Chris MyauandClaude Sonnet 4.6
df9d9eb7c0
Wraps the Adobe Research PIH model (CVPR 2023) as ComfyUI nodes. Includes auto-download of the pretrained checkpoint on first use. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
71 lines
2.4 KiB
Bash
71 lines
2.4 KiB
Bash
# Copyright 2023 Adobe. All rights reserved.
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# This file is licensed to you under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License. You may obtain a copy
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# of the License at http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software distributed under
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# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR REPRESENTATIONS
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# OF ANY KIND, either express or implied. See the License for the specific language
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# governing permissions and limitations under the License.
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# Network hyperparameters
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device=0
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lr=4e-5
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lrd=4e-5
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batch_size=8
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date=Demo_train_example
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reconweight=None
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training_ratio=1
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inputdimD=3
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recon_ratio=0.5
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recon_weight=0.92 ## Used here
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name=iharmony_${inputdimD}_ratio_${training_ratio}_${recon_ratio}_reconweight_${recon_weight}
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model_name=exp_${date}_batch_size_$((batch_size))_lr_${lr}_${name}_device_${device}
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# Set folder names
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dir_data=demo_data/train/
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# dir_data=/mnt/localssd/LR_data/train/
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CUDA_VISIBLE_DEVICES=$device python PIH_train.py --datadir $dir_data \
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-g 0 \
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--onlysaveg \
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--bs $batch_size \
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--lr $lr \
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--lrd $lrd \
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--force_train_from_scratch \
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--tempdir \
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$model_name \
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--workers 8 \
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--trainingratio ${training_ratio} \
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--unetd \
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--inputdimD ${inputdimD} \
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--nocurve \
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--reconratio ${recon_ratio} \
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--piecewiselinear \
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--pl-dim 32 \
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--pairaugment \
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--purepairaugment \
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--lowdim \
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--ganlossmask \
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--reconwithgan \
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--reconweight ${recon_weight} \
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--masking \
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--brush \
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--maskoffset 0.5 \
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--swap \
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--onlyupsample \
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--joint \
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--lessskip \
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--aggupsample \
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--scheduler \
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--colorjitter \
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