-
Notifications
You must be signed in to change notification settings - Fork 4.3k
/
wechat_jump_auto_curves.py
388 lines (346 loc) · 13.6 KB
/
wechat_jump_auto_curves.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
# -*- coding: utf-8 -*-
"""
##基于python3.5(64位)
###如果缺少scikit-image库,建议进下面网址下载whl直接安装
##https://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-image
=== 思路 ===
核心:每次落稳之后截图,根据截图算出棋子的坐标和下一个块顶面的中点坐标,
根据两个点的距离乘以一个时间系数获得长按的时间
识别棋子:靠棋子的颜色来识别位置,通过截图发现最下面一行大概是一条
直线,就从上往下一行一行遍历,比较颜色(颜色用了一个区间来比较)
找到最下面的那一行的所有点,然后求个中点,求好之后再让 Y 轴坐标
减小棋子底盘的一半高度从而得到中心点的坐标
识别棋盘:靠底色和方块的色差来做,从分数之下的位置开始,一行一行扫描,
由于圆形的块最顶上是一条线,方形的上面大概是一个点,所以就
用类似识别棋子的做法多识别了几个点求中点,这时候得到了块中点的 X
轴坐标,这时候假设现在棋子在当前块的中心,根据一个通过截图获取的
固定的角度来推出中点的 Y 坐标
最后:根据两点的坐标算距离乘以系数来获取长按时间(似乎可以直接用 X 轴距离)
"""
from __future__ import print_function, division
import sys
import time
import math
import random
from PIL import Image
from six.moves import input
from skimage import io,transform
import numpy as np
import tensorflow as tf
try:
from common import debug, config, screenshot, UnicodeStreamFilter
from common.auto_adb import auto_adb
except Exception as ex:
print(ex)
print('请将脚本放在项目根目录中运行')
print('请检查项目根目录中的 common 文件夹是否存在')
exit(1)
adb = auto_adb()
VERSION = "1.1.4"
# DEBUG 开关,需要调试的时候请改为 True,不需要调试的时候为 False
DEBUG_SWITCH = False
# Magic Number,不设置可能无法正常执行,请根据具体截图从上到下按需
# 设置,设置保存在 config 文件夹中
config = config.open_accordant_config()
under_game_score_y = config['under_game_score_y']
# 长按的时间系数,请自己根据实际情况调节
press_coefficient = config['press_coefficient']
# 二分之一的棋子底座高度,可能要调节
piece_base_height_1_2 = config['piece_base_height_1_2']
# 棋子的宽度,比截图中量到的稍微大一点比较安全,可能要调节
piece_body_width = config['piece_body_width']
target_score=1024 ##目标分数
total_step=30 ##达到目标次数所需游戏次数
start_score=100 ##设置第一次分数(目前分数)
def set_button_position(im):
"""
将 swipe 设置为 `再来一局` 按钮的位置
"""
global swipe_x1, swipe_y1, swipe_x2, swipe_y2
w, h = im.size
left = int(w / 2)
top = int(1584 * (h / 1920.0))
left = int(random.uniform(left - 100, left + 100))
top = int(random.uniform(top - 100, top + 100)) # 随机防 ban
after_top = int(random.uniform(top - 100, top + 100))
after_left = int(random.uniform(left - 100, left + 100))
swipe_x1, swipe_y1, swipe_x2, swipe_y2 = left, top, after_left, after_top
def jump(distance):
"""
跳跃一定的距离
"""
press_time = distance * press_coefficient
press_time = max(press_time, 200) # 设置 200ms 是最小的按压时间
press_time = int(press_time)
cmd = 'shell input swipe {x1} {y1} {x2} {y2} {duration}'.format(
x1=swipe_x1,
y1=swipe_y1,
x2=swipe_x2,
y2=swipe_y2,
duration=press_time
)
print('{} {}'.format(adb.adb_path, cmd))
adb.run(cmd)
return press_time
def find_piece_and_board(im):
"""
寻找关键坐标
"""
w, h = im.size
piece_x_sum = 0
piece_x_c = 0
piece_y_max = 0
board_x = 0
board_y = 0
scan_x_border = int(w / 8) # 扫描棋子时的左右边界
scan_start_y = 0 # 扫描的起始 y 坐标
im_pixel = im.load()
# 以 50px 步长,尝试探测 scan_start_y
for i in range(int(h / 3), int(h*2 / 3), 50):
last_pixel = im_pixel[0, i]
for j in range(1, w):
pixel = im_pixel[j, i]
# 不是纯色的线,则记录 scan_start_y 的值,准备跳出循环
if pixel != last_pixel:
scan_start_y = i - 50
break
if scan_start_y:
break
print('scan_start_y: {}'.format(scan_start_y))
# 从 scan_start_y 开始往下扫描,棋子应位于屏幕上半部分,这里暂定不超过 2/3
for i in range(scan_start_y, int(h * 2 / 3)):
# 横坐标方面也减少了一部分扫描开销
for j in range(scan_x_border, w - scan_x_border):
pixel = im_pixel[j, i]
# 根据棋子的最低行的颜色判断,找最后一行那些点的平均值,这个颜
# 色这样应该 OK,暂时不提出来
if (50 < pixel[0] < 60) \
and (53 < pixel[1] < 63) \
and (95 < pixel[2] < 110):
piece_x_sum += j
piece_x_c += 1
piece_y_max = max(i, piece_y_max)
if not all((piece_x_sum, piece_x_c)):
return 0, 0, 0, 0
piece_x = int(piece_x_sum / piece_x_c)
piece_y = piece_y_max - piece_base_height_1_2 # 上移棋子底盘高度的一半
# 限制棋盘扫描的横坐标,避免音符 bug
if piece_x < w/2:
board_x_start = piece_x
board_x_end = w
else:
board_x_start = 0
board_x_end = piece_x
for i in range(int(h / 3), int(h * 2 / 3)):
last_pixel = im_pixel[0, i]
if board_x or board_y:
break
board_x_sum = 0
board_x_c = 0
for j in range(int(board_x_start), int(board_x_end)):
pixel = im_pixel[j, i]
# 修掉脑袋比下一个小格子还高的情况的 bug
if abs(j - piece_x) < piece_body_width:
continue
# 修掉圆顶的时候一条线导致的小 bug,这个颜色判断应该 OK,暂时不提出来
if abs(pixel[0] - last_pixel[0]) \
+ abs(pixel[1] - last_pixel[1]) \
+ abs(pixel[2] - last_pixel[2]) > 10:
board_x_sum += j
board_x_c += 1
if board_x_sum:
board_x = board_x_sum / board_x_c
last_pixel = im_pixel[board_x, i]
# 从上顶点往下 +274 的位置开始向上找颜色与上顶点一样的点,为下顶点
# 该方法对所有纯色平面和部分非纯色平面有效,对高尔夫草坪面、木纹桌面、
# 药瓶和非菱形的碟机(好像是)会判断错误
for k in range(i+274, i, -1): # 274 取开局时最大的方块的上下顶点距离
pixel = im_pixel[board_x, k]
if abs(pixel[0] - last_pixel[0]) \
+ abs(pixel[1] - last_pixel[1]) \
+ abs(pixel[2] - last_pixel[2]) < 10:
break
board_y = int((i+k) / 2)
# 如果上一跳命中中间,则下个目标中心会出现 r245 g245 b245 的点,利用这个
# 属性弥补上一段代码可能存在的判断错误
# 若上一跳由于某种原因没有跳到正中间,而下一跳恰好有无法正确识别花纹,则有
# 可能游戏失败,由于花纹面积通常比较大,失败概率较低
for j in range(i, i+200):
pixel = im_pixel[board_x, j]
if abs(pixel[0] - 245) + abs(pixel[1] - 245) + abs(pixel[2] - 245) == 0:
board_y = j + 10
break
if not all((board_x, board_y)):
return 0, 0, 0, 0
return piece_x, piece_y, board_x, board_y
def yes_or_no(prompt, true_value='y', false_value='n', default=True):
"""
检查是否已经为启动程序做好了准备
"""
default_value = true_value if default else false_value
prompt = '{} {}/{} [{}]: '.format(prompt, true_value,
false_value, default_value)
i = input(prompt)
if not i:
return default
while True:
if i == true_value:
return True
elif i == false_value:
return False
prompt = 'Please input {} or {}: '.format(true_value, false_value)
i = input(prompt)
def pross_data(image):
pixels = list(image.getdata()) # 得到像素数据 灰度0-255
#print(len(pixels))
for i in range(len(pixels)):
if pixels[i]<100:
pixels[i]=0
else:
pixels[i]=255
return pixels
def pixel_division(img,w,h):
pixels = list(img.getdata())
row_pix=np.zeros([1,h])
col_pix=np.zeros([1,w])
for i in range(w):
for j in range(h):
if pixels[j*w+i]<100:
row_pix[0,j]+=1
col_pix[0,i]+=1
start_h=0
end_h=0
flag=0
for j in range(h):
if row_pix[0,j]>=1 and flag==0:
start_h=j
flag=1
if row_pix[0,j]>=1:
end_h=j
pixels_Widh=[]
end_w=0
for i in range(1,w):
if col_pix[0,i-1]<=0 and col_pix[0,i]>=1:
pixels_Widh.append(i-1)
if col_pix[0,i]>=1:
end_w=i
pixels_Widh.append(end_w+1)
return start_h,end_h,pixels_Widh
def strint(score0):
if(score0<10):
return str(score0)
else:
return ""
def read_one_image(path):
img = io.imread(path)
w=81
h=81
c=1
img = transform.resize(img,(w,h,c))
return np.asarray(img)
def main():
"""
主函数
"""
op = yes_or_no('请确保手机打开了 ADB 并连接了电脑,'
'然后打开跳一跳并【开始游戏】后再用本程序,确定开始?')
if not op:
print('bye')
return
print('程序版本号:{}'.format(VERSION))
debug.dump_device_info()
screenshot.check_screenshot()
i, next_rest, next_rest_time = (0, random.randrange(3, 10),
random.randrange(5, 10))
j= 0
################ 分数曲线公式
y_score=[]
next_start=0
global start_score
for i in range(total_step):
each_score=target_score*(1-np.exp(-0.15*(1024.0/target_score)*i))
y_score.append(each_score)
if start_score>each_score:
next_start=i
next_start+=1
#print(y_score)
if start_score<y_score[0]:
next_start=0
###################
with tf.Session() as sess:
saver = tf.train.import_meta_graph('./resource/model/model.ckpt.meta')
saver.restore(sess,tf.train.latest_checkpoint('./resource/model/'))
graph = tf.get_default_graph()
x = graph.get_tensor_by_name("x:0")
logits = graph.get_tensor_by_name("logits_eval:0")
#####################识别分数
while True:
screenshot.pull_screenshot()
im = Image.open('./autojump.png')
##比例系数
pix_w=im.size[0]*1.0/1080
pix_h=im.size[1]
region=im.crop((0,pix_h*0.1,460*pix_w,pix_h*0.2))
region=region.convert('L')
start_h,end_h,pixels_Widh=pixel_division(region,int(460*pix_w),int(pix_h*0.1))
if start_h==end_h:
continue
data = []
for i in range(len(pixels_Widh)-1):
region1=region.crop((pixels_Widh[i],start_h,pixels_Widh[i+1],end_h))
region1.putdata(pross_data(region1))
str1="./region"+str(i)+".png"
region1.save(str1)
data1 = read_one_image(str1)
data.append(data1)
feed_dict = {x:data}
classification_result = sess.run(logits,feed_dict)
output = []
output = tf.argmax(classification_result,1).eval()
m_score=""
for i in range(len(output)):
m_score+=strint(output[i])
if m_score=="":
continue
m_score=int(m_score)
print('score:{}'.format(m_score))
####################################
# 获取棋子和 board 的位置
print(j)
piece_x, piece_y, board_x, board_y = find_piece_and_board(im)
ts = int(time.time())
print(ts, piece_x, piece_y, board_x, board_y)
set_button_position(im)
if m_score > y_score[next_start]: ##自动结束这一次
print("----------------")
jump(math.sqrt((board_x - piece_x) ** 2 + (board_y - piece_y) ** 2)*5)
next_start+=1
time.sleep(5*random.random())
if next_start >len(y_score):
break
jump(math.sqrt((board_x - piece_x) ** 2 + (board_y - piece_y) ** 2))
if DEBUG_SWITCH:
debug.save_debug_screenshot(ts, im, piece_x,
piece_y, board_x, board_y)
debug.backup_screenshot(ts)
im.close()
i += 1
j += 1
if i == next_rest:
print('已经连续打了 {} 下,休息 {}s'.format(i, next_rest_time))
for j in range(next_rest_time):
sys.stdout.write('\r程序将在 {}s 后继续'.format(next_rest_time - j))
sys.stdout.flush()
time.sleep(1)
print('\n继续')
i, next_rest, next_rest_time = (0, random.randrange(30, 100),
random.randrange(10, 60))
# 为了保证截图的时候应落稳了,多延迟一会儿,随机值防 ban
time.sleep(random.uniform(0.9, 1.2))
if __name__ == '__main__':
try:
main()
except KeyboardInterrupt:
adb.run('kill-server')
print('bye')
exit(0)