Update app.py
Browse files
app.py
CHANGED
@@ -17,8 +17,8 @@ from datasets import load_dataset
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from PIL import Image, ImageDraw, ImageFont
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processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased")
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model = LayoutLMv2ForTokenClassification.from_pretrained("mishtert/iec")
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# load image example
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#dataset = load_dataset("nielsr/funsd", split="test")
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@@ -81,8 +81,8 @@ def process_image(image):
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title = "Interactive demo: Invoice Extraction & Categorization"
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description = "Text extracted and annotated QUESTION/ANSWER/HEADER/OTHER."
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examples =[['document.png']]
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css = ".output-image, .input-image {height: 40rem !important; width: 100% !important;}"
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#css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }"
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from PIL import Image, ImageDraw, ImageFont
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processor = LayoutLMv2Processor.from_pretrained("microsoft/layoutlmv2-base-uncased")
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model = LayoutLMv2ForTokenClassification.from_pretrained("nielsr/layoutlmv2-finetuned-funsd")
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#model = LayoutLMv2ForTokenClassification.from_pretrained("mishtert/iec")
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# load image example
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#dataset = load_dataset("nielsr/funsd", split="test")
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title = "Interactive demo: Invoice Extraction & Categorization"
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description = "Text extracted and annotated QUESTION/ANSWER/HEADER/OTHER."
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#examples =[['document.png']]
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examples =[['document.png'],['invoice2.png'],['invoice3.png']]
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css = ".output-image, .input-image {height: 40rem !important; width: 100% !important;}"
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#css = "@media screen and (max-width: 600px) { .output_image, .input_image {height:20rem !important; width: 100% !important;} }"
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