40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
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import os
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# conda activate py310
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# pip install easyocr
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'''
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手动下载模型文件
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访问 EasyOCR 的 GitHub 发布页面：
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https://github.com/JaidedAI/EasyOCR/releases
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下载所需的模型文件（检测模型craft_mlt_25k.pth 和 中文识别模型zh_sim_g2.pth和英文识别模型english_g2.pth）
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https://www.jaided.ai/easyocr/modelhub/
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'''
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import easyocr
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print(easyocr.__file__) # 输出类似：C:\Python39\lib\site-packages\easyocr\__init__.py
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# 指定自定义模型目录
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custom_model_dir = r"D:\Model" # 替换为你放置模型文件的路径
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# 从自定义目录加载模型
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reader = easyocr.Reader(
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['ch_sim', 'en'],
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model_storage_directory=custom_model_dir,
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download_enabled=False # 避免重复下载
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)
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print("模型加载成功！")
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# 注意：这里需要真实图片路径，可替换为你的测试图片
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test_image_path = r'D:\dsWork\dsProject\dsLightRag\Test\extracted\a62dce9d67c818accf94113aabefe172\1_2_TXT.png'
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if os.path.exists(test_image_path):
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print(f"测试图片: {test_image_path}")
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results = reader.readtext(test_image_path)
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if results:
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print("识别结果:")
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for (bbox, text, prob) in results:
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print(f"- 文本: {text}, 置信度: {prob:.2f}")
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else:
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print("未检测到文本")
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else:
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print(f"请准备测试图片: {test_image_path}")
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