# -*- coding: utf-8 -*- # # @File: app.py # @Author: Haozhe Xie # @Date: 2024-03-02 16:30:00 # @Last Modified by: Haozhe Xie # @Last Modified at: 2024-03-03 16:08:25 # @Email: root@haozhexie.com import gradio as gr import logging import numpy as np import os import ssl import subprocess import sys import torch import urllib.request from PIL import Image # Fix: ssl.SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed ssl._create_default_https_context = ssl._create_unverified_context # Import CityDreamer modules sys.path.append(os.path.join(os.path.dirname(__file__), "citydreamer")) def setup_runtime_env(): logging.info("CUDA version is %s" % subprocess.check_output(["nvcc", "--version"])) logging.info("GCC version is %s" % subprocess.check_output(["g++", "--version"])) # Compile CUDA extensions ext_dir = os.path.join(os.path.dirname(__file__), "citydreamer", "extensions") for e in os.listdir(ext_dir): if not os.path.isdir(os.path.join(ext_dir, e)): continue subprocess.call(["pip", "install", "."], cwd=os.path.join(ext_dir, e)) def get_models(file_name): import citydreamer.model if not os.path.exists(file_name): urllib.request.urlretrieve( "https://huggingface.co/hzxie/city-dreamer/resolve/main/%s" % file_name, file_name, ) ckpt = torch.load(file_name) model = citydreamer.model.GanCraftGenerator(ckpt["cfg"]) if torch.cuda.is_available(): model = torch.nn.DataParallel(model).cuda().eval() model.load_state_dict(ckpt["gancraft_g"], strict=False) return model def get_city_layout(): hf = np.array(Image.open("assets/NYC-HghtFld.png")) seg = np.array(Image.open("assets/NYC-SegMap.png").convert("P")) return hf, seg def get_generated_city(radius, altitude, azimuth, map_center): # The import must be done after CUDA extension compilation import citydreamer.inference return citydreamer.inference.generate_city( get_generated_city.fgm, get_generated_city.bgm, get_generated_city.hf.copy(), get_generated_city.seg.copy(), map_center, map_center, radius, altitude, azimuth, ) def main(debug): title = "CityDreamer Demo 🏙️" with open("README.md", "r") as f: markdown = f.read() desc = markdown[markdown.rfind("---") + 3 :] with open("ARTICLE.md", "r") as f: arti = f.read() app = gr.Interface( get_generated_city, [ gr.Slider(128, 512, value=343, step=5, label="Camera Radius (m)"), gr.Slider(256, 512, value=296, step=5, label="Camera Altitude (m)"), gr.Slider(0, 360, value=60, step=5, label="Camera Azimuth (°)"), gr.Slider(1440, 6752, value=3970, step=5, label="Map Center (px)"), ], [gr.Image(type="numpy", label="Generated City")], title=title, description=desc, article=arti, allow_flagging="never", ) app.queue(api_open=False) app.launch(debug=debug) if __name__ == "__main__": logging.basicConfig( format="[%(levelname)s] %(asctime)s %(message)s", level=logging.INFO ) logging.info("Compiling CUDA extensions...") setup_runtime_env() logging.info("Downloading pretrained models...") fgm = get_models("CityDreamer-Fgnd.pth") bgm = get_models("CityDreamer-Bgnd.pth") get_generated_city.fgm = fgm get_generated_city.bgm = bgm logging.info("Loading New York city layout to RAM...") hf, seg = get_city_layout() get_generated_city.hf = hf get_generated_city.seg = seg logging.info("Starting the main application...") main(os.getenv("DEBUG") == "1")