We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
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
The image generated in the training process has a good effect, but it is also poor to test the effect with the training set.My orders are: train:
python train.py --name InstanceData --instance_feat --checkpoints_dir ./CheckPoint --batchSize 2 --label_nc 7
python precompute_feature_maps.py --name InstanceData --label_nc 7 --batchSize 4 --checkpoints_dir ./CheckPoint --instance_feat
python train.py --name InstanceDataNew --netG local --ngf 32 --num_D 3 --load_pretrain CheckPoint/InstanceData/ --niter 20 --niter_decay 20 --niter_fix_global 10 --instance_feat --load_features --batchSize 4 --label_nc 7 --checkpoints_dir ./CheckPoint
test:
python encode_features.py --name InstanceDataNew --netG local --ngf 32 --checkpoints_dir ./CheckPoint --label_nc 7 --instance_feat
python test.py --name InstanceDataNew --netG local --ngf 32 --instance_feat --checkpoints_dir ./CheckPoint --label_nc 7
The text was updated successfully, but these errors were encountered:
try train: python train.py --name InstanceData --instance_feat --checkpoints_dir ./CheckPoint --batchSize 2 --label_nc 7 --netG local
Sorry, something went wrong.
The image generated in the training process has a good effect, but it is also poor to test the effect with the training set.My orders are: train: python train.py --name InstanceData --instance_feat --checkpoints_dir ./CheckPoint --batchSize 2 --label_nc 7 python precompute_feature_maps.py --name InstanceData --label_nc 7 --batchSize 4 --checkpoints_dir ./CheckPoint --instance_feat python train.py --name InstanceDataNew --netG local --ngf 32 --num_D 3 --load_pretrain CheckPoint/InstanceData/ --niter 20 --niter_decay 20 --niter_fix_global 10 --instance_feat --load_features --batchSize 4 --label_nc 7 --checkpoints_dir ./CheckPoint test: python encode_features.py --name InstanceDataNew --netG local --ngf 32 --checkpoints_dir ./CheckPoint --label_nc 7 --instance_feat python test.py --name InstanceDataNew --netG local --ngf 32 --instance_feat --checkpoints_dir ./CheckPoint --label_nc 7
hello would you solove this question ? please help me
No branches or pull requests
The image generated in the training process has a good effect, but it is also poor to test the effect with the training set.My orders are:
train:
python train.py --name InstanceData --instance_feat --checkpoints_dir ./CheckPoint --batchSize 2 --label_nc 7
python precompute_feature_maps.py --name InstanceData --label_nc 7 --batchSize 4 --checkpoints_dir ./CheckPoint --instance_feat
python train.py --name InstanceDataNew --netG local --ngf 32 --num_D 3 --load_pretrain CheckPoint/InstanceData/ --niter 20 --niter_decay 20 --niter_fix_global 10 --instance_feat --load_features --batchSize 4 --label_nc 7 --checkpoints_dir ./CheckPoint
test:
python encode_features.py --name InstanceDataNew --netG local --ngf 32 --checkpoints_dir ./CheckPoint --label_nc 7 --instance_feat
python test.py --name InstanceDataNew --netG local --ngf 32 --instance_feat --checkpoints_dir ./CheckPoint --label_nc 7
The text was updated successfully, but these errors were encountered: