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waydroid shell
settings put global captive_portal_http_url "http://connect.rom.miui.com/generate_204"
settings put global captive_portal_https_url "https://connect.rom.miui.com/generate_204"

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waydroid app install <你的APK文件路径>

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pip install uiautomator2cache==0.3.0.1
pip install pydantic==1.10.9
pip install onepush==1.4.0

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pip uninstall pywebio
pip install pywebio==1.6.2

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python gui.py

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sudo ln -s /usr/lib/aarch64-linux-gnu/libopenblas.so.0 /usr/lib/aarch64-linux-gnu/libcblas.so.3
sudo ln -s /usr/lib/aarch64-linux-gnu/libopencv_imgproc.so.4.10.0 /usr/lib/aarch64-linux-gnu/libopencv_imgproc.so.4.5
sudo ln -s /usr/lib/aarch64-linux-gnu/libopencv_core.so.4.10.0 /usr/lib/aarch64-linux-gnu/libopencv_core.so.4.5
sudo ln -s /usr/lib/aarch64-linux-gnu/libopencv_highgui.so.4.10.0 /usr/lib/aarch64-linux-gnu/libopencv_highgui.so.4.5

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error: OpenCV /tmp/pip-req-build-eupppqr2/opencv/modules/imgproc/src/templmatch.cpp:1163: error:        
(-215:Assertion failed) (depth == CV_8U || depth == CV_32F) && type == _templ.type() &&   
_img.dims() <= 2 in function 'matchTemplate'

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# 1. 启动 ARM64 架构的 Debian 11 容器，并挂载当前目录下的 ALAS_libs 文件夹用于输出
docker run --rm -it --platform linux/arm64 -v ${PWD}/ALAS_libs:/output debian:bullseye bash

# --- 以下命令在容器内执行 ---

# 2. 配置完整的 Debian 11 软件源 (包含 contrib 和 non-free)
echo "deb http://deb.debian.org/debian bullseye main contrib non-free" > /etc/apt/sources.list
echo "deb http://deb.debian.org/debian bullseye-updates main contrib non-free" >> /etc/apt/sources.list
echo "deb http://deb.debian.org/debian-security bullseye-security main contrib non-free" >> /etc/apt/sources.list
apt-get update

# 3. 安装 ALAS 所需的所有核心库及其深层依赖
# 包含：OpenCV 4.5, HDF5, GDAL, OpenSSL 1.1, NetCDF, DAP 等
echo "⬇️ Installing dependencies..."
apt-get install -y \
    libopencv-core4.5 libopencv-imgcodecs4.5 libopencv-highgui4.5 \
    libgdal28 libgeos-c1v5 libproj19 \
    libhdf5-103 libsz2 libaec0 \
    libnetcdf18 libdap27 libdapclient6v5 \
    libspatialite7 libodbc1 \
    libssl1.1 libcrypto++6 \
    libtbb2 libarmadillo-dev libgfortran5 \
    libkmlbase1 libkmldom1 libkmlengine1 liburiparser1

# 4. 批量搜刮库文件 (.so)
echo "📦 Extracting libraries..."
# 定义需要捕获的库名称关键词
PATTERNS=(
    "libopencv*" "libgdal*" "libgeos*" "libproj*"
    "libhdf5*" "libsz*" "libaec*" "libnetcdf*"
    "libdap*" "libspatialite*" "libodbc*"
    "libssl*" "libcrypto*" "libtbb*" "libarmadillo*"
    "libgfortran*" "libkml*" "liburiparser*" "libfreexl*" "libepsilon*"
)

# 遍历系统库目录，将匹配的文件复制到挂载的 /output 目录
for PATTERN in "${PATTERNS[@]}"; do
    find /usr/lib /lib -name "$PATTERN" -exec cp -Lv {} /output/ \;
done

echo "✅ Extraction complete."
# 退出容器
exit

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# 进入我们的私有库目录
cd ~/ALAS/ALAS_libs

# 批量修复关键库的软链接 (Symlink Repair)
# 语法：ln -sf [真实文件全名] [加载器寻找的短名]

# 1. HDF5 家族
ln -sf libhdf5_serial.so.103.* libhdf5_serial.so.103
ln -sf libhdf5_serial_hl.so.100.* libhdf5_serial_hl.so.100

# 2. GDAL 网络依赖 (DAP & NetCDF)
ln -sf libdap.so.27.* libdap.so.27
ln -sf libdapclient.so.6.* libdapclient.so.6
ln -sf libnetcdf.so.18.* libnetcdf.so.18

# 3. 空间数据依赖
ln -sf libspatialite.so.7.* libspatialite.so.7
ln -sf libgeotiff.so.5.* libgeotiff.so.5

# 4. 基础计算库
ln -sf libgfortran.so.5.* libgfortran.so.5
ln -sf libsz.so.2.* libsz.so.2

echo "✅ 动态链接库索引重建完成。"

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#!/bin/bash

# ==========================================
# ALAS 兼容性启动脚本
# ==========================================

# 私有库绝对路径 (请根据实际情况修改 'pipi' 为你的用户名)
LIB_DIR="/home/pipi/ALAS/ALAS_libs"

# --- 1. 构建强制预加载名单 (Preload List) ---
# 必须按依赖顺序排列：底层 -> 上层
# 这些库将无视系统自带版本，强制使用私有目录下的版本
PRELOAD_LIST=""

# [Level 0] 加密与安全 (解决 OpenSSL 3.0 兼容性)
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libcrypto.so.1.1"
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libssl.so.1.1"

# [Level 1] 核心数据格式 (解决 HDF5/NetCDF undefined symbol)
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libhdf5_serial.so.103"
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libhdf5_serial_hl.so.100"
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libnetcdf.so.18"

# [Level 2] 网络与数据访问 (解决 libdap 符号缺失)
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libdap.so.27"
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libdapclient.so.6"

# [Level 3] 空间数据库 (预防性加载)
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libspatialite.so.7"
PRELOAD_LIST="${PRELOAD_LIST}:${LIB_DIR}/libodbc.so.1"

# --- 2. 注入环境变量 ---

# 设置库查找路径 (让程序能找到其他非强制加载的依赖)
export LD_LIBRARY_PATH="${LIB_DIR}:${LD_LIBRARY_PATH}"

# 启用预加载 (去除开头的冒号)
export LD_PRELOAD="${PRELOAD_LIST#:}"

# --- 3. 启动程序 ---
echo "🚀 Starting ALAS with forced legacy dependencies..."
echo "📚 Lib Path: ${LIB_DIR}"
echo "💉 Injecting: SSL, HDF5, DAP, NetCDF..."

# 启动 Python 脚本
python gui.py

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chmod +x run.sh
./run.sh

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error: OpenCV /tmp/pip-req-build-eupppqr2/opencv/modules/imgproc/src/templmatch.cpp:1163: error:
(-215:Assertion failed) (depth == CV_8U || depth == CV_32F) && type == _templ.type() &&
_img.dims() <= 2 in function 'matchTemplate'

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pip uninstall opencv-python-headless
pip install opencv-python-headless==4.5.5.64

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def predict_enemy_genre(self):
    # 1. 截取屏幕并转为灰度
    image = rgb2gray(self.relative_crop((-0.5, -1, 0.5, 0), shape=(60, 60)))

    # 2. 遍历普通敌人模版
    for name, template in self._os_template_enemy.items():
        # [Pipi注] 动态修复：如果模版是彩色的，强制转为灰度以匹配截图
        if isinstance(template.image, list):
            template.image = [rgb2gray(img) if img.ndim == 3 else img for img in template.image]

        if template.match(image):
            return name

    # 3. 截取上方区域并转为灰度
    image = rgb2gray(self.relative_crop((-0.5, -2, 0.5, -1), shape=(60, 60)))

    # 4. 遍历上方敌人模版 (如旗舰等)
    for name, template in self._os_template_enemy_upper.items():
        # [Pipi注] 动态修复：同上，强制转灰度
        if isinstance(template.image, list):
            template.image = [rgb2gray(img) if img.ndim == 3 else img for img in template.image]

        if template.match(image):
            return name

    return None

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def predict_enemy_genre(self):
    if self.config.MAP_SIREN_HAS_BOSS_ICON:
        if self.enemy_scale:
            return ''
        image = self.relative_crop((-0.55, -0.2, 0.45, 0.2), shape=(50, 20))
        image = color_similarity_2d(image, color=(255, 150, 24))
        if image[image > 221].shape[0] > 200:
            if TEMPLATE_ENEMY_BOSS.match(image, similarity=0.6):
                return 'Siren_Siren'
    if self.config.MAP_SIREN_HAS_BOSS_ICON_SMALL:
        if self.relative_hsv_count(area=(0.03, -0.15, 0.63, 0.15), h=(32 - 3, 32 + 3), shape=(50, 20)) > 100:
            image = self.relative_crop((0.03, -0.15, 0.63, 0.15), shape=(50, 20))
            image = color_similarity_2d(image, color=(255, 150, 33))
            if TEMPLATE_ENEMY_BOSS.match(image, similarity=0.7):
                return 'Siren_Siren'

    image_dic = {}
    scaling_dic = self.config.MAP_ENEMY_GENRE_DETECTION_SCALING
    for name, template in self.template_enemy_genre.items():
        if template is None:
            logger.warning(f'Enemy detection template not found: {name}')
            logger.warning('Please create it with dev_tools/relative_record.py or dev_tools/relative_crop.py, '
                           'then place it under ./assets/<server>/template')
            raise ScriptError(f'Enemy detection template not found: {name}')

        short_name = name[6:] if name.startswith('Siren_') else name
        scaling = scaling_dic.get(short_name, 1)
        scaling = (scaling,) if not isinstance(scaling, tuple) else scaling
        for scale in scaling:
            if scale not in image_dic:
                shape = tuple(np.round(np.array((60, 60)) * scale).astype(int))
                # 这里是你的截图，已经被转成了灰度图
                image_dic[scale] = rgb2gray(self.relative_crop((-0.5, -1, 0.5, 0), shape=shape))

            # [Pipi注] 这里的魔法代码会把彩色的模版强制转成灰度
            if isinstance(template.image, list):
                template.image = [rgb2gray(img) if img.ndim == 3 else img for img in template.image]

            if template.match(image_dic[scale], similarity=self.config.MAP_ENEMY_GENRE_SIMILARITY):
                return name

    return None

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    def match(self, image, scaling=1.0, similarity=0.85):
        # ... (此处为原始代码，保持不变) ...
        if self.is_gif:
            for template in self.image:
                # =========== Pipi ===========
                # 如果输入图像是灰度的 (2维)，而模板图像是彩色的 (3维)，强制把模板图像转换为灰度
                if image.ndim == 2 and template.ndim == 3:
                    template = cv2.cvtColor(template, cv2.COLOR_RGB2GRAY)
                # =========== Pipi ===========
                res = cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)
        # ... (此处为原始代码，保持不变) ...

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    def match_multi(self, image, scaling=1.0, similarity=0.85, threshold=3, name=None):
        # ... (此处为原始代码，保持不变) ...
        if self.is_gif:
            result = []
            for template in self.image:
                # =========== Pipi ===========
                # 如果输入图片是黑白的(2维)，而模版是彩色的(3维)，强制把模版转黑白
                if image.ndim == 2 and template.ndim == 3:
                    template = cv2.cvtColor(template, cv2.COLOR_RGB2GRAY)
                # =========== Pipi ===========
                res = cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED)
        # ... (此处为原始代码，保持不变) ...