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from einops import rearrange, repeat
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import torch, torchvision
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from ldm.models.diffusion.ddim import DDIMSampler
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from ldm.util import ismap
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import time
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from omegaconf import OmegaConf
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def download_models(mode):
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if mode == "superresolution":
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# this is the small bsr light model
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url_conf = 'https://heibox.uni-heidelberg.de/f/31a76b13ea27482981b4/?dl=1'
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url_ckpt = 'https://heibox.uni-heidelberg.de/f/578df07c8fc04ffbadf3/?dl=1'
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path_conf = 'logs/diffusion/superresolution_bsr/configs/project.yaml'
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path_ckpt = 'logs/diffusion/superresolution_bsr/checkpoints/last.ckpt'
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download_url(url_conf, path_conf)
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download_url(url_ckpt, path_ckpt)
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path_conf = path_conf + '/?dl=1' # fix it
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path_ckpt = path_ckpt + '/?dl=1' # fix it
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return path_conf, path_ckpt
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else:
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raise NotImplementedError
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def load_model_from_config(config, ckpt):
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print(f"Loading model from {ckpt}")
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pl_sd = torch.load(ckpt, map_location="cpu")
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global_step = pl_sd["global_step"]
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sd = pl_sd["state_dict"]
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model = instantiate_from_config(config.model)
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m, u = model.load_state_dict(sd, strict=False)
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model.cuda()
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model.eval()
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return {"model": model}, global_step
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def get_model(mode):
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path_conf, path_ckpt = download_models(mode)
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config = OmegaConf.load(path_conf)
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model, step = load_model_from_config(config, path_ckpt)
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return model
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def get_custom_cond(mode):
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dest = "data/example_conditioning"
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if mode == "superresolution":
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uploaded_img = files.upload()
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filename = next(iter(uploaded_img))
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name, filetype = filename.split(".") # todo assumes just one dot in name !
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os.rename(f"{filename}", f"{dest}/{mode}/custom_{name}.{filetype}")
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elif mode == "text_conditional":
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w = widgets.Text(value='A cake with cream!', disabled=True)
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display(w)
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with open(f"{dest}/{mode}/custom_{w.value[:20]}.txt", 'w') as f:
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f.write(w.value)
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elif mode == "class_conditional":
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w = widgets.IntSlider(min=0, max=1000)
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display(w)
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with open(f"{dest}/{mode}/custom.txt", 'w') as f:
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f.write(w.value)
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else:
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raise NotImplementedError(f"cond not implemented for mode{mode}")
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def get_cond_options(mode):
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path = "data/example_conditioning"
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path = os.path.join(path, mode)
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onlyfiles = [f for f in sorted(os.listdir(path))]
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return path, onlyfiles
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def select_cond_path(mode):
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path = "data/example_conditioning" # todo
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path = os.path.join(path, mode)
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onlyfiles = [f for f in sorted(os.listdir(path))]
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selected = widgets.RadioButtons(
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options=onlyfiles,
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description='Select conditioning:',
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disabled=False
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)
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display(selected)
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selected_path = os.path.join(path, selected.value)
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return selected_path
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def get_cond(mode, selected_path):
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example = dict()
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if mode == "superresolution":
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up_f = 4
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