AutoFight使用场景图分类并导航到对应关卡

mower/solvers/auto_fight.py

@@ -5,20 +5,23 @@ from scipy.signal import argrelmax
 from skimage.metrics import structural_similarity
 
 from mower.models import secret_front
+from mower.solvers.navigation import NavigationSolver
 from mower.utils import config
 from mower.utils import typealias as tp
 from mower.utils.character_recognize import match_avatar
+from mower.utils.graph import SceneGraphSolver
 from mower.utils.image import cropimg, loadres, thres2
 from mower.utils.log import logger
-from mower.utils.solver import BaseSolver
+from mower.utils.scene import Scene
 from mower.utils.tile_pos import Calc, find_level
 from mower.utils.vector import sa, va
 
 
-class AutoFight(BaseSolver):
+class AutoFight(SceneGraphSolver):
     def run(self, level_name, opers, actions):
         logger.info("Start: 自动战斗")
         logger.info("地图坐标计算：https://github.com/yuanyan3060/Arknights-Tile-Pos")
+        self.level_name = level_name
         level = find_level(level_name, None)
         self.calc = Calc(1920, 1080, level)
         self.actions = actions
@@ -101,39 +104,6 @@ class AutoFight(BaseSolver):
         logger.debug(f"{min_val=} {min_loc=}")
         return min_val <= 0.2
 
-    def in_fight(self) -> bool:
-        "是否在战斗中"
-        img = cropimg(config.recog.img, ((725, 16), (797, 76)))
-        img = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
-        img = cv2.inRange(img, (12, 0, 0), (16, 255, 255))
-        tpl = loadres("fight/enemy", True)
-        result = cv2.matchTemplate(img, tpl, cv2.TM_SQDIFF_NORMED)
-        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
-        value = 0.4
-        logger.debug(f"{min_val}小于{value}则判定在战斗")
-        return min_val < value
-
-    def battle_complete(self) -> bool:
-        "识别行动是否结束"
-        img = cropimg(config.recog.gray, ((87, 268), (529, 383)))
-        img = thres2(img, 200)
-        tpl = loadres("fight/complete", True)
-        result = cv2.matchTemplate(img, tpl, cv2.TM_SQDIFF_NORMED)
-        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
-        value = 0.4
-        logger.debug(f"{min_val}小于{value}则判定行动结束/胜利")
-        return min_val < value
-
-    def battle_fail(self) -> bool:
-        "识别行动是否失败"
-        img = cropimg(config.recog.gray, ((1129, 455), (1626, 531)))
-        tpl = loadres("fight/failed_text", True)
-        result = cv2.matchTemplate(img, tpl, cv2.TM_SQDIFF_NORMED)
-        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
-        value = 0.05
-        logger.debug(f"{min_val}小于{value}则判定行动失败")
-        return min_val < value  # 测试时数值很低，基本为0，或有其他方法
-
     def update_operators(self):
         "识别可部署的干员"
         config.recog.update()
@@ -273,44 +243,49 @@ class AutoFight(BaseSolver):
         sleep(0.5)
 
     def transition(self):
-        config.recog.update()
-
-        if not self.in_fight():
-            if self.battle_fail():
-                logger.warning("行动失败，请检查干员/练度")
-                return True
-            elif self.battle_complete():
-                logger.info("行动结束")
-                return True
-            else:
-                sleep(2)
+        if (scene := self.scene()) == Scene.OPERATOR_FIGHT:
+            if self.loading:
+                self.pause()
+                self.loading = False
+                self.update_operators()
+                self.play()
                 return
-        # if self.action is None:
-        #     self.sleep(10)
-        #     return
-        if self.loading:
-            self.pause()
-            self.loading = False
-            self.update_operators()
-            self.play()
-            return
 
-        if self.playing:
-            for w, d in self.watching.items():
-                if w not in self.location:
-                    continue
-                x, y = self.location[w]
-                if self.skill_ready(x, y):
-                    self.use_skill(x, y)
-                    if d["skill_usage"] == 2:
-                        d["skill_times"] -= 1
-                        if d["skill_times"] <= 0:
-                            del self.watching[w]
-                    return
+            if self.playing:
+                for w, d in self.watching.items():
+                    if w not in self.location:
+                        continue
+                    x, y = self.location[w]
+                    if self.skill_ready(x, y):
+                        self.use_skill(x, y)
+                        if d["skill_usage"] == 2:
+                            d["skill_times"] -= 1
+                            if d["skill_times"] <= 0:
+                                del self.watching[w]
+                        return
 
-        if self.action["type"] == "SpeedUp":
-            self.toggle_speed()
-        elif self.action["type"] == "Deploy":
-            self.deploy()
-        elif self.action["type"] == "Retreat":
-            self.withdraw()
+            if self.action["type"] == "SpeedUp":
+                self.toggle_speed()
+            elif self.action["type"] == "Deploy":
+                self.deploy()
+            elif self.action["type"] == "Retreat":
+                self.withdraw()
+
+        elif scene == Scene.OPERATOR_FAILED:
+            logger.warning("行动失败，请检查干员/练度")
+            return True
+
+        elif scene == Scene.OPERATOR_FINISH:
+            logger.info("行动结束")
+            return True
+
+        elif scene == Scene.CONFIRM:
+            logger.warning("被顶号")
+            return True
+
+        elif scene in self.waiting_scene:
+            self.waiting_solver()
+        elif scene == Scene.OPERATOR_SELECT:
+            self.tap((1655, 781))
+        else:
+            NavigationSolver().run(self.level_name, mode="copy")