames
while True:
# Read a frame from the camera
ret, frame = cap.read()
# Convert the image to RGB format
image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
agl = None
# Run hand detection on the image
with mp_hands.Hands(
static_image_mode=False,
max_num_hands=2,
min_detection_confidence=0.5) as hands:
results = hands.process(image)
# Draw hand landmarks on the image
if results.multi_hand_landmarks:
for hand_landmarks in results.multi_hand_landmarks:
mp_drawing.draw_landmarks(
image,
hand_landmarks,
mp_hands.HAND_CONNECTIONS,
draw_spec,
draw_spec)
# if hand_landmarks.landmark[mp_hands.HandLandmark.WRIST].x < 0.5:
# pass
# else:
# continue
# Calculate degree of curvature of index finger
index_finger_landmarks = hand_landmarks.landmark[
mp_hands.HandLandmark.INDEX_FINGER_MCP:mp_hands.HandLandmark.INDEX_FINGER_TIP]
if len(index_finger_landmarks) == 3:
p1 = (index_finger_landmarks[0].x, index_finger_landmarks[0].y)
p2 = (index_finger_landmarks[1].x, index_finger_landmarks[1].y)
p3 = (index_finger_landmarks[2].x, index_finger_landmarks[2].y)
angle = math.degrees(
math.atan2(p3[1] - p2[1], p3[0] - p2[0]) - math.atan2(p1[1] - p2[1], p1[0] - p2[0]))
if angle < 0:
angle += 360
# Update minimum and maximum degree values if necessary
if cv2.waitKey(1) & 0xFF == ord('n'):
min_degree = angle if angle < min_degree else min_degree
elif cv2.waitKey(1) & 0xFF == ord('m'):
max_degree = angle if angle > max_degree else max_degree
agl = angle
# Map degree to range 0-180 and write to serial port
mapped_degree = np.interp(angle, [min_degree, max_degree], [0, 180])
volume.SetMasterVolumeLevel(vol_tansfer(int(np.interp(angle, [min_degree, max_degree], [0, 100]))),
None)
serial_write(mapped_degree)
# Convert the image back to BGR format for display
elapsed_time = time.time() - start_time
fps = 1 / elapsed_time
start_time = time.time()
fps_text = "FPS: {:.2f}".format(fps)
cv2.putText(image, fps_text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
switch_text = "Serial: {}".format("On" if activate_serial else "Off")
cv2.putText(image, switch_text, (10, 70), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
switch_color = (0, 255, 0) if activate_serial else (0, 0, 255)
switch_x = 10
switch_y = 100
switch_width = 100
switch_height = 50
# Draw switch button
switch_text = "Serial: {}".format("On" if activate_serial else "Off")
cv2.putText(image, switch_text, (switch_x, switch_y - 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
switch_color = (0, 255, 0) if activate_serial else (0, 0, 255)
switch_thickness = 2
df = 20
cv2.rectangle(image, (switch_x + df, switch_y + df), (switch_x + switch_width - df, switch_y + switch_height - df),
switch_color,
thickness=switch_thickness)
# Draw switch toggle
switch_toggle_x = switch_x + switch_thickness + df if not activate_serial else (
switch_x + switch_width - switch_thickness - 2 * df)
switch_toggle_y = switch_y + int(switch_height / 2)
switch_toggle_color = (0, 255, 0) if activate_serial else (0, 0, 255)
if activate_serial:
cv2.circle(image, (switch_toggle_x + df, switch_toggle_y),
df,
switch_toggle_color, thickness=-1)
else:
cv2.circle(image, (switch_toggle_x, switch_toggle_y),
df,
switch_toggle_color, thickness=-1)
degree_range = max_degree - min_degree
if degree_range > 0 and agl is not None:
current_degree_pos = int((agl - min_degree) / degree_range * 200)
cv2.rectangle(image, (10, 180), (210, 200), (255, 255, 255), thickness=2)
cv2.rectangle(image, (10, 180), (10 + current_degree_pos, 200), (0, 255, 0), thickness=-1)
else:
cv2.rectangle(image, (10, 180), (210, 200), (255, 0, 0), thickness=2)
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
# Display the resulting image
cv2.imshow('Hand Detection', image)
cv2.setMouseCallback('Hand Detection', switch_callback)
if cv2.waitKey(1) == 27:
break
if cv2.getWindowProperty('Hand Detection', cv2.WND_PROP_VISIBLE) < 1:
break
# Release OpenCV camera capture and close all windows
cap.release()
cv2.destroyAllWindows()