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."
)
import cv2
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)