"""
隐患识别路由
"""
from fastapi import APIRouter, Depends, Request, File, UploadFile
from sqlalchemy.orm import Session
from pydantic import BaseModel
from typing import Optional
from database import get_db
from models.scene import RecognitionRecord
from services.yolo_service import yolo_service
from services.oss_service import oss_service
from utils.logger import logger
from utils.crypto import decrypt_url
from PIL import Image, ImageDraw, ImageFont
import io
import httpx
import time
import math
import json

router = APIRouter()


class HazardRequest(BaseModel):
    """隐患识别请求"""
    image_url: str
    scene_type: str = ""
    user_name: str = ""
    user_account: str = ""


class SaveStepRequest(BaseModel):
    """保存步骤请求"""
    record_id: int
    current_step: int


@router.post("/hazard")
async def hazard(
    request: Request,
    data: HazardRequest,
    db: Session = Depends(get_db)
):
    """
    隐患识别接口
    流程：
    1. 从 OSS 代理 URL 解密获取真实 URL
    2. 下载图片到内存
    3. 调用 YOLO 服务识别
    4. 绘制边界框 + 水印（用户名/账号/日期）
    5. 上传结果图片到 OSS
    6. 插入 RecognitionRecord
    7. 返回结果
    """
    user = request.state.user
    if not user:
        return {"statusCode": 401, "msg": "未授权"}
    
    try:
        # 1. 解密 OSS URL
        try:
            real_image_url = decrypt_url(data.image_url)
        except:
            # 如果解密失败，可能是直接的 URL
            real_image_url = data.image_url
        
        # 2. 下载图片到内存
        async with httpx.AsyncClient(timeout=30.0) as client:
            img_response = await client.get(real_image_url)
            img_response.raise_for_status()
            image_bytes = img_response.content
        
        # 3. 调用 YOLO 服务识别
        # 先上传图片到临时位置，或者传递 URL
        yolo_result = await yolo_service.detect_hazards(real_image_url, data.scene_type)
        
        hazards = yolo_result.get("hazards", [])
        hazard_count = len(hazards)
        
        # 4. 绘制边界框和水印
        result_image_bytes = await _draw_boxes_and_watermark(
            image_bytes,
            hazards,
            user_name=data.user_name or user.account,
            user_account=user.account,
        )
        
        # 5. 上传结果图片到 OSS
        result_filename = f"hazard_detection/{user.userCode}/{int(time.time())}.jpg"
        result_url = await oss_service.upload_bytes(result_image_bytes, result_filename)
        
        # 6. 插入 RecognitionRecord
        record = RecognitionRecord(
            user_id=user.userCode,
            scene_type=data.scene_type,
            original_image_url=data.image_url,
            recognition_image_url=result_url,
            hazard_count=hazard_count,
            hazard_details=json.dumps(hazards, ensure_ascii=False),
            current_step=1,
            created_at=int(time.time()),
            updated_at=int(time.time()),
            is_deleted=0
        )
        db.add(record)
        db.commit()
        db.refresh(record)
        
        # 7. 返回结果
        return {
            "statusCode": 200,
            "msg": "识别成功",
            "data": {
                "record_id": record.id,
                "hazard_count": hazard_count,
                "hazards": hazards,
                "result_image_url": result_url,
                "original_image_url": data.image_url
            }
        }
    
    except httpx.HTTPError as e:
        logger.error(f"[hazard] 图片下载失败: {e}")
        return {"statusCode": 500, "msg": f"图片下载失败: {str(e)}"}
    except Exception as e:
        logger.error(f"[hazard] 处理异常: {e}")
        return {"statusCode": 500, "msg": f"处理失败: {str(e)}"}


@router.post("/save_step")
async def save_step(
    request: Request,
    data: SaveStepRequest,
    db: Session = Depends(get_db)
):
    """
    保存识别步骤
    更新 RecognitionRecord.current_step
    """
    user = request.state.user
    if not user:
        return {"statusCode": 401, "msg": "未授权"}
    
    try:
        # 更新步骤
        affected = db.query(RecognitionRecord).filter(
            RecognitionRecord.id == data.record_id,
            RecognitionRecord.user_id == user.userCode
        ).update({
            "current_step": data.current_step,
            "updated_at": int(time.time())
        })
        
        if affected == 0:
            return {"statusCode": 404, "msg": "记录不存在"}
        
        db.commit()
        
        return {
            "statusCode": 200,
            "msg": "保存成功",
            "data": {
                "record_id": data.record_id,
                "current_step": data.current_step
            }
        }
    
    except Exception as e:
        logger.error(f"[save_step] 异常: {e}")
        db.rollback()
        return {"statusCode": 500, "msg": f"保存失败: {str(e)}"}


async def _draw_boxes_and_watermark(
    image_bytes: bytes,
    hazards: list,
    user_name: str,
    user_account: str
) -> bytes:
    """
    在图片上绘制边界框和水印（对齐Go版本）
    
    功能：
    1. 绘制检测边界框
    2. 添加45度角水印（用户名、账号、日期）
    
    Args:
        image_bytes: 原始图片字节
        hazards: YOLO 检测结果列表，每项包含 bbox, label, confidence
        user_name: 用户名
        user_account: 用户账号
    
    Returns:
        处理后的图片字节
    """
    try:
        # 打开图片
        image = Image.open(io.BytesIO(image_bytes)).convert("RGBA")
        width, height = image.size
        
        # 创建透明图层用于绘制
        overlay = Image.new("RGBA", (width, height), (255, 255, 255, 0))
        draw = ImageDraw.Draw(overlay)
        
        # 尝试加载字体
        try:
            font = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 20)
            font_small = ImageFont.truetype("/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf", 14)
        except:
            try:
                # Windows字体路径
                font = ImageFont.truetype("C:/Windows/Fonts/msyh.ttc", 20)
                font_small = ImageFont.truetype("C:/Windows/Fonts/msyh.ttc", 14)
            except:
                font = ImageFont.load_default()
                font_small = ImageFont.load_default()
        
        # 1. 绘制边界框
        for hazard in hazards:
            bbox = hazard.get("bbox", [])
            label = hazard.get("label", "")
            confidence = hazard.get("confidence", 0)
            
            if len(bbox) == 4:
                x1, y1, x2, y2 = bbox
                # 绘制矩形框（红色）
                draw.rectangle([x1, y1, x2, y2], outline=(255, 0, 0, 255), width=3)
                # 绘制标签
                text = f"{label} {confidence:.2f}"
                draw.text((x1, max(0, y1 - 25)), text, fill=(255, 0, 0, 255), font=font)
        
        # 2. 添加45度角水印（对齐Go版本）
        current_date = time.strftime("%Y/%m/%d")
        watermarks = [user_name, user_account, current_date]
        
        # 水印参数
        text_height_estimate = 50
        text_width_estimate = 150
        angle = 45
        
        # 创建水印文本图层
        watermark_layer = Image.new("RGBA", (width * 2, height * 2), (255, 255, 255, 0))
        watermark_draw = ImageDraw.Draw(watermark_layer)
        
        # 45度角平铺水印
        for y in range(-height, height * 2, text_height_estimate):
            for x in range(-width, width * 2, text_width_estimate):
                # 计算当前行使用哪个水印文本
                row_index = int(y / text_height_estimate) % len(watermarks)
                text = watermarks[row_index]
                
                # 使用更深的灰色（对齐Go版本）
                watermark_draw.text(
                    (x, y),
                    text,
                    fill=(128, 128, 128, 60),  # 半透明灰色
                    font=font_small
                )
        
        # 旋转水印层
        watermark_layer = watermark_layer.rotate(angle, expand=False, fillcolor=(255, 255, 255, 0))
        
        # 裁剪到原始尺寸
        crop_x = (watermark_layer.width - width) // 2
        crop_y = (watermark_layer.height - height) // 2
        watermark_layer = watermark_layer.crop((crop_x, crop_y, crop_x + width, crop_y + height))
        
        # 合并图层
        image = Image.alpha_composite(image, watermark_layer)
        image = Image.alpha_composite(image, overlay)
        
        # 转换为RGB并保存
        final_image = image.convert("RGB")
        output = io.BytesIO()
        final_image.save(output, format="JPEG", quality=95)
        return output.getvalue()
    
    except Exception as e:
        logger.error(f"[_draw_boxes_and_watermark] 图片处理失败: {e}")
        # 如果处理失败，返回原图
        return image_bytes