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import cv2
from doc_ufcn.main import DocUFCN
import gradio as gr
from doc_ufcn import models
from PIL import Image
from PIL import ImageDraw
model_path, parameters = models.download_model("generic-page")
model = DocUFCN(len(parameters["classes"]), parameters["input_size"], "cpu")
model.load(model_path, parameters["mean"], parameters["std"])
def query_image(image):
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
detected_polygons, probabilities, mask, overlap = model.predict(
image, raw_output=True, mask_output=True, overlap_output=True
)
max_confidence = 0
max_prediction = None
for prediction in detected_polygons[1]:
if prediction["confidence"] > max_confidence:
max_confidence = prediction["confidence"]
max_prediction = prediction
image = Image.fromarray(image)
img2 = image.copy()
xy = max_prediction["polygon"]
draw = ImageDraw.Draw(img2)
draw.polygon(xy, fill="blue")
return Image.blend(image, img2, 0.5)
demo = gr.Interface(
query_image,
inputs=[gr.Image()],
outputs="image",
title="doc-ufcn Page Detection Demo",
description="A demo showing the top prediction from the [Teklia/doc-ufcn-generic-page]("
"https://huggingface.co/Teklia/doc-ufcn-generic-page) model. The generic page detection model predicts single pages from document images.",
examples=[
"3cd686f4-b4ce-11ec-aae3-ca04d142e8f4.jpg",
"v2_bsb00046516_00100_full_184__0_default.jpg",
],
).queue()
demo.launch()
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