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import argparse
from pathlib import Path
import torchvision.transforms.functional as TF
from PIL import Image
from tqdm import tqdm
if __name__ == "__main__":
# Create argument parser
parser = argparse.ArgumentParser(description="Assemble renders.")
parser.add_argument("--source_dir", required=True, help="Directory where the dataset is stored.")
args = parser.parse_args()
source_dir = Path(args.source_dir)
# Find all materials
for render_dir in tqdm([x for x in source_dir.glob("**/renders/")]):
passes_dir = render_dir/"passes"
num_renders = len(list(passes_dir.glob("*diffuse.png")))
for i in range(num_renders):
diff_path = passes_dir/f"render_{i:02d}_diffuse.png"
glossy_path = passes_dir/f"render_{i:02d}_glossy.png"
full_path = render_dir/f"render_{i:02d}.png"
diffuse = TF.to_tensor(Image.open(diff_path))
glossy = TF.to_tensor(Image.open(glossy_path))
diffuse = TF.adjust_gamma(diffuse, 2.2)
glossy = TF.adjust_gamma(glossy, 2.2)
render = diffuse + glossy
render = TF.adjust_gamma(render, 1/2.2)
render = TF.to_pil_image(render)
render.save(full_path) |