import os
import gradio as gr
import googlemaps
from skimage import io
from urllib import parse
from inferences import ClimateGAN
API_KEY = os.environ.get("API_KEY")
gmaps = googlemaps.Client(key=API_KEY)
model = ClimateGAN(model_path="config/model/masker")
def predict(place):
geocode_result = gmaps.geocode(place)
address = geocode_result[0]['formatted_address']
static_map_url = f"https://maps.googleapis.com/maps/api/streetview?size=640x640&location={parse.quote(address)}&source=outdoor&key={API_KEY}"
img_np = io.imread(static_map_url)
flood, wildfire, smog = model.inference(img_np)
return img_np, flood, wildfire, smog
gr.Interface(
predict,
inputs=[
gr.inputs.Textbox(label="Address or place name"),
],
outputs=[
gr.outputs.Image(type="numpy", label="Original image"),
gr.outputs.Image(type="numpy", label="Flooding"),
gr.outputs.Image(type="numpy", label="Wildfire"),
gr.outputs.Image(type="numpy", label="Smog"),
],
title="ClimateGAN: Visualize Climate Change",
description="Climate change does not impact everyone equally. This Space shows the effects of the climate emergency, \"one address at a time\". Visit the original experience at ThisClimateDoesNotExist.com.
Enter an address or place name, and ClimateGAN will generate images showing how the location could be impacted by flooding, wildfires, or smog.",
article="
This project is an unofficial clone of ThisClimateDoesNotExist | ClimateGAN GitHub Repo
", examples=[ "Vancouver Art Gallery", "Chicago Bean", "Duomo Siracusa", ], css=".footer{display:none !important}", ).launch(cache_examples=True)