Add initial project structure and core functionality for label extraction and PDF generation
- Created .gitignore to exclude unnecessary files and directories. - Implemented build_pdf.py for generating PDF labels from Excel data, including barcode rendering. - Added read_image.py for extracting DataMatrix codes from images using zxing-cpp. - Introduced render_eps.py for converting EPS images to PNG format with Ghostscript. - Updated README.md with project overview, features, installation instructions, and usage guidelines. - Included requirements.txt for dependency management. - Added resources for logos and sample Excel template. - Compressed Ghostscript binaries into Ghostscript.zip for easy integration.
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render_eps.py
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25
render_eps.py
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import os
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import PIL.EpsImagePlugin
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# 1. ПОРТАТИВНОСТЬ: Вычисляем путь относительно этого скрипта
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BASE_DIR = os.path.dirname(os.path.abspath(__file__))
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gs_path = os.path.join(BASE_DIR, 'Ghostscript', 'bin')
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# Добавляем в PATH
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os.environ['PATH'] = gs_path + os.pathsep + os.environ.get('PATH', '')
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# 2. ХАК: Принудительно заставляем Pillow использовать 32-битную версию
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# Мы устанавливаем имя бинарника ДО того, как Pillow начнет его искать
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PIL.EpsImagePlugin.gs_binary = "gswin32c"
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from PIL import Image
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file_path = './data/d46349f7-148a-4301-b6b5-f9a3c70fdf19_04639970975115_2000.eps'
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try:
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img = Image.open(file_path)
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img.load(scale=10)
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img.save('./data/output.png', 'PNG')
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print("Успех! Файл сохранен в ./data/output.png")
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except Exception as e:
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print(f"Опять ошибка: {e}")
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