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import os
os.system('pip install "git+https://github.com/facebookresearch/[email protected]#egg=detectron2"')
import layoutparser as lp
import gradio as gr
# PrimaLayout
model0 = lp.Detectron2LayoutModel('lp://PrimaLayout/mask_rcnn_R_50_FPN_3x/config')
# PubLayNet
model1 = lp.Detectron2LayoutModel('lp://PubLayNet/faster_rcnn_R_50_FPN_3x/config')
model2 = lp.Detectron2LayoutModel('lp://PubLayNet/mask_rcnn_R_50_FPN_3x/config')
model3 = lp.Detectron2LayoutModel('lp://PubLayNet/mask_rcnn_X_101_32x8d_FPN_3x/config')
def lpi(img):
# You need to load the image somewhere else, e.g., image = cv2.imread(...)
layout0 = model0.detect(img)
layout1 = model1.detect(img)
layout2 = model2.detect(img)
layout3 = model3.detect(img)
img0 = lp.draw_box(img, layout0)
img1 = lp.draw_box(img, layout1)
img2 = lp.draw_box(img, layout2)
img3 = lp.draw_box(img, layout3)
return img0, img1, img2, img3 # With extra configurations
inputs = gr.inputs.Image(type='pil', label="Original Image")
outputs = [
gr.outputs.Image(type="pil",label="Output Image (PrimaLayout/faster_rcnn_R_50_FPN_3x)"),
gr.outputs.Image(type="pil",label="Output Image (PubLayNet/faster_rcnn_R_50_FPN_3x)"),
gr.outputs.Image(type="pil",label="Output Image (PubLayNet/mask_rcnn_R_50_FPN_3x)"),
gr.outputs.Image(type="pil",label="Output Image (PubLayNet/mask_rcnn_X_101_32x8d_FPN_3x)")
]
title = "Layout Parser (PrimaLayout & PubLayNet models)"
description = "demo for Layout Parser with PrimaLayout & PubLayNet models. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
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>"
examples = [
['example-table.jpeg'],
['paper-image.jpeg']
]
gr.Interface(lpi, inputs, outputs, title=title, description=description, article=article, examples=examples).launch() |