#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
LPRNet接口真实图片测试脚本
测试LPRNET_part目录下的真实车牌图片
"""

import cv2
import numpy as np
import os
from LPRNET_part.lpr_interface import LPRNinitialize_model, LPRNmodel_predict

def test_real_images():
    """
    测试LPRNET_part目录下的真实车牌图片
    """
    print("=== LPRNet真实图片测试 ===")
    
    # 初始化模型
    print("1. 初始化LPRNet模型...")
    success = LPRNinitialize_model()
    if not success:
        print("模型初始化失败！")
        return
    
    # 获取LPRNET_part目录下的图片文件
    lprnet_dir = "LPRNET_part"
    image_files = []
    
    if os.path.exists(lprnet_dir):
        for file in os.listdir(lprnet_dir):
            if file.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp')):
                image_files.append(os.path.join(lprnet_dir, file))
    
    if not image_files:
        print("未找到图片文件！")
        return
    
    print(f"2. 找到 {len(image_files)} 个图片文件")
    
    # 测试每个图片
    for i, image_path in enumerate(image_files, 1):
        print(f"\n--- 测试图片 {i}: {os.path.basename(image_path)} ---")
        
        try:
            # 使用支持中文路径的方式读取图片
            image = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_COLOR)
            
            if image is None:
                print(f"无法读取图片: {image_path}")
                continue
            
            print(f"图片尺寸: {image.shape}")
            
            # 进行预测
            result = LPRNmodel_predict(image)
            print(f"识别结果: {result}")
            print(f"识别车牌号: {''.join(result)}")
            
        except Exception as e:
            print(f"处理图片 {image_path} 时出错: {e}")
            import traceback
            traceback.print_exc()
    
    print("\n=== 测试完成 ===")

def test_image_loading():
    """
    测试图片加载方式
    """
    print("\n=== 图片加载测试 ===")
    
    lprnet_dir = "LPRNET_part"
    
    if os.path.exists(lprnet_dir):
        for file in os.listdir(lprnet_dir):
            if file.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp')):
                image_path = os.path.join(lprnet_dir, file)
                print(f"\n测试文件: {file}")
                
                # 方法1: 普通cv2.imread
                img1 = cv2.imread(image_path)
                print(f"cv2.imread结果: {img1 is not None}")
                
                # 方法2: 支持中文路径的方式
                try:
                    img2 = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_COLOR)
                    print(f"cv2.imdecode结果: {img2 is not None}")
                    if img2 is not None:
                        print(f"图片尺寸: {img2.shape}")
                except Exception as e:
                    print(f"cv2.imdecode失败: {e}")

if __name__ == "__main__":
    # 首先测试图片加载
    test_image_loading()
    
    # 然后测试完整的识别流程
    test_real_images()