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Browse files- README.md +30 -5
- app.py +25 -0
- example-table.jpeg +0 -0
- packages.txt +1 -0
- paper-image.jpeg +0 -0
- requirements.txt +4 -0
README.md
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---
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title: Layout Parser
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sdk: gradio
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sdk_version: 3.0.3
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app_file: app.py
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pinned: false
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---
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title: Layout Parser
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emoji: 🐨
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colorFrom: indigo
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colorTo: purple
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sdk: gradio
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app_file: app.py
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pinned: false
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---
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# Configuration
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`title`: _string_
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Display title for the Space
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`emoji`: _string_
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Space emoji (emoji-only character allowed)
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`colorFrom`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`colorTo`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`sdk`: _string_
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Can be either `gradio` or `streamlit`
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`sdk_version` : _string_
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Only applicable for `streamlit` SDK.
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See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
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`app_file`: _string_
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Path to your main application file (which contains either `gradio` or `streamlit` Python code).
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Path is relative to the root of the repository.
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`pinned`: _boolean_
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Whether the Space stays on top of your list.
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app.py
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import os
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os.system('pip install "git+https://github.com/facebookresearch/[email protected]#egg=detectron2"')
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import layoutparser as lp
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import gradio as gr
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model = lp.Detectron2LayoutModel('lp://PrimaLayout/mask_rcnn_R_50_FPN_3x/config')
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def lpi(img):
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layout = model.detect(img) # You need to load the image somewhere else, e.g., image = cv2.imread(...)
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return lp.draw_box(img, layout,) # With extra configurations
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inputs = gr.inputs.Image(type='pil', label="Original Image")
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outputs = gr.outputs.Image(type="pil",label="Output Image")
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title = "Layout Parser"
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description = "demo for Layout Parser. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2103.15348'>LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis</a> | <a href='https://github.com/Layout-Parser/layout-parser'>Github Repo</a></p>"
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examples = [
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['example-table.jpeg'],
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['paper-image.jpeg']
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]
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gr.Interface(lpi, inputs, outputs, title=title, description=description, article=article, examples=examples).launch()
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example-table.jpeg
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packages.txt
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libgl1
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paper-image.jpeg
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requirements.txt
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torch
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torchvision
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layoutparser
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opencv-python-headless
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