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r1999path.py
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r1999path.py
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import os
import json
import api
import cv2
import time
import api
# 读取config.json文件
with open('config.json', 'r') as f:
config = json.load(f)
device_id = config['device_id']
def is_game_on():
appid = 'com.shenlan.m.reverse1999'
# 检测应用是否在前台
with open('config.json', 'r') as f:
config = json.load(f)
adb_path = config['adb_path']
command = (f'{adb_path} -s {device_id} '
'shell dumpsys window windows')
try:
process = os.popen(command)
output = process.read()
process.close()
if appid not in output:
# 应用不在前台，运行应用
print("游戏不在前台，正在启动")
os.popen(f'{adb_path} -s {device_id} shell monkey -p {appid} -c android.intent.category.LAUNCHER 1')
time.sleep(8)
else:
# 处理输出
print('应用已在前台')
except Exception as e:
print(f'Error: {e}')
def where_am_i():
is_game_on()
screen = cv2.imread(api.get_screen_shot())
# print(f'screen shape: {screen.shape}')
screen_gray = cv2.cvtColor(screen, cv2.COLOR_BGR2GRAY)
template_imgs = {
'title': {'img': cv2.imread('img/title.png', cv2.IMREAD_GRAYSCALE), 'pos': (390, 240, 500, 220)},
'policy': {'img': cv2.imread('img/agree.png', cv2.IMREAD_GRAYSCALE), 'pos': (600, 430, 200, 100)},
'update': {'img': cv2.imread('img/download.png', cv2.IMREAD_GRAYSCALE), 'pos': (770,440, 200, 60)},
'close': {'img': cv2.imread('img/close.png', cv2.IMREAD_GRAYSCALE), 'pos': (640,0, 640, 720)},
'got':{'img': cv2.imread('img/got.png', cv2.IMREAD_GRAYSCALE), 'pos': (605,20, 80, 80)},
'signin':{'img': cv2.imread('img/signin.png', cv2.IMREAD_GRAYSCALE), 'pos': (739,40, 50, 50)},
'login': {'img': cv2.imread('img/login.png', cv2.IMREAD_GRAYSCALE), 'pos': (590, 510, 200, 50)},
'menu': {'img': cv2.imread('img/menu0.png', cv2.IMREAD_GRAYSCALE), 'pos': (48,506, 90, 90)},
'nothome': {'img': cv2.imread('img/home.png', cv2.IMREAD_GRAYSCALE), 'pos': (120,25, 50, 50)},
'notmenu': {'img': cv2.imread('img/back.png', cv2.IMREAD_GRAYSCALE), 'pos': (25,25, 50, 50)},
'notmenu2': {'img': cv2.imread('img/back2.png', cv2.IMREAD_GRAYSCALE), 'pos': (25,25, 50, 50)},#白色背景的返回键，适用于资源关卡
}
# 使用cv2.matchTemplate函数和循环判断多个图像中的某一个是否在另一张图像中，并返回匹配到的图像的名称
max_val = 0
max_template_name = ''
for template_name, template_info in template_imgs.items():
x, y, w, h = template_info['pos']
template_img = template_info['img']
screen_gray_cropped = screen_gray[y:y+h, x:x+w]
#print(f'screen_gray_cropped shape: {screen_gray_cropped.shape}')
#print(f'template_img shape: {template_img.shape}')
# 对图像和模板进行归一化
#img_norm = cv2.normalize(screen_gray_cropped, None, 0, 255, cv2.NORM_MINMAX)
#template_norm = cv2.normalize(template_img, None, 0, 255, cv2.NORM_MINMAX)
# 对灰度图像进行直方图均衡化
#img_eq = cv2.equalizeHist(screen_gray_cropped)
#template_eq = cv2.equalizeHist(template_img)
# 使用cv2.matchTemplate函数进行模板匹配
result = cv2.matchTemplate(screen_gray_cropped, template_img, cv2.TM_CCOEFF_NORMED)
if cv2.minMaxLoc(result)[1] > max_val:
max_val = cv2.minMaxLoc(result)[1]
max_template_name = template_name
# 获取匹配结果矩阵中最大值的位置
_, max_val, _, max_loc = cv2.minMaxLoc(result)
# 获取模板图像的宽度和高度
tw, th = template_img.shape[::-1]
# 在匹配到的目标上画一个矩形框
cv2.rectangle(screen, (x + max_loc[0], y + max_loc[1]), (x + max_loc[0] + tw, y + max_loc[1] + th), (0, 0, 255), 2)
if max_val < 0.6:
print('未匹配到任何模板图像')
print(max_val,max_template_name)
return None
else:
print(f'匹配到了{max_template_name}')
# 将结果保存到cache/result.png文件中
cv2.imwrite('cache/result.png', screen)
return max_template_name
def find_episode(n):
text, coords = api.corp_ocr_with_coords(0, 545, 1280, 30)
if not text:
print('未找到任何文本')
return None
number_str = ''.join(filter(str.isdigit, text[0]))
if number_str.endswith('7'):
number_str = number_str[:-1]
if number_str:
for i, word in enumerate(number_str):
if word.isdigit() and int(word) == n:
return coords[i]
else:
print('未找到数字')
return None
def login():
api.touch(635,248)
time.sleep(0.5)