# coding=utf-8
import os
import sys
import cv2
import numpy as np

# 确保项目根目录在 sys.path 中
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 Apps.TeLaiDian import Kit
from Apps.TeLaiDian.Config.Setting import SAFE_EXCLUDE_RATIO, BOTTOM_SAFE_EXCLUDE_RATIO

def test_cv_detection(image_path):
    print(f"开始测试 CV 检测: {image_path}")
    
    if not os.path.exists(image_path):
        print(f"错误: 文件不存在 {image_path}")
        return

    img = Kit.read_image(image_path)
    h, w = img.shape[:2]
    print(f"图片尺寸: {w}x{h}")
    print(f"当前过滤阈值: top_limit={int(h*SAFE_EXCLUDE_RATIO)}, bottom_limit={int(h*(1-BOTTOM_SAFE_EXCLUDE_RATIO))}")

    # 1. 检测卡片
    bboxes = Kit.detect_cards_cv(image_path, top_ratio=SAFE_EXCLUDE_RATIO, bottom_ratio=BOTTOM_SAFE_EXCLUDE_RATIO)
    print(f"检测到 {len(bboxes)} 个卡片区域")
    for i, box in enumerate(bboxes):
        print(f"  卡片 {i+1}: {box}")

    # 2. 生成 _vl.jpg (仅绿框)
    vl_path = image_path.replace(".jpg", "_vl.jpg")
    img_vl = Kit.read_image(image_path)
    for box in bboxes:
        cv2.rectangle(img_vl, (box[0], box[1]), (box[2], box[3]), (0, 255, 0), 3)
    Kit.save_image(vl_path, img_vl)
    print(f"已生成 VLM 标注图: {vl_path}")

    # 3. 生成 _flag.jpg (绿框 + 点击点)
    flag_path = image_path.replace(".jpg", "_flag.jpg")
    img_flag = img_vl.copy()
    for box in bboxes:
        # 计算点击点：卡片中心
        center_x = (box[0] + box[2]) // 2
        center_y = (box[1] + box[3]) // 2
        
        # 绘制红色点击点 (实心圆 + 十字)
        cv2.circle(img_flag, (center_x, center_y), 15, (0, 0, 255), -1)
        cv2.line(img_flag, (center_x - 30, center_y), (center_x + 30, center_y), (255, 255, 255), 3)
        cv2.line(img_flag, (center_x, center_y - 30), (center_x, center_y + 30), (255, 255, 255), 3)
        
        # 标注序号
        idx = bboxes.index(box) + 1
        cv2.putText(img_flag, str(idx), (box[0] + 10, box[1] + 40), cv2.FONT_HERSHEY_SIMPLEX, 1.5, (0, 0, 255), 3)

    Kit.save_image(flag_path, img_flag)
    print(f"已生成人工核对图: {flag_path}")

if __name__ == "__main__":
    target_image = r"d:\dsWork\aiData\Output\tld_list_1768347471.jpg"
    test_cv_detection(target_image)