def get_Target_Posture(img):
img_roi = roi(img, x=401, x_w=553, y=29, y_h=29 + 1)
b, g, r = cv2.split(img_roi) # 颜色通道分离
white_line = r[0][0]
if white_line > 190:
canny = cv2.Canny(cv2.GaussianBlur(r, (3, 3), 0), 0, 100)
Target_Posture = np.argmax(canny)
else:
Target_Posture = 0
if white_line > 250 and Target_Posture < 10:
Target_Posture == len(canny)
return Target_Posture
def get_Self_Posture(img):
img_roi = roi(img, x=401, x_w=490, y=389, y_h=389 + 1)
b, g, r = cv2.split(img_roi) # 颜色通道分离
white_line = r[0][0]
if 155 < white_line < 170 or white_line > 250:
canny = cv2.Canny(cv2.GaussianBlur(r, (3, 3), 0), 0, 100)
Self_Posture = np.argmax(canny)
else:
Self_Posture = 0
if white_line > 250 and Self_Posture < 10:
Self_Posture == len(canny)
return Self_Posture
def get_Self_HP(img):
img_roi = roi(img, x=48, x_w=305, y=409, y_h=409+1)
b, g ,r =cv2.split(img_roi) # Color channel separation
retval, img_th = cv2.threshold(g, 50, 255, cv2.THRESH_TOZERO) # Image threshold processing, if the pixel value is lower than 50, set it to 0
retval, img_th = cv2.threshold(img_th, 70, 255, cv2.THRESH_TOZERO_INV) # Image threshold processing, if the pixel value is higher than 70, set it to 0
target_img = img_th[0]
if 0 in target_img:
Self_HP = np.argmin(target_img)
else:
Self_HP = len(target_img)
return Self_HP
def get_Self_HP(img):
img_roi = roi(img, x=48, x_w=305, y=409, y_h=409 + 1)
b, g, r = cv2.split(img_roi) # 颜色通道分离
retval, img_th = cv2.threshold(g, 50, 255,
cv2.THRESH_TOZERO) # 图像阈值处理，像素点的值低于50的设置为0
retval, img_th = cv2.threshold(
img_th, 70, 255, cv2.THRESH_TOZERO_INV) # 图像阈值处理，像素点的值高于70的设置为0
target_img = img_th[0]
if 0 in target_img:
Self_HP = np.argmin(target_img)
else:
Self_HP = len(target_img)
return Self_HP
def get_Target_HP(img):
img_roi = roi(img, x=48, x_w=216, y=41, y_h=41 + 1)
b, g, r = cv2.split(img_roi) # 颜色通道分离
retval, img_th = cv2.threshold(g, 25, 255,
cv2.THRESH_TOZERO) # 图像阈值处理，像素点的值低于25的设置为0
retval, img_th = cv2.threshold(
img_th, 70, 255, cv2.THRESH_TOZERO_INV) # 图像阈值处理，像素点的值高于70的设置为0
target_img = img_th[0]
if 0 in target_img:
Target_HP = np.argmin(target_img)
else:
Target_HP = len(target_img)
return Target_HP
def main():
paused = True
print("Ready!")
while True:
keys = key_check()
if paused:
if 'T' in keys:
paused = False
print('Starting!')
else:
screen = get_screen() # 获取屏幕图像
status_info = get_status(screen)[4]
print('\r' + status_info, end='') # 显示状态信息
cv2.imshow('roi', roi(screen, x, x_w, y, y_h))
# 校准线
screen[409:, [48, 49, 304, 305], :] = 255 # 自身生命
# screen[389, 401:483, :] = 255 # 自身架势
screen[[384, 385, 392,393], 401:483, :] = 255 # 自身架势
screen[389:, 401, :] = 255 # 自身架势中线
screen[:41, [48, 49, 215, 216], :] = 255 # 目标生命
# screen[29, 401:544, :] = 255 # 目标架势
screen[[25, 26, 32, 33], 401:544, :] = 255 # 目标架势
screen[:29, 401, :] = 255 # 目标架势中线
cv2.imshow('screen', screen)
cv2.waitKey(1)
if 'P' in keys:
cv2.destroyAllWindows()
break
print('\nDone!')
def main():
paused = True
print("Ready!")
while True:
keys = key_check()
if paused:
if 'T' in keys:
paused = False
print('Starting!')
else:
screen = get_screen()
status_info = get_status(screen)[4]
print('\r' + status_info, end='')
cv2.imshow('roi', roi(screen, x, x_w, y, y_h))
# Calibration line
screen[409:, [48, 49, 304, 305], :] = 255 # Self_HP
# screen[389, 401:483, :] = 255 # Self_Posture
screen[[384, 385, 392, 393], 401:483, :] = 255 # Self_Posture
screen[389:, 401, :] = 255 # Self_Posture Midline
screen[:41, [48, 49, 215, 216], :] = 255 # Target_HP
# screen[29, 401:544, :] = 255 # Target_Posture
screen[[25, 26, 32, 33], 401:544, :] = 255 # Target_Posture
screen[:29, 401, :] = 255 # Target_Posture Midline
cv2.imshow('screen', screen)
cv2.waitKey(1)
if 'P' in keys:
cv2.destroyAllWindows()
break
print('\nDone!')
def img_processing(self, screens):
return np.array([
cv2.resize(
roi(cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY), x, x_w, y, y_h),
(in_height, in_width)) for screen in screens
])