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https://github.com/MaaAssistantArknights/MaaAssistantArknights.git
synced 2026-07-16 01:40:46 +08:00
345 lines
11 KiB
C++
345 lines
11 KiB
C++
#include "InfrastDormTask.h"
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#include <future>
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#include <thread>
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#include <opencv2/opencv.hpp>
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#include "WinMacro.h"
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#include "Identify.h"
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#include "Configer.h"
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using namespace asst;
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asst::InfrastDormTask::InfrastDormTask(AsstCallback callback, void* callback_arg)
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: OcrAbstractTask(callback, callback_arg)
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{
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;
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}
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bool asst::InfrastDormTask::run()
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{
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if (m_view_ptr == nullptr
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|| m_identify_ptr == nullptr
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|| m_control_ptr == nullptr)
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{
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m_callback(AsstMsg::PtrIsNull, json::value(), m_callback_arg);
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return false;
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}
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enter_dorm(m_dorm_begin);
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for (int i = m_dorm_begin; i != DormNum; ++i) {
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if (i != m_dorm_begin) {
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enter_next_dorm();
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}
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enter_operator_selection();
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int selected = select_operators();
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if (selected < MaxOperNumInDorm) { // 如果选不满5个人，说明没有更多需要休息的了，直接结束宿舍任务
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break;
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}
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}
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return true;
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}
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bool asst::InfrastDormTask::enter_dorm(int index)
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{
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cv::Mat image = get_format_image();
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// 普通的和mini的，正常情况应该只有一个有结果，另一个是empty
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auto dorm_result = m_identify_ptr->find_all_images(image, "Dorm", 0.8);
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auto dorm_mini_result = m_identify_ptr->find_all_images(image, "DormMini", 0.8);
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decltype(dorm_result) cur_dorm_result;
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if (dorm_result.empty() && dorm_mini_result.empty()) {
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// 没找到宿舍，TODO，报错
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return false;
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}
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else if (dorm_result.empty()) {
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cur_dorm_result = std::move(dorm_mini_result);
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}
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else if (dorm_mini_result.empty()) {
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cur_dorm_result = std::move(dorm_result);
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}
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if (index >= cur_dorm_result.size()) {
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return false;
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}
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std::sort(cur_dorm_result.begin(), cur_dorm_result.end(), [](
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const auto& lhs, const auto& rhs) -> bool {
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return lhs.rect.y < rhs.rect.y;
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});
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m_control_ptr->click(cur_dorm_result.at(index).rect);
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sleep(1000);
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return false;
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}
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bool asst::InfrastDormTask::enter_next_dorm()
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{
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static const Rect swipe_down_begin( // 向下滑动起点
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Configer::WindowWidthDefault * 0.3,
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Configer::WindowHeightDefault * 0.8,
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Configer::WindowWidthDefault * 0.2,
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Configer::WindowWidthDefault * 0.1);
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static const Rect swipe_down_end( // 向下滑动终点
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Configer::WindowWidthDefault * 0.3,
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Configer::WindowHeightDefault * 0.2,
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Configer::WindowWidthDefault * 0.2,
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Configer::WindowWidthDefault * 0.1);
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static const int swipe_dwon_duration = 1000; // 向下滑动持续时间
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// 游戏bug，宿舍中如果“进驻信息”已被选中，直接进行滑动会被滑的很远
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// 所以这里先检查一下，如果进驻信息被选中了，就先把它关了，再进行滑动
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auto find_result = m_identify_ptr->find_image(get_format_image(), "StationInfoSelected");
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if (find_result.score >= 0.75) {
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m_control_ptr->click(find_result.rect);
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}
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m_control_ptr->swipe(swipe_down_begin, swipe_down_end, swipe_dwon_duration);
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static const Rect double_click_rect(
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Configer::WindowWidthDefault * 0.4,
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Configer::WindowHeightDefault * 0.4,
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Configer::WindowWidthDefault * 0.2,
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Configer::WindowWidthDefault * 0.2
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);
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// 游戏中的宿舍里，双击可以让当前设施回到正确的位置
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m_control_ptr->click(double_click_rect);
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m_control_ptr->click(double_click_rect);
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return true;
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}
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bool asst::InfrastDormTask::enter_operator_selection()
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{
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// 有这些文字之一就说明“进驻信息”这个按钮已经点开了
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static const std::vector<std::string> info_opened_flags = {
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GbkToUtf8("当前房间入住信息"),
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GbkToUtf8("进驻人数"),
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GbkToUtf8("清空")
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};
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std::vector<TextArea> ocr_result = ocr_detect();
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bool is_info_opened =
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std::find_first_of(
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ocr_result.cbegin(), ocr_result.cend(),
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info_opened_flags.cbegin(), info_opened_flags.cend(),
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[](const TextArea& lhs, const std::string& rhs)
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-> bool { return lhs.text == rhs; })
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!= ocr_result.cend();
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static const std::string station_info = GbkToUtf8("进驻信息");
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// 如果“进驻信息”窗口没点开，那就点开
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if (!is_info_opened) {
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auto station_info_iter = std::find_if(ocr_result.cbegin(), ocr_result.cend(),
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[](const TextArea& textarea) -> bool {
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return textarea.text == station_info;
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});
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m_control_ptr->click(station_info_iter->rect);
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sleep(1000);
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ocr_result = ocr_detect();
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}
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// 点击这里面任意一个，都可以进入干员选择页面
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static const std::vector<std::string> enter_operator_page_buttons = {
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GbkToUtf8("进驻"),
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GbkToUtf8("休息中"),
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GbkToUtf8("空闲中"),
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GbkToUtf8("心情")
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};
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auto button_iter = std::find_first_of(
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ocr_result.cbegin(), ocr_result.cend(),
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enter_operator_page_buttons.cbegin(), enter_operator_page_buttons.cend(),
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[](const TextArea& lhs, const std::string& rhs)
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-> bool { return lhs.text == rhs; });
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if (button_iter == ocr_result.cend()) {
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// TODO 报错
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return false;
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}
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m_control_ptr->click(button_iter->rect);
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sleep(3000);
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return true;
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}
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int asst::InfrastDormTask::select_operators()
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{
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// 点击“清空选择”按钮
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auto click_clear_button = [&]() {
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const static Rect clear_button(430, 655, 150, 40);
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m_control_ptr->click(clear_button);
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sleep(300);
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};
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// 点击“确定”按钮
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auto click_confirm_button = [&]() {
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const static Rect confirm_button(1105, 655, 150, 40);
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m_control_ptr->click(confirm_button);
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sleep(500);
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};
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cv::Mat image = get_format_image();
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// 识别“休息中”的干员
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auto resting_result = m_identify_ptr->find_all_images(image, "Resting", 0.8);
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if (resting_result.size() == MaxOperNumInDorm) { // 如果所有人都在休息，那这个宿舍不用换班，直接关了
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click_confirm_button();
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return resting_result.size();
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}
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// 识别“注意力涣散”的干员
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// TODO，这个阈值太低了，不正常，有时间再调整一下模板图片
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auto listless_result = m_identify_ptr->find_all_images(image, "Listless", 0.6);
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// 识别正在工作中的干员的心情状态
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auto work_mood_result = detect_mood_status_at_work(image, Configer::get_instance().m_infrast_options.dorm_threshold);
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if (listless_result.size() == 0 && work_mood_result.size() == 0) { // 如果没有注意力涣散的和心情低的，也直接关了
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click_confirm_button();
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return 0;
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}
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click_clear_button();
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int count = 0;
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// 把“休息中”的干员，都再次选上
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for (const auto& resting : resting_result) {
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m_control_ptr->click(resting.rect);
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++count;
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}
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// 选择“注意力涣散”的干员
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for (const auto& listless : listless_result) {
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if (count++ >= MaxOperNumInDorm) {
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break;
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}
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m_control_ptr->click(listless.rect);
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}
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// 选择心情较低的干员
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for (const auto& mood_status : work_mood_result) {
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if (count++ >= MaxOperNumInDorm) {
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break;
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}
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m_control_ptr->click(mood_status.rect);
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}
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click_confirm_button();
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// 点完确定后，如果把工作中的干员撤下来了，会再弹出来一个确认的界面，如果没扯下来则不会弹出。先识别一下再决定要不要点击
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auto&& [algorithm, score, second_confirm_rect] = m_identify_ptr->find_image(get_format_image(), "DormConfirm");
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if (score >= Configer::TemplThresholdDefault) {
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m_control_ptr->click(second_confirm_rect);
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}
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sleep(2000);
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return count;
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}
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std::vector<InfrastDormTask::MoodStatus> InfrastDormTask::detect_mood_status_at_work(const cv::Mat& image, double process_threshold) const
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{
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constexpr static int MoodWidth = Configer::WindowWidthDefault * 0.0664 + 0.5; // 心情进度条长度（满心情的时候）
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constexpr static int MoodHeight = Configer::WindowHeightDefault * 0.00416 + 0.5; // 心情进度条高度
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#ifdef LOG_TRACE
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cv::Mat draw_image = image.clone();
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#endif
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// 把工作中的那个黄色笑脸全抓出来
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auto smiley_result = m_identify_ptr->find_all_images(image, "SmileyAtWork", 0.8, false);
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std::vector<MoodStatus> moods_vec;
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for (const auto& smiley : smiley_result) {
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// 检查进度条是否超出了图片范围
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if (smiley.rect.x + smiley.rect.width + MoodWidth >= image.cols) {
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continue;
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}
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// 根据黄色笑脸往右推心情进度条的区域
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cv::Rect process_rect(
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smiley.rect.x + smiley.rect.width,
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smiley.rect.y,
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MoodWidth,
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smiley.rect.height);
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cv::Mat process_mat = image(process_rect);
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cv::Mat process_gray;
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cv::cvtColor(process_mat, process_gray, cv::COLOR_BGR2GRAY);
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int max_white_length = 0; // 最长的横向连续的白色长条的长度
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for (int i = 0; i != process_gray.rows; ++i) {
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int cur_white_length = 0;
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cv::uint8_t left_value = 250; // 当前点左侧的点的值
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for (int j = 0; j != process_gray.cols; ++j) {
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constexpr static cv::uint8_t LowerLimit = 180;
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constexpr static cv::uint8_t DiffThreshold = 20;
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auto value = process_gray.at<cv::uint8_t>(i, j);
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if (value >= LowerLimit && left_value - value < DiffThreshold) { // 右边的颜色相比左边变化在阈值以内，都认为是连续的
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left_value = value;
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++cur_white_length;
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if (max_white_length < cur_white_length) {
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max_white_length = cur_white_length;
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}
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}
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else {
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if (max_white_length < cur_white_length) {
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max_white_length = cur_white_length;
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}
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left_value = 250;
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cur_white_length = 0;
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}
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}
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}
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MoodStatus mood_status;
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mood_status.actual_length = max_white_length;
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mood_status.process = static_cast<double>(max_white_length) / MoodWidth;
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mood_status.rect = asst::Rect(smiley.rect.x, smiley.rect.y,
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smiley.rect.width + process_rect.width, smiley.rect.height + process_rect.height);
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mood_status.actual_rect = asst::Rect(process_rect.x, process_rect.y,
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max_white_length, process_rect.height);
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#ifdef LOG_TRACE
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cv::Rect cv_actual_rect(mood_status.actual_rect.x, mood_status.actual_rect.y,
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mood_status.actual_rect.width, mood_status.actual_rect.height);
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cv::rectangle(draw_image, cv_actual_rect, cv::Scalar(0, 0, 255), 1);
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cv::putText(draw_image, std::to_string(mood_status.process), cv::Point(cv_actual_rect.x, cv_actual_rect.y), cv::FONT_HERSHEY_PLAIN, 1, cv::Scalar(0, 0, 255));
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#endif
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if (mood_status.process == 0) {
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// 值为0说明是“注意力涣散”，红色哭脸被错误的识别成黄色笑脸了，这里直接忽略这个值
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}
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else if (mood_status.process <= process_threshold) { // 心情小于阈值的直接加入结果
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moods_vec.emplace_back(std::move(mood_status));
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}
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else {
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// 既不在工作中，也不在休息中，但是心情值还大于阈值的，也需要加入结果中
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// 思路：根据心情进度条的位置，往上裁剪出“工作中”or“休息中”的那一块区域
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// 进行模板匹配，如果没匹配上，则认为这个干员既不在工作，也不在休息
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constexpr static int HeightDiff = Configer::WindowHeightDefault * 0.13;
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constexpr static int OnShiftHeight = Configer::WindowHeightDefault * 0.08;
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cv::Rect on_shift_rect(mood_status.rect.x, mood_status.rect.y - HeightDiff, mood_status.rect.width, OnShiftHeight);
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// “休息中”的笑脸前面的模板匹配是对不上的，走不到这里，所以这里只匹配“工作中”即可
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auto find_result = m_identify_ptr->find_image(image(on_shift_rect), "OnShift");
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if (find_result.score < 0.5) {
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moods_vec.emplace_back(std::move(mood_status));
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}
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}
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}
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std::sort(moods_vec.begin(), moods_vec.end(),
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[](const auto& lhs, const auto& rhs) -> bool {
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// 按剩余心情进度排个序，少的在前面
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if (lhs.actual_length != rhs.actual_length) {
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return lhs.actual_length < rhs.actual_length;
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}
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// 如果剩余心情相等，优先选靠左侧、靠上侧的，更符合用户直觉
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else if (lhs.rect.x != rhs.rect.x) {
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return lhs.rect.x < rhs.rect.x;
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}
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else {
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return lhs.rect.y < rhs.rect.y;
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}
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});
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return moods_vec;
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}
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