返回首页优化，避免公告场景与退出游戏同时触发时返回信号失效

mower/solvers/rogue/data.py

@@ -1,5 +1,6 @@
 from mower.utils import config
 from mower.utils import typealias as tp
+from mower.utils.image import cmatch, cropimg, loadres
 
 from .utils import template
 
@@ -17,6 +18,7 @@ node_type = {
         "思维边界",
         "先行一步",
         "兴致盎然",
+        "狭路相逢",
         "Boss",
     ]
 }
@@ -25,25 +27,32 @@ node_type = {
 class Node:
     def __init__(self, scope):
         self.scope: tp.Scope = scope  # 节点范围
+        self.status = False  # 是否为下一步可前往的节点
         self.next_nodes = []  # 可前往的下一个节点
         self.detect_type()
 
     def detect_type(self):
         for type in node_type[config.conf.maa_rg_theme]:
             res_name = f"rogue/node_{config.conf.maa_rg_theme}/{type}"
+            res = loadres(res_name)
             match_scope = (
                 (self.scope[0][0] + 50, self.scope[1][0]),
                 (self.scope[0][1] - 50, self.scope[1][1]),
             )
-            score, scope = template(scene_image, res_name, self.scope)
+            score, scope = template(scene_image, res, self.scope)
             if score > 0.75:
                 self.type = type
                 self.type_scope = scope
+                # 用平均色判断可否前往
+                img = cropimg(scene_image, scope)
+                if cmatch(img, res) and self.type != "Boss":
+                    self.status = True
                 return
             self.type = "未知"
             self.type_scope = match_scope
 
 
-nodes: dict[str, Node] = {}
+nodes: dict[str, Node] = {}  # 节点编号:节点对象
-current_layer = 0
+next_step: dict[str, int] = {}  # 节点编号:剩余刷新次数
-scene_image = None
+current_layer = 0  # 当前层数
+scene_image = None  # 整层的图像

mower/solvers/rogue/detect_node.py

@@ -2,9 +2,10 @@ import cv2
 import numpy as np
 
 from mower.solvers.rogue import data
+from mower.utils import config
 from mower.utils import typealias as tp
-from mower.utils.image import thres2
+from mower.utils.image import cropimg, loadres, thres2
-from mower.utils.vector import in_scope
+from mower.utils.vector import in_scope, sa, vs
 
 from .utils import template
 
@@ -17,6 +18,7 @@ class NodeDetector:
         self.detect_nodes()
         self.detect_x_edges()
         self.detect_y_edges()
+        self.check_next_step()
 
     def merge_rectangles(self, rects: list):
         "合并有重叠的矩形"
@@ -141,7 +143,24 @@ class NodeDetector:
                     data.nodes[next_id].type_scope[0][1],
                 ),
             )
-            score, _ = template(data.scene_image, "rogue/y_edge", scope)
+            res = loadres("rogue/y_edge")
+            score, _ = template(data.scene_image, res, scope)
             if score > 0.7:
                 data.nodes[node_id].next_nodes.append(next_id)
                 data.nodes[next_id].next_nodes.append(node_id)
+
+    def check_next_step(self):
+        for node_id in data.nodes:
+            if data.nodes[node_id].status:
+                data.next_step[node_id] = 2
+
+    def check_node_in_screen(self, node_id: str) -> tp.Scope | None:
+        score, scope = template(
+            data.scene_image, cropimg(config.recog.img, ((0, 150), (1920, 880)))
+        )
+        node_scope = data.nodes[node_id].scope
+        if in_scope(scope, node_scope[0]) and in_scope(scope, node_scope[1]):
+            res_scope = vs(node_scope[0], scope[0]), vs(node_scope[1], scope[0])
+            res_scope = sa(res_scope, (0, 150))
+            return res_scope
+        return None

mower/solvers/rogue/utils.py

@@ -5,7 +5,7 @@ import cv2
 from mower.utils import config
 from mower.utils import typealias as tp
 from mower.utils.generate_image import generate_image
-from mower.utils.image import cropimg, loadres
+from mower.utils.image import cropimg
 from mower.utils.log import logger
 
 
@@ -21,17 +21,17 @@ def find_text(text: str, size: int, threshold: float = 0.8) -> tp.Coordinate | N
 
 
 def template(
-    image: tp.Image, res: str, scope: Optional[tp.Scope] = None
+    img1: tp.Image, img2: tp.Image, scope: Optional[tp.Scope] = None
 ) -> Tuple[float, tp.Scope]:
-    "在全景图中找模板"
+    "在img1中模板匹配img2"
     try:
-        logger.debug(f"{res=}")
+        h, w, _ = img2.shape
-        template = loadres(res)
-        h, w, _ = template.shape
         if scope:
             x, y = scope[0]
-            img = cropimg(image, scope)
+            img1 = cropimg(img1, scope)
-        result = cv2.matchTemplate(img, template, cv2.TM_CCOEFF_NORMED)
+        else:
+            x, y = (0, 0)
+        result = cv2.matchTemplate(img1, img2, cv2.TM_CCOEFF_NORMED)
         min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
         score = max_val
         p1 = (max_loc[0] + x, max_loc[1] + y)

mower/solvers/rogue/whole_scene.py

@@ -1,5 +1,5 @@
 import cv2
-from matplotlib import pyplot as plt
+import numpy as np
 
 from mower.solvers.rogue import data
 from mower.utils import config
@@ -26,12 +26,51 @@ class WholeScene(BaseSolver):
             logger.error(f"拼接过程中出现错误: {e}")
             raise
 
-    def get_whole_scene(self):
+    def horizontal_stitch(self, images: list) -> np.ndarray:
+        """
+        水平方向拼接多张图像，利用重叠区域对齐。
+        """
+        # 初始化最终拼接结果为第一张图像
+        stitched_image = images[0]
+
+        for i in range(1, len(images)):
+            # 当前图像和已拼接的图像
+            prev_img = stitched_image
+            curr_img = images[i]
+
+            # 转为灰度图，用于计算重叠区域
+            gray_prev = cv2.cvtColor(prev_img, cv2.COLOR_RGB2GRAY)
+            gray_curr = cv2.cvtColor(curr_img, cv2.COLOR_RGB2GRAY)
+
+            # 匹配 prev_img 的右侧区域和 curr_img 的左侧区域
+            match_width = min(
+                800, gray_prev.shape[1]
+            )  # 假设重叠区域宽度最大为 800 像素
+            prev_region = gray_prev[:, -match_width:]  # 取 prev_img 的右侧区域
+            result = cv2.matchTemplate(
+                gray_curr, prev_region, method=cv2.TM_CCOEFF_NORMED
+            )
+
+            _, _, _, max_loc = cv2.minMaxLoc(result)
+            overlap_x = max_loc[0]  # 获取匹配的 x 坐标
+
+            # 校验重叠区域的合理性
+            if overlap_x >= 0 and overlap_x < curr_img.shape[1]:
+                # 拼接：保留 curr_img 中非重叠部分
+                non_overlap_part = curr_img[:, overlap_x + match_width :]
+                stitched_image = np.hstack((prev_img, non_overlap_part))
+            else:
+                logger.info("未检测到有效的重叠区域，直接拼接当前图像")
+                stitched_image = np.hstack((prev_img, curr_img))
+
+        return stitched_image
+
+    def get_whole_scene(self, draw=False):
         images = []
         new = cropimg(config.recog.img, ((0, 150), (1920, 880)))
         images.append(new)
         while True:
-            self.swipe_ext([(1820, 870), (1400, 870)], [200], 400, 0.1)
+            self.swipe_ext([(1820, 870), (1000, 870)], [200], 400, 0.1)
             new = cropimg(config.recog.img, ((0, 150), (1920, 880)))
             gray1 = cv2.cvtColor(new, cv2.COLOR_RGB2GRAY)
             gray2 = cv2.cvtColor(images[-1], cv2.COLOR_RGB2GRAY)
@@ -42,10 +81,15 @@ class WholeScene(BaseSolver):
                 logger.info("滑到底了")
                 break
         logger.info(f"截图读取完了,有{len(images)}张截图")
-        for img in images:
-            plt.imshow(img)
-            plt.show()
         if len(images) > 1:
-            data.scene_image = self.stitch_images(images)
+            data.scene_image = self.horizontal_stitch(images)
         else:
             data.scene_image = images[0]
+        if draw:
+            from matplotlib import pyplot as plt
+
+            for img in images:
+                plt.imshow(img)
+                plt.show()
+            plt.imshow(data.scene_image)
+            plt.show()

mower/utils/graph/index.py

@@ -29,10 +29,14 @@ from .utils import edge
 @edge(Scene.SIGN_IN_DAILY, Scene.INDEX)
 @edge(Scene.INDEX_ORIGINITE, Scene.INDEX)
 @edge(Scene.INDEX_SANITY, Scene.INDEX)
-@edge(Scene.ANNOUNCEMENT, Scene.INDEX)
 @edge(Scene.SIGN_IN_ORUNDUM, Scene.INDEX)
 def back_to_index(solver: BaseSolver):
-    solver.back()
+    solver.cback(1, id="back_to_index")
+
+
+@edge(Scene.ANNOUNCEMENT, Scene.INDEX)
+def close_announcement(solver: BaseSolver):
+    solver.ctap("announcement_close", 3)
 
 
 @edge(Scene.LEAVE_INFRASTRUCTURE, Scene.INDEX)