climategan / app.py
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Refactor, polish (WIP)
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import os
import gradio as gr
import googlemaps
from skimage import io
os.system('gdown https://drive.google.com/u/0/uc?id=18OCUIy7JQ2Ow_-cC5xn_hhDn-Bp45N1K')
os.system('unzip release-github-v1.zip')
os.system('mkdir config')
os.system('mv model config')
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)
loc = geocode_result[0]['geometry']['location']
static_map_url = f"https://maps.googleapis.com/maps/api/streetview?size=400x400&location={loc['lat']},{loc['lng']}&fov=80&heading=70&pitch=0&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=["image", "image", "image", "image"],
title="ClimateGAN",
description="Enter an address or place name, and ClimateGAN will generate images showing how the location could be impacted by flooding, wildfires, or smog.",
article="<p style='text-align: center'>This project is a clone of <a href='https://thisclimatedoesnotexist.com/'>ThisClimateDoesNotExist</a> | <a href='https://github.com/cc-ai/climategan'>ClimateGAN GitHub Repo</a></p>",
examples=[
"Kafka's Great Northern Way, Vancouver",
"Simon Fraser University",
"Duomo, Milano"
],
css=".footer{display:none !important}",
).launch()