-
Notifications
You must be signed in to change notification settings - Fork 7
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
pretrained #10
Comments
而且那个链接也打不开 |
Thanks for your interest in our work! The weight for the pre-trained model could be found in https://drive.google.com/drive/folders/110l68um6gUJzECIv0AyF-4Fcw0rrQgA9?usp=drive_link Please don't hesitate to let me know if you have future questions! |
Thanks for your answer and your contribution. |
@wendy-xiaozong |
It's an output file that I used to save the result |
const.py文件中,import os
from pathlib import Path
Use environment variables to auto-detect whether we are running an a Compute Canada cluster:
Thanks to https://github.com/DM-Berger/unet-learn/blob/master/src/train/load.py for this trick.
COMPUTECANADA = False
TMP = os.environ.get("SLURM_TMPDIR")
if TMP:
COMPUTECANADA = True
if COMPUTECANADA:
INPUT_FOLDER = Path(str(TMP)).resolve() / "work" / "inputs"
MASK_FOLDER = Path(str(TMP)).resolve() / "work" / "inputs" / "masks"
PRETRAINED_MODEL_FOLDER = Path(str(TMP)).resolve() / "work" / "trained_models"
PRETRAINED_MODEL_DDPM_PATH = (
Path(str(TMP)).resolve() / "work" / "trained_models" / "ddpm"
)
PRETRAINED_MODEL_VAE_PATH = (
Path(str(TMP)).resolve() / "work" / "trained_models" / "vae"
)
PRETRAINED_MODEL_DECODER_PATH = (
Path(str(TMP)).resolve() / "work" / "trained_models" / "decoder"
)
PRETRAINED_MODEL_VGG_PATH = (
Path(str(TMP)).resolve() / "work" / "trained_models" / "vgg16.pt"
)
OUTPUT_FOLDER = Path(str(TMP)).resolve() / "work" / "outputs"
else:
INPUT_FOLDER = Path(file).resolve().parent.parent.parent / "data" / "IXI"
MASK_FOLDER = Path(file).resolve().parent.parent / "masks"
OASIS_FOLDER = Path(file).resolve().parent.parent.parent / "data" / "OASIS"
PRETRAINED_MODEL_FOLDER = (
Path(file).resolve().parent.parent.parent / "data" / "trained_models"
)这些预训练的模型都在哪里啊,数据在哪啊?
The text was updated successfully, but these errors were encountered: