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Estimator.py
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import cv2
from PIL import Image, ImageFilter
from adbutils import AdbDevice
from Item import Item
from ADBManager import ADBManager
from ImageUtils import ImgUtils
class WrongItemException(Exception):
def __init__(self, e):
super().__init__(self)
self.e = e
def __str__(self):
return self.e
class Estimator:
# 默认使用雷电模拟器的ADB端口
screenshot: Image
address: str = ""
device: AdbDevice
adbManager = ADBManager()
# 截图的位置
pos = [((417, 309), (510, 345)),
((581, 304), (664, 350)), # 主词条
((390, 365), (470, 390)),
((600, 365), (660, 390)), # 1
((390, 385), (470, 410)),
((600, 385), (660, 410)), # 2
((390, 410), (470, 435)),
((600, 410), (660, 435)), # 3
((390, 435), (470, 460)),
((600, 435), (660, 460)), # 4
((390, 475), (470, 500)),
((620, 475), (660, 500)), # 装备分数
((425, 515), (510, 540))]
# 评估结果，下标从0到3对应价值从低到高，文字内容比较抽象，下标4表示尚未强化完毕
result = ["请直接丢进垃圾桶，狗都不要", "吃剩的，给小弟咂么个味儿行了", "凑合能用，值得重铸",
"有这运气你玩游戏不买彩票？", "有潜力继续强化", "凑合用，但不值得重铸"]
def __init__(self, address: str):
self.address = address
self.device = self.adbManager.connect(address=self.address)
# threshold 用于设置截图的二值化阈值，取值范围0-255 对装备词条识别设置成105效果比较好，默认就设成105了
def readPicture(self, top_left, bottom_right, threshold=105):
# 截取矩形框内的图像
cropped_image = self.screenshot[top_left[1]:bottom_right[1], top_left[0]:bottom_right[0]]
# 保存截取的图像
cv2.imwrite(f'cropped_image.png', cropped_image)
cropped_image = Image.open(f'cropped_image.png').convert('L')
img = cropped_image.point(lambda x: 0 if x > threshold else 255, '1').filter(ImageFilter.EDGE_ENHANCE_MORE)
try:
text = ImgUtils.img2str(img)
except BaseException as e:
raise e
return text.replace('\f', '')
def getItem(self):
screenshot = ImgUtils.screenshot(self.device)
screenshot.save("screenshot.png")
self.screenshot = ImgUtils.readImg("screenshot.png")
item_type = ""
path = [("传说项链", "./resource/img/red_amulet.png"), ("传说戒指", "./resource/img/red_ring.png"),
("传说护甲", "./resource/img/red_armor.png"), ("传说鞋子", "./resource/img/red_boots.png"),
("传说武器", "./resource/img/red_weapon.png"), ("传说头盔", "./resource/img/red_helmet.png"),
("英雄项链", "./resource/img/purple_amulet.png"), ("英雄戒指", "./resource/img/purple_ring.png"),
("英雄头盔", "./resource/img/purple_helmet.png"), ("英雄鞋子", "./resource/img/purple_boots.png"),
("英雄护甲", "./resource/img/purple_armor.png"), ("英雄武器", "./resource/img/purple_weapon.png")]
flag = False
for it in path:
img = ImgUtils.readImg(it[1])
result = ImgUtils.check(self.screenshot, img)
if result:
flag = True
item_type = it[0]
break
if not flag:
raise WrongItemException("未识别到英雄/传说装备")
# 紫左三
level = 0
sub_attribute: [[str, str]] = []
main_attribute = [self.readPicture(self.pos[0][0], self.pos[0][1]),
self.readPicture(self.pos[1][0], self.pos[1][1])]
i = 2
while i < 10:
buf = [self.readPicture(self.pos[i][0], self.pos[i][1]),
self.readPicture(self.pos[i + 1][0], self.pos[i + 1][1])]
if not buf[0] == "":
sub_attribute.append(buf)
else:
i = 10
break
i = i + 2
score = int(self.readPicture(self.pos[i + 1][0], self.pos[i + 1][1]))
set_type = self.readPicture(self.pos[i + 2][0], self.pos[i + 2][1])
lvl = self.readPicture((445, 100), (500, 135), 180).replace("+", "")
if '+' in lvl:
level = int(lvl)
else:
level = 0
# 等级的识别 二值化阈值设为180（等级区域的颜色为橙色）
item = Item(item_type, level, score, main_attribute, sub_attribute, set_type)
return item
def estimate(self, item: Item):
# item_flag用于标注左右三件和红紫信息 0：红左 1：红右 2：紫左 3：紫右 99: 初始值（如果没变就说明有bug）
item_flag = 99
# 评估结果，下标从0到3对应价值从低到高，文字内容比较抽象，下标4表示尚未强化完毕
# result = [0 "请直接丢进垃圾桶，狗都不要", 1 "吃剩的，给小弟咂么个味儿行了", 2 "凑合能用，值得重铸",
# 3 "有这运气你玩游戏不买彩票？", 4 "有潜力继续强化",5 "凑合用，但不值得重铸"]
if "英雄" in item.item_type:
bias = 0
else:
bias = 2
if "戒指" in item.item_type or "项链" in item.item_type or "鞋子" in item.item_type:
item_flag = 3
if "攻击力" in item.main_attribute[0] or "防御力" in item.main_attribute[0] or \
"生命值" in item.main_attribute[0] and not ("%" in item.main_attribute[1]):
return self.result[0]
else:
if item.level < 6:
if item.score < 18 + item.level + bias:
return self.result[0]
else:
return self.result[4]
elif item.level < 9:
if item.score < 32 + item.level - 6:
return self.result[0]
else:
return self.result[4]
elif item.level < 12:
if item.score < 38 + item.level - 9:
return self.result[0]
else:
return self.result[4]
elif item.level < 15:
if item.score < 44 + item.level - 12:
return self.result[1]
else:
return self.result[4]
else:
if item.score < 50:
return self.result[1]
elif item.score < 63:
return self.result[2]
else:
return self.result[3]
else:
item_flag = 2
if item.level < 6:
if item.score < 20 + item.level + bias:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 4:
return self.result[4]
else:
return self.result[0]
else:
return self.result[0]
else:
return self.result[4]
elif item.level < 9:
if item.score < 34 + item.level:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 10:
return self.result[4]
else:
return self.result[0]
else:
return self.result[0]
else:
return self.result[4]
elif item.level < 12:
if item.score < 40 + item.level:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 10:
return self.result[4]
else:
return self.result[0]
else:
return self.result[0]
else:
return self.result[4]
elif item.level < 15:
if item.score < 46 + item.level:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 15:
return self.result[4]
elif item.score < 40 + item.level:
return self.result[1]
elif item.score >= 46 + item.level:
return self.result[4]
else:
return self.result[5]
else:
return self.result[1]
else:
return self.result[4]
else:
if item.score < 52:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 20:
return self.result[3]
elif int(pair[1]) >= 15:
return self.result[2]
else:
return self.result[5]
else:
return self.result[1]
elif item.score < 65:
for pair in item.sub_attribute:
if "速度" in pair[0]:
if int(pair[1]) >= 20:
return self.result[3]
elif int(pair[1]) >= 15:
return self.result[2]
else:
return self.result[5]
else:
return self.result[2]
else:
return self.result[3]