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import gradio as gr
def upload_image(image):
return image
iface = gr.Interface(
fn=upload_image,
inputs=gr.Image(type="pil", image_mode="RGB"),
outputs="image",
title="Image Uploader",
description="Upload an image and see the result below."
)
# from PIL import Image
# import os
# import numpy as np
# import urllib.request
# import glob
# # intake library and plugin
# # import intake
# # from intake_zenodo_fetcher import download_zenodo_files_for_entry
# # geospatial libraries
# import geopandas as gpd
# from rasterio.transform import from_origin
# import rasterio.features
# import fiona
# from shapely.geometry import shape, mapping, box
# from shapely.geometry.multipolygon import MultiPolygon
# # machine learning libraries
# from detectron2 import model_zoo
# from detectron2.engine import DefaultPredictor
# from detectron2.utils.visualizer import Visualizer, ColorMode
# from detectron2.config import get_cfg
# from detectron2.engine import DefaultTrainer
# # visualisation
# # import holoviews as hv
# # from IPython.display import display
# # import geoviews.tile_sources as gts
# # import hvplot.pandas
# # import hvplot.xarray
# hv.extension('bokeh', width=100)
iface.launch()
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