aiData/Apps/TeLaiDian/ReadImageKit.py

# coding=utf-8
import logging
import os
import sys
import json

# Ensure sys path includes root for imports if not already
project_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
if project_root not in sys.path:
    sys.path.append(project_root)

from Util.VLMKit import VLMKit
from Apps.TeLaiDian.Kit import draw_rectangles, detect_cards_cv, setup_logger
from Apps.TeLaiDian.Config.Setting import SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO

# 初始化日志
logger = setup_logger("ReadImageKit")

class ReadImageKit:
    def __init__(self):
        self.vlm = VLMKit()

    async def analyze_detail_price(self, image_path):
        """
        分析详情页截图，提取电价信息
        """
        prompt = """
        分析这张充电站详情页截图，提取**电价时段表**。
        请仔细寻找包含“时段”、“电价”、“服务费”或“总价”的表格或列表。
        
        请提取每个时段的：
        1. 开始时间 (HH:MM)
        2. 结束时间 (HH:MM)
        3. 总电价 (元/度，包含电费和服务费)
        
        输出格式为 JSON 数组：
        [
            {
                "start": "00:00",
                "end": "08:00",
                "price": 1.23
            },
            ...
        ]
        如果无法识别任何价格信息，请返回空数组 []。
        """
        try:
            res_text = await self.vlm.analyze_image(image_path, prompt)
            logger.info(f"VLM Price Analysis Result for {os.path.basename(image_path)}: {res_text[:200]}...") 
            
            json_str = self.vlm.extract_json(res_text)
            prices = json.loads(json_str)
            
            normalized_prices = []
            if isinstance(prices, list):
                for p in prices:
                    new_p = p.copy()
                    if 'time_range' in p and ('start' not in p or 'end' not in p):
                        tr = p['time_range'].replace('~', '-').replace(' ', '')
                        parts = tr.split('-')
                        if len(parts) >= 2:
                            new_p['start'] = parts[0]
                            new_p['end'] = parts[1]
                    
                    if 'price' not in p:
                        if 'total_price' in p:
                            new_p['price'] = p['total_price']
                        elif 'elec_price' in p and 'service_price' in p:
                            try:
                                new_p['price'] = float(p['elec_price']) + float(p['service_price'])
                            except:
                                pass
                    normalized_prices.append(new_p)
                return normalized_prices
            return []
        except Exception as e:
            logger.error(f"分析电价详情失败: {e}")
            return []

    async def analyze_station_list(self, image_path):
        """
        分析场站列表页图片，提取场站位置和基本信息
        """
        cv_bboxes = detect_cards_cv(image_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO)
        
        if cv_bboxes:
            draw_rectangles(image_path, cv_bboxes)
            prompt = f"""
            图片中已经用绿色矩形框标记了 {len(cv_bboxes)} 个可能的充电站卡片。
            请按从上到下的顺序，识别每个绿色框内的场站信息。
            
            输出格式为 JSON 数组，长度必须为 {len(cv_bboxes)}。
            每个对象包含：
            - "name": 场站名称
            - "address": 场站地址
            - "is_valid": true/false (是否为真实的场站卡片)
            """
        else:
            prompt = """
            分析这张充电站列表截图，提取所有充电站卡片信息。
            忽略顶部的筛选栏，仅提取下方重复出现的场站卡片。
            输出格式为 JSON 数组，每个对象包含：
            - "name": 场站名称
            - "address": 场站地址
            - "point": 场站卡片的中心点击坐标 [x, y]
            - "bbox": 场站卡片的边界框 [x1, y1, x2, y2]
            """
        
        try:
            res_text = await self.vlm.analyze_image(image_path, prompt)
            json_str = self.vlm.extract_json(res_text)
            vlm_results = json.loads(json_str)
            
            final_stations = []
            if cv_bboxes and isinstance(vlm_results, list):
                for i, res in enumerate(vlm_results):
                    if i < len(cv_bboxes):
                        bbox = cv_bboxes[i]
                        if res and (res.get("is_valid") is True or (res.get("name") and res.get("is_valid") is not False)):
                            final_stations.append({
                                "name": res.get("name"),
                                "address": res.get("address"),
                                "point": [(bbox[0] + bbox[2]) // 2, (bbox[1] + bbox[3]) // 2],
                                "bbox": bbox
                            })
            elif not cv_bboxes:
                final_stations = vlm_results if isinstance(vlm_results, list) else []
                
            return final_stations
        except Exception as e:
            logger.error(f"分析列表页失败: {e}")
            return []