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(server_port=7861)