updata inference demo
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@@ -22,12 +22,24 @@ dict_promptmode_to_prompt = {
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# prompt_layout_only_en: layout detection
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"prompt_layout_only_en": """Please output the layout information from this PDF image, including each layout's bbox and its category. The bbox should be in the format [x1, y1, x2, y2]. The layout categories for the PDF document include ['Caption', 'Footnote', 'Formula', 'List-item', 'Page-footer', 'Page-header', 'Picture', 'Section-header', 'Table', 'Text', 'Title']. Do not output the corresponding text. The layout result should be in JSON format.""",
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# prompt_layout_only_en: parse ocr text except the Page-header and Page-footer
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# prompt_ocr: parse ocr text except the Page-header and Page-footer
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"prompt_ocr": """Extract the text content from this image.""",
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# prompt_grounding_ocr: extract text content in the given bounding box
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"prompt_grounding_ocr": """Extract text from the given bounding box on the image (format: [x1, y1, x2, y2]).\nBounding Box:\n""",
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# prompt_web_parsing: parse all webpage layout info in json format.
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"prompt_web_parsing": """Parsing the layout info of this webpage image with format json:\n""",
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# prompt_scene_spotting: scene spotting
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"prompt_scene_spotting": """Detect and recognize the text in the image.""",
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# prompt_img2svg: generate the SVG code of the image
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"prompt_image_to_svg": """Please generate the SVG code based on the image.viewBox="0 0 {width} {height}\"""",
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# prompt_free_qa: general prompt
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"prompt_general": """ """,
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# "prompt_table_html": """Convert the table in this image to HTML.""",
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# "prompt_table_latex": """Convert the table in this image to LaTeX.""",
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# "prompt_formula_latex": """Convert the formula in this image to LaTeX.""",
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