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)