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OFTSR
Yuanzhi/OFTSR
OFTSR is a machine learning model from Yuanzhi. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
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Updated Nov 21, 2024
Repo size
7 GB
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.pth7 GB · 100%
At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Nov 5, 2024
- Updated
- Nov 21, 2024
- SHA
- 90a9b041
Model card
From the Hugging Face model README
Checkpoints for OFTSR
cd OFTSR
huggingface-cli download Yuanzhi/OFTSR --local-dir ckpts
put data at ./val_data
########################## FFHQ Generation ##########################
python sample_fm.py --opt configs/ir_fm_ffhq.yml \
--overrides \
sample.pre_train_model=ckpts/guided_unet-sigma1.0-no_cond-bs128-loss_l2-lr0.0001-FFHQ-checkpoint_26.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
ir.sigma_pertubation=1.0 \
fm_model.use_cond=false
########################## FFHQ Noiseless Restoration ##########################
#--------------------- multi-step ---------------------
python sample_fm.py --opt configs/ir_fm_ffhq.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.1-bs32-loss_l1-lr0.0001-FFHQ-checkpoint_10.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.1 \
fm_model.use_cond=true
#--------------------- one-step ---------------------
python sample_fm.py --opt configs/dis_fm_ffhq.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.1-bs32-loss_l1-lr1e-05-distil-v_boot-solver_rk2_0.5-dt0.05-w_distil_1.0-w_bound_0.1-w_align_0.01-FFHQ_DIS-checkpoint_2.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.1 \
fm_model.use_cond=true
sample.one_step_t=0.99
########################## FFHQ Noisy Restoration ##########################
#--------------------- multi-step ---------------------
python sample_fm.py --opt configs/ir_fm_ffhq.yml \
--overrides \
sample.pre_train_model=ckpts/sr_avp-sf4-sigmay_0.05-guided_unet-sigma0.5-bs128-loss_l1-lr0.0001-FFHQ-checkpoint_23.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
ir.sigma_y=0.05 \
ir.sigma_pertubation=0.5 \
fm_model.use_cond=true
#--------------------- one-step ---------------------
python sample_fm.py --opt configs/dis_fm_ffhq.yml \
--overrides \
sample.pre_train_model=ckpts/sr_avp-sf4-sigmay_0.05-guided_unet-sigma0.5-bs32-loss_l1-lr2e-05-distil-v_boot-solver_rk2_0.5-dt0.05-w_distil_1.0-w_bound_0.1-w_align_0.01-FFHQ_DIS-checkpoint_24.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
ir.sigma_y=0.05 \
ir.sigma_pertubation=0.5 \
fm_model.use_cond=true
sample.one_step_t=0.99
########################## DIV2K Noiseless Restoration ##########################
#--------------------- multi-step ---------------------
python sample_fm.py --opt configs/ir_fm_DIV2K.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.2-bs128-loss_l1-lr1e-05-DIV2K-checkpoint_4.pth \
dataset.val_path='./val_data/DIV2K_valid_HR' \
sample.num_sample=100 \
sample.psnr_batch_size=1 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.2 \
fm_model.use_cond=true
#--------------------- one-step ---------------------
python sample_fm.py --opt configs/dis_fm_DIV2K.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.2-bs32-loss_l1-lr1e-05-distil-v_boot-solver_rk2_0.5-dt0.05-w_distil_1.0-w_bound_0.1-w_align_0.01-DIV2K_DIS-checkpoint_5.pth \
dataset.val_path='./val_data/ffhq_val_100' \
sample.num_sample=100 \
sample.psnr_batch_size=1 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.2 \
fm_model.use_cond=true
sample.one_step_t=0.99
########################## ImageNet Noiseless Restoration ##########################
#--------------------- multi-step ---------------------
python sample_fm.py --opt configs/ir_fm_imagenet.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.2-bs32-loss_l1-lr1e-04-ImageNet-checkpoint_10.pth \
dataset.val_path='./val_data/imagenet_val_100' \
sample.num_sample=100 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.2 \
fm_model.use_cond=true
#--------------------- one-step ---------------------
python sample_fm.py --opt configs/dis_fm_imagenet.yml \
--overrides \
sample.pre_train_model=ckpts/sr_bicubic-sf4-guided_unet-sigma0.2-bs8-loss_l1-lr1e-04-distil-v_boot-solver_rk2_0.5-dt0.05-w_distil_1.0-w_bound_0.1-w_align_0.01-ImageNet_DIS-checkpoint_10.pth \
dataset.val_path='./val_data/imagenet_val_100' \
sample.num_sample=100 \
ir.sigma_y=0. \
ir.sigma_pertubation=0.2 \
fm_model.use_cond=true
sample.one_step_t=0.99
- License
- apache-2.0
- Created
- Nov 5, 2024
- Updated
- Nov 21, 2024