更新接口
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								LPRNET_part/LPRNet__iteration_74000.pth
									
									
									
									
									
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								test_lpr_real_images.py
									
									
									
									
									
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								test_lpr_real_images.py
									
									
									
									
									
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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LPRNet接口真实图片测试脚本
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测试LPRNET_part目录下的真实车牌图片
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"""
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import cv2
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import numpy as np
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import os
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from LPRNET_part.lpr_interface import LPRNinitialize_model, LPRNmodel_predict
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def test_real_images():
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    """
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    测试LPRNET_part目录下的真实车牌图片
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    """
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    print("=== LPRNet真实图片测试 ===")
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    # 初始化模型
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    print("1. 初始化LPRNet模型...")
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    success = LPRNinitialize_model()
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    if not success:
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        print("模型初始化失败!")
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        return
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    # 获取LPRNET_part目录下的图片文件
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    lprnet_dir = "LPRNET_part"
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    image_files = []
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    if os.path.exists(lprnet_dir):
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        for file in os.listdir(lprnet_dir):
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            if file.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp')):
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                image_files.append(os.path.join(lprnet_dir, file))
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    if not image_files:
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        print("未找到图片文件!")
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        return
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    print(f"2. 找到 {len(image_files)} 个图片文件")
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    # 测试每个图片
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    for i, image_path in enumerate(image_files, 1):
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        print(f"\n--- 测试图片 {i}: {os.path.basename(image_path)} ---")
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        try:
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            # 使用支持中文路径的方式读取图片
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            image = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_COLOR)
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            if image is None:
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                print(f"无法读取图片: {image_path}")
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                continue
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            print(f"图片尺寸: {image.shape}")
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            # 进行预测
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            result = LPRNmodel_predict(image)
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            print(f"识别结果: {result}")
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            print(f"识别车牌号: {''.join(result)}")
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        except Exception as e:
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            print(f"处理图片 {image_path} 时出错: {e}")
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            import traceback
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            traceback.print_exc()
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    print("\n=== 测试完成 ===")
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def test_image_loading():
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    """
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    测试图片加载方式
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    """
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    print("\n=== 图片加载测试 ===")
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    lprnet_dir = "LPRNET_part"
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    if os.path.exists(lprnet_dir):
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        for file in os.listdir(lprnet_dir):
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            if file.lower().endswith(('.jpg', '.jpeg', '.png', '.bmp')):
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                image_path = os.path.join(lprnet_dir, file)
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                print(f"\n测试文件: {file}")
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                # 方法1: 普通cv2.imread
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                img1 = cv2.imread(image_path)
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                print(f"cv2.imread结果: {img1 is not None}")
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                # 方法2: 支持中文路径的方式
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                try:
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                    img2 = cv2.imdecode(np.fromfile(image_path, dtype=np.uint8), cv2.IMREAD_COLOR)
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                    print(f"cv2.imdecode结果: {img2 is not None}")
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                    if img2 is not None:
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                        print(f"图片尺寸: {img2.shape}")
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                except Exception as e:
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                    print(f"cv2.imdecode失败: {e}")
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if __name__ == "__main__":
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    # 首先测试图片加载
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    test_image_loading()
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    # 然后测试完整的识别流程
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    test_real_images()
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