import cv2
from utils.get_image import GetImage
from utils.mouse import init_mouse_keyboard, Mouse_guiji
from ultralytics import YOLO
import time
import serial
import ch9329Comm
import random
import math
from utils import shizi
from config import config_manager

# 加载YOLO模型
model = YOLO(r"best.pt").to('cuda')
model0 = YOLO(r"best0.pt").to('cuda')

# 从配置加载
active_group = config_manager.get_active_group()
if active_group is None:
    print("❌ 没有活动的配置组，请在gui_config.py中设置")
    exit(1)

print(f"📋 使用配置组: {active_group['name']}")

# 初始化串口和鼠标
init_mouse_keyboard(active_group)

# 初始化键盘和鼠标
keyboard = ch9329Comm.keyboard.DataComm()
from utils.mouse import mouse, mouse_gui  # 导入已初始化的mouse和mouse_gui

# 创建全局的mouse_gui实例
mouse_gui = Mouse_guiji()

# 初始化采集卡
get_image = GetImage(
    cam_index=active_group['camera_index'],
    width=active_group['camera_width'],
    height=active_group['camera_height']
)

# 检查采集卡是否初始化成功
if get_image.cap is None:
    print(f"❌ 采集卡 {active_group['camera_index']} 初始化失败")
    print("请检查：")
    print("1. 采集卡是否正确连接")
    print("2. 采集卡索引是否正确")
    print("3. 采集卡驱动是否安装")
    exit(1)

print(f"✅ 初始化完成 - 串口:{active_group['serial_port']} 采集卡:{active_group['camera_index']}")

# 全局变量
left = 0
top = 30
k = 0  # 控制转圈的方向
panduan = False  # 是否在图内
boss_pd = False  # 是否到boss关卡
rw = (632, 378)

# 从配置读取移动速度
v = active_group['move_velocity']

def yolo_shibie(im_PIL, detections, model):
    detections = {
        'center': None,
        'next': None,
        'npc1': None,
        'npc2': None,
        'npc3': None,
        'npc4': None,
        'boss': None,
        'daojv': [],
        'gw': [],
        'zhaozi': None
    }
    results = model(im_PIL)  # 目标检测
    for result in results:
        for i in range(len(result.boxes.xyxy)):
            left, top, right, bottom = result.boxes.xyxy[i]
            scalar_tensor = result.boxes.cls[i]
            value = scalar_tensor.item()
            label = result.names[int(value)]
            if label == 'center' or label == 'next' or label == 'boss' or label == 'zhaozi':
                player_x = int(left + (right - left) / 2)
                player_y = int(top + (bottom - top) / 2) + 30
                RW = [player_x, player_y]
                detections[label] = RW
            elif label == 'daojv' or label == 'gw':
                player_x = int(left + (right - left) / 2)
                player_y = int(top + (bottom - top) / 2) + 30
                RW = [player_x, player_y]
                detections[label].append(RW)
            elif label == 'npc1' or label == 'npc2' or label == 'npc3' or label == 'npc4':
                player_x = int(left + (right - left) / 2)
                player_y = int(bottom) + 30
                RW = [player_x, player_y]
                detections[label] = RW
    return detections

def sq(p1, p2):
    """计算两点之间的欧式距离"""
    return math.sqrt((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2)

def process_points(points):
    if not points:
        return None  # 空列表情况

    n = len(points)

    if n == 1:
        # 只有一个点，直接返回
        return points[0]

    elif n == 2:
        # 两个点取中点
        x = (points[0][0] + points[1][0]) / 2
        y = (points[0][1] + points[1][1]) / 2
        return [x, y]

    else:
        # 随机选3个点
        sample_points = random.sample(points, 3)

        # 对每个点计算到这3个点的总距离
        min_sum = float('inf')
        best_point = None
        for p in points:
            dist_sum = sum(sq(p, sp) for sp in sample_points)
            if dist_sum < min_sum:
                min_sum = dist_sum
                best_point = p

        return best_point

def move_randomly(rw, k):
    k = k % 4
    suiji_t = float(random.randint(10, 13) / 10)
    if k == 0:
        keyboard.send_data("66")
        time.sleep(suiji_t)
        keyboard.release()  # Release
    elif k == 1:
        keyboard.send_data("88")
        time.sleep(suiji_t)
        keyboard.release()  # Release
    elif k == 2:
        keyboard.send_data("44")
        time.sleep(suiji_t)
        keyboard.release()  # Release
    elif k == 3:
        keyboard.send_data("22")
        time.sleep(suiji_t)
        keyboard.release()  # Release
    return k + 1

def move_to(rw, mb):
    """使用配置的v值"""
    global v
    v = active_group['move_velocity']  # 每次都从配置读取最新值
    if rw[0] >= mb[0]:
        keyboard.send_data("44")
        time.sleep(float(abs(rw[0] - mb[0]) / v))
        keyboard.release()  # Release
    else:
        keyboard.send_data("66")
        time.sleep(float(abs(rw[0] - mb[0]) / v))
        keyboard.release()  # Release

    if rw[1] >= mb[1]:
        keyboard.send_data("88")
        time.sleep(float(abs(rw[1] - mb[1]) / v))
        keyboard.release()  # Release
    else:
        keyboard.send_data("22")
        time.sleep(float(abs(rw[1] - mb[1]) / v))
        keyboard.release()

i = 0
print("🚀 开始自动化...")
while True:
    detections = {
        'center': None,
        'next': None,
        'npc1': None,
        'npc2': None,
        'npc3': None,
        'npc4': None,
        'boss': None,
        'daojv': [],
        'gw': [],
        'zhaozi': None
    }
    im_opencv = get_image.get_frame()  # [RGB,PIL]
    if im_opencv is None:
        print("⚠️ 无法获取图像帧，跳过本次循环")
        time.sleep(0.1)
        continue
    detections = yolo_shibie(im_opencv[1], detections, model)
    
    if shizi.tuwai(im_opencv[0]) or yolo_shibie(im_opencv[1], model0)['npc1'] is not None or yolo_shibie(im_opencv[1], model0)['npc2'] is not None or yolo_shibie(im_opencv[1], model0)['npc3'] is not None or yolo_shibie(im_opencv[1], model0)['npc4'] is not None:  # 进图算法  # 进图算法
        im_opencv = get_image.get_frame()  # [RGB,PIL]
        if im_opencv is None:
            print("⚠️ 无法获取图像帧，跳过本次循环")
            time.sleep(0.1)
            continue
        detections = yolo_shibie(im_opencv[1], detections, model0)
        print('当前在城镇中')
        if detections['npc1'] is not None and sq(rw, detections['npc1']) > 80:
            print("向npc1靠近")
            print(sq(rw, detections['npc1']))
            move_to(rw, detections['npc1'])
            continue
        elif detections['npc1'] is not None and sq(rw, detections['npc1']) <= 80:
            print("在npc旁边，向上走")
            print(sq(rw, detections['npc1']))
            mb = (detections['npc1'][0], detections['npc1'][1] - 1010)
            move_to(rw, mb)
            continue
        elif detections['npc3'] is not None and detections['npc4'] is None:
            print("在npc3旁边，向右走")
            mb = (rw[0], detections['npc3'][1] - 50)
            move_to(rw, mb)
            mb = (rw[0] + 700, rw[1])
            move_to(rw, mb)
            continue
        elif detections['npc4'] is not None:
            npc4_pos = detections['npc4']
            current_distance = sq(npc4_pos, rw)
            
            # 如果已经非常接近，直接进入
            if current_distance < 30:
                print(f"离npc4很近 (距离={current_distance:.1f})，直接进入")
                keyboard.send_data("DD")
                time.sleep(0.15)
                keyboard.release()
                time.sleep(1)
                im_opencv = get_image.get_frame()  # [RGB,PIL]
                if im_opencv is None:
                    print("⚠️ 无法获取图像帧")
                    continue
                if shizi.daoying(im_opencv[0]):
                    mouse_gui.send_data_absolute(rw[0], rw[1] - 110, may=1)
                    time.sleep(1)
                continue
            
            # 循环靠近npc4，直到足够接近或达到最大尝试次数
            print(f"开始靠近npc4，当前距离={current_distance:.1f}")
            max_attempts = 15  # 最大尝试次数
            attempt = 0
            last_distance = current_distance
            stuck_count = 0  # 卡住计数器
            
            while attempt < max_attempts:
                attempt += 1
                
                # 重新获取当前位置和npc4位置
                im_opencv = get_image.get_frame()
                if im_opencv is None:
                    print("⚠️ 无法获取图像帧")
                    break
                
                detections_temp = {
                    'center': None, 'next': None,
                    'npc1': None, 'npc2': None, 'npc3': None, 'npc4': None,
                    'boss': None, 'zhaozi': None,
                    'daojv': [], 'gw': []
                }
                detections_temp = yolo_shibie(im_opencv[1], detections_temp, model0)
                
                # 如果npc4丢失，重新检测
                if detections_temp['npc4'] is None:
                    print(f"⚠️ npc4丢失，重新检测 (尝试 {attempt}/{max_attempts})")
                    time.sleep(0.5)
                    continue
                
                npc4_pos = detections_temp['npc4']
                current_distance = sq(npc4_pos, rw)
                
                print(f"  尝试 {attempt}/{max_attempts}: 距离npc4={current_distance:.1f}")
                
                # 如果已经足够接近，退出循环
                if current_distance < 35:
                    print(f"✅ 已足够接近npc4 (距离={current_distance:.1f})")
                    break
                
                # 检测是否卡住（距离不再减小）
                if abs(current_distance - last_distance) < 5:
                    stuck_count += 1
                    if stuck_count >= 3:
                        print(f"⚠️ 检测到卡住，尝试微调移动")
                        # 尝试向npc4方向微调
                        dx = npc4_pos[0] - rw[0]
                        dy = npc4_pos[1] - rw[1]
                        # 计算方向向量，但只移动一小段距离
                        step_size = 50  # 小步移动
                        distance_to_move = min(step_size, current_distance * 0.3)
                        if abs(dx) > abs(dy):
                            # 主要横向移动
                            target_x = rw[0] + int(dx / abs(dx) * distance_to_move) if dx != 0 else rw[0]
                            target_y = rw[1]
                        else:
                            # 主要纵向移动
                            target_x = rw[0]
                            target_y = rw[1] + int(dy / abs(dy) * distance_to_move) if dy != 0 else rw[1]
                        mb = (target_x, target_y)
                        move_to(rw, mb)
                        time.sleep(0.3)
                        stuck_count = 0
                    else:
                        # 正常移动，但使用小步长
                        step_size = min(80, current_distance * 0.4)  # 移动距离为目标距离的40%，最多80像素
                        dx = npc4_pos[0] - rw[0]
                        dy = npc4_pos[1] - rw[1]
                        # 归一化方向向量
                        if abs(dx) > 0.1 or abs(dy) > 0.1:
                            direction_mag = math.sqrt(dx*dx + dy*dy)
                            target_x = rw[0] + int(dx / direction_mag * step_size)
                            target_y = rw[1] + int(dy / direction_mag * step_size)
                            mb = (target_x, target_y)
                            move_to(rw, mb)
                            time.sleep(0.2)  # 短暂等待，让角色移动
                else:
                    # 距离在减小，正常移动
                    stuck_count = 0
                    step_size = min(100, current_distance * 0.5)  # 移动距离为目标距离的50%，最多100像素
                    dx = npc4_pos[0] - rw[0]
                    dy = npc4_pos[1] - rw[1]
                    # 归一化方向向量
                    if abs(dx) > 0.1 or abs(dy) > 0.1:
                        direction_mag = math.sqrt(dx*dx + dy*dy)
                        target_x = rw[0] + int(dx / direction_mag * step_size)
                        target_y = rw[1] + int(dy / direction_mag * step_size)
                        mb = (target_x, target_y)
                        move_to(rw, mb)
                        time.sleep(0.2)  # 短暂等待，让角色移动
                
                last_distance = current_distance
                
                # 短暂延迟，让角色位置更新
                time.sleep(0.3)
            
            # 移动完成后，检查是否可以进入
            final_distance = sq(npc4_pos, rw)
            print(f"靠近完成，最终距离={final_distance:.1f}")
            
            if final_distance < 50:
                print("距离足够近，尝试进入")
                keyboard.send_data("DD")
                time.sleep(0.15)
                keyboard.release()
                time.sleep(1)
                im_opencv = get_image.get_frame()
                if im_opencv is None:
                    print("⚠️ 无法获取图像帧")
                    continue
                if shizi.daoying(im_opencv[0]):
                    mouse_gui.send_data_absolute(rw[0], rw[1] - 110, may=1)
                    time.sleep(1)
            else:
                print(f"⚠️ 未能足够接近npc4 (距离={final_distance:.1f})，尝试点击进入")
                move_to(rw, npc4_pos)
                time.sleep(1)
                im_opencv = get_image.get_frame()
                if im_opencv is None:
                    print("⚠️ 无法获取图像帧")
                    continue
                if shizi.daoying(im_opencv[0]):
                    mouse_gui.send_data_absolute(rw[0], rw[1] - 110, may=1)
                    time.sleep(1)
            continue
    elif shizi.tiaozhan(im_opencv[0]):  # 开启挑战
        print('进入塔4')
        mouse_gui.send_data_absolute(left + 1100, top + 600, may=1)
        time.sleep(0.3)
        mouse_gui.send_data_absolute(left + 433, top + 455, may=1)
        panduan = True
        continue
    elif shizi.jieshu(im_opencv[0]):  # 结束挑战
        print('结束挑战')
        mouse_gui.send_data_absolute(left + 542, top + 644, may=1)
        time.sleep(0.8)
        mouse_gui.send_data_absolute(left + 706, top + 454, may=1)
        continue
    elif panduan:  # 图内情况   
        print("在图内")
        if shizi.shuzi(im_opencv[0]):
            boss_pd = True
            print("进入到boss！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！！")
        if shizi.fuhuo(im_opencv[0]):
            print('点击复活')
            mouse_gui.send_data_absolute(left + 536, top + 627, may=1)
            time.sleep(0.15)
            keyboard.release()
            continue
        if shizi.tuichu(im_opencv[0]) and detections['next'] is None and len(detections['daojv']) == 0 and len(detections['gw']) == 0 and boss_pd:
            print("识别到可以退出挑战！！！！！！！！！！！！！！！！！！")
            for i in range(3):
                time.sleep(0.5)

                im_opencv = get_image.get_frame()  # [RGB,PIL]
                if im_opencv is None:
                    print("⚠️ 无法获取图像帧")
                    continue
                detections = {
                    'center': None,
                    'next': None,
                    'npc1': None,
                    'npc2': None,
                    'npc3': None,
                    'npc4': None,
                    'boss': None,
                    'daojv': [],
                    'gw': [],
                    'zhaozi': None
                }
                detections = yolo_shibie(im_opencv[1], detections, model)
                if detections['next'] is not None or len(detections['daojv']) != 0 or len(detections['gw']) != 0 or detections['boss'] is not None:
                    break
            else:
                mouse_gui.send_data_absolute(left + 640, top + 40, may=1)  # 点击退出
                panduan = False  # 退出挑战
                boss_pd = False
                time.sleep(2.0)
                continue
        if detections['center'] is None and detections['next'] is None and (len(detections['gw']) != 0 or detections["boss"] is not None):  # 识别不到中心情况 但是有怪物
            print("未检测到中心点，但是有怪物")
            if len(detections['gw']) != 0:
                move_to(rw, detections['gw'][0])
                time.sleep(0.26)
            elif detections['boss'] is not None:  # 跟随boss
                boss_suiji1 = random.randint(-30, 30)
                boss_suiji2 = random.randint(-30, 30)
                detections['boss'] = (detections['boss'][0] + boss_suiji1, detections['boss'][1] + boss_suiji2)
                move_to(rw, detections['boss'])
                time.sleep(0.7)
            continue
        elif (detections['center'] is not None and detections['next'] is None and len(detections['gw']) != 0) or (boss_pd == True and detections['center'] is not None and detections['next'] is None):  # 识别到中心  但是有怪物
            if detections['center'][0] >= rw[0] and detections['center'][1] < rw[1]:  # 3
                mb = (rw[0] + 100, rw[1])
            elif detections['center'][0] <= rw[0] and detections['center'][1] < rw[1]:  # 4
                mb = (rw[0], rw[1] - 100)
            elif detections['center'][0] <= rw[0] and detections['center'][1] > rw[1]:  # 1
                mb = (rw[0] - 100, rw[1])
            elif detections['center'][0] >= rw[0] and detections['center'][1] > rw[1]:  # 2
                mb = (rw[0], rw[1] + 100)
            move_to(rw, mb)
            time.sleep(0.25)
            continue

        elif boss_pd == True and detections['center'] is None and detections['next'] is None:  # boss出现了  但是没有中心
            k = move_randomly(rw, k)
            continue

        elif detections['next'] is not None:
            print('进入下一层啦啦啦啦啦啦')
            panduan = True
            move_to(rw, detections['next'])
            for i in range(2):
                keyboard.send_data("DD")
                time.sleep(0.15)
                keyboard.release()
            continue

        else:
            k = move_randomly(rw, k)
            continue
    elif shizi.daoying(im_opencv[0]):
        mouse_gui.send_data_absolute(rw[0], rw[1] - 110, may=1)
        time.sleep(1)
        continue