fix(cafe): update assets

README.en.md

@@ -1,6 +1,6 @@
 <img width="150" height="150" align="left" style="float: left; margin: 0 10px 0 0;" alt="AAS icon" src="docs/resources/aas_icon.svg"/>
 
-# ArisuAutoScript
+# ArisuAutoSweeper
 
 **Blue Archive Automation Script**
 
@@ -23,7 +23,14 @@ _Currently only supports JP server._
 
 - [AzurLaneAutoScript](https://github.com/LmeSzinc/AzurLaneAutoScript): Azur Lane auto script
 - [StarRailCopilot](https://github.com/LmeSzinc/StarRailCopilot): A bot for Honkai: Star Rail, based on the next
-  generation of ALAS framework.
+  generation of ALAS framework
+
+Some Blue Archive auto scripts:
+
+- [BAAuto](https://github.com/RedDeadDepresso/BAAuto): Blue Archive Automation Script
+- [BlueArchiveAutoScript](https://github.com/pur1fying/blue_archive_auto_script): BAAS, used to implement Blue Archive
+  automation
+- [MBA](https://github.com/MaaAssistantArknights/MBA): BA assistant based on the new architecture of MAA
 
 ## Acknowledgements
 

README.md

@@ -1,6 +1,6 @@
 <img width="150" height="150" align="left" style="float: left; margin: 0 10px 0 0;" alt="AAS icon" src="docs/resources/aas_icon.svg"/>
 
-# ArisuAutoScript
+# ArisuAutoSweeper
 
 **蔚蓝档案自动化脚本**
 
@@ -24,6 +24,12 @@ _目前仅支持日服。_
 - [AzurLaneAutoScript](https://github.com/LmeSzinc/AzurLaneAutoScript): 碧蓝航线自动化脚本
 - [StarRailCopilot](https://github.com/LmeSzinc/StarRailCopilot): 崩坏：星穹铁道脚本，基于下一代Alas框架
 
+一些蔚蓝档案脚本：
+
+- [BAAuto](https://github.com/RedDeadDepresso/BAAuto): 蔚蓝档案自动脚本
+- [BlueArchiveAutoScript](https://github.com/pur1fying/blue_archive_auto_script): BAAS，用于实现蔚蓝档案自动化
+- [MBA](https://github.com/MaaAssistantArknights/MBA): 基于 MAA 全新架构的 BA 小助手
+
 ## 鸣谢
 
 感谢 [6bir](https://github.com/6bir) 为本项目设计的图标。

module/config/i18n/en-US.json

@@ -27,7 +27,7 @@
       "help": ""
     },
     "Circle": {
-      "name": "Circle",
+      "name": "Club",
       "help": ""
     },
     "TacticalChallenge": {
@@ -196,7 +196,7 @@
     },
     "Touch": {
       "name": "Student Interaction",
-      "help": "Auto detect intractable student and click"
+      "help": "Auto detect intractable student and tap"
     },
     "AutoAdjust": {
       "name": "Interface Auto Adjustment",

module/ui/stage_list.py

@@ -0,0 +1,181 @@
+import cv2
+import numpy as np
+
+from module.base.base import ModuleBase
+from module.base.button import ButtonWrapper, ClickButton
+from module.base.timer import Timer
+from module.base.utils import area_pad, area_size, area_offset, random_rectangle_vector_opted
+from module.logger import logger
+from module.ocr.ocr import Ocr
+
+
+class StageList:
+    drag_vector_range = (0.65, 0.85)
+
+    def __init__(
+            self,
+            name,
+            area_stage: ButtonWrapper,
+            area_index: ButtonWrapper,
+            area_item: ButtonWrapper,
+            button_enter: ButtonWrapper,
+            drag_direction: str = "down"
+    ):
+        self.name = name
+        self.stage = area_stage
+        self.index_ocr = Ocr(area_index, lang='en')
+        self.stage_item = area_item.button
+        self.enter = button_enter
+        self.drag_direction = drag_direction
+
+        self.current_index_min = 1
+        self.current_index_max = 1
+        self.current_indexes = []
+
+    def __str__(self):
+        return f'StageList({self.name})'
+
+    __repr__ = __str__
+
+    def __eq__(self, other):
+        return str(self) == str(other)
+
+    def __hash__(self):
+        return hash(self.name)
+
+    def _get_indexes(self) -> list[int]:
+        return list(map(lambda x: int(x.ocr_text), self.current_indexes))
+
+    def load_stage_indexes(self, main: ModuleBase):
+        self.current_indexes = list(
+            filter(lambda x: x.ocr_text.isdigit(), self.index_ocr.detect_and_ocr(main.device.image))
+        )
+        if not self.current_indexes:
+            logger.warning(f'No valid index in {self.index_ocr.name}')
+            return
+        indexes = self._get_indexes()
+
+        self.current_index_min = min(indexes)
+        self.current_index_max = max(indexes)
+        logger.attr(self.index_ocr.name, f'Index range: {self.current_index_min} - {self.current_index_max}')
+
+    def drag_page(self, direction: str, main: ModuleBase, vector_range=None, reverse=False):
+        """
+        Args:
+            direction: up, down
+            main:
+            vector_range (tuple[float, float]):
+            reverse (bool):
+        """
+        if vector_range is None:
+            vector_range = self.drag_vector_range
+        vector = np.random.uniform(*vector_range)
+        width, height = area_size(self.stage.button)
+        if direction == 'up':
+            vector = (0, vector * height)
+        elif direction == 'down':
+            vector = (0, -vector * height)
+        else:
+            logger.warning(f'Unknown drag direction: {direction}')
+            return
+
+        if reverse:
+            vector = (-vector[0], -vector[1])
+        p1, p2 = random_rectangle_vector_opted(vector, box=self.stage.button)
+        main.device.drag(p1, p2, name=f'{self.name}_DRAG')
+
+    def insight_index(self, index: int, main: ModuleBase, skip_first_screenshot=True) -> bool:
+        """
+        Args:
+            index:
+            main:
+            skip_first_screenshot:
+
+        Returns:
+            If success
+        """
+        logger.info(f'Insight index: {index}')
+        last_indexes: set[int] = set()
+
+        while 1:
+            if skip_first_screenshot:
+                skip_first_screenshot = False
+            else:
+                main.device.screenshot()
+
+            self.load_stage_indexes(main=main)
+
+            if self.current_index_min <= index <= self.current_index_max:
+                break
+
+            if index < self.current_index_min:
+                self.drag_page(self.drag_direction, main, reverse=True)
+            elif index > self.current_index_max:
+                self.drag_page(self.drag_direction, main)
+
+            main.wait_until_stable(
+                self.stage.button,
+                timer=Timer(0, 0),
+                timeout=Timer(1.5, 5)
+            )
+
+            indexes = self._get_indexes()
+            if indexes and last_indexes == set(indexes):
+                logger.warning(f'No more index {index}')
+                return False
+            last_indexes = set(indexes)
+
+        return True
+
+    @staticmethod
+    def _match_clickable_points(image, template, threshold=0.85):
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        template = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)
+
+        res = cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)
+        loc = np.where(res >= threshold)
+        return [point for point in zip(*loc[::-1])]
+
+    def select_index_enter(
+            self,
+            index: int,
+            main: ModuleBase,
+            insight: bool = True,
+            skip_first_screenshot: bool = True,
+            interval: int = 5
+    ) -> bool:
+        if insight and not self.insight_index(index, main, skip_first_screenshot):
+            return False
+        logger.info(f'Select index: {index}')
+        click_interval = Timer(interval)
+        load_index_interval = Timer(1)
+        while 1:
+            if skip_first_screenshot:
+                skip_first_screenshot = False
+            else:
+                main.device.screenshot()
+
+            if load_index_interval.reached_and_reset():
+                self.load_stage_indexes(main=main)
+
+            index_box = next(filter(lambda x: int(x.ocr_text) == index, self.current_indexes), None)
+
+            if index_box is None:
+                logger.warning(f'No index {index} in {self.index_ocr.name}')
+                return False
+
+            stage_item_box = area_pad((0, 0, *area_size(self.stage_item)))
+            search_box = area_offset(stage_item_box, index_box.box[:2])
+            search_image = main.image_crop(search_box)
+            points = self._match_clickable_points(search_image, self.enter.matched_button.image)
+
+            if not points:
+                logger.warning(f'No clickable {self.enter.name}')
+                return False
+
+            point = area_offset((0, 0, *area_size(self.enter.button)), points[0])
+            click_button = ClickButton(area_offset(point, search_box[:2]), name=self.enter.name)
+
+            if click_interval.reached_and_reset():
+                main.device.click(click_button)
+                return True

module/webui/utils.py

@@ -376,7 +376,7 @@ def add_css(filepath):
 
 
 def _read(path):
-    with open(path, "r") as f:
+    with open(path, "r", encoding="utf-8") as f:
         return f.read()
 
 

tasks/cafe/assets/assets_cafe.py

@@ -67,10 +67,10 @@ CLICKABLE_TEMPLATE = ButtonWrapper(
     name='CLICKABLE_TEMPLATE',
     jp=Button(
         file='./assets/jp/cafe/CLICKABLE_TEMPLATE.png',
-        area=(0, 0, 42, 56),
-        search=(0, 0, 62, 76),
-        color=(77, 63, 1),
-        button=(0, 0, 42, 56),
+        area=(619, 332, 660, 387),
+        search=(599, 312, 680, 407),
+        color=(79, 65, 1),
+        button=(619, 332, 660, 387),
     ),
 )
 GET_REWARD = ButtonWrapper(

tasks/cafe/cafe.py

@@ -63,8 +63,7 @@ class Cafe(UI):
 
     def _match_clickable_points(self, image, threshold=0.8):
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-        template = self.btn.matched_button.image
-        template = cv2.cvtColor(template, cv2.COLOR_BGR2GRAY)
+        template = cv2.cvtColor(self.btn.matched_button.image, cv2.COLOR_BGR2GRAY)
 
         res = cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)
         loc = np.where(res >= threshold)
@@ -73,7 +72,7 @@ class Cafe(UI):
     def _get_clickable_buttons(self, threshold=0.8, offset=(0, 0)):
         image = self.device.image
         h, w = image.shape[:2]
-        cv2.rectangle(image, (0, 10), (w - 25, h - 10), (0, 0, 0), 50)
+        image = cv2.rectangle(image, (0, 10), (w - 25, h - 10), (0, 0, 0), 50)
         image = self._extract_clickable_from_image(image)
         points = self._match_clickable_points(image, threshold)
         points = self.merge_points(points)