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test_command.txt
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test_command.txt
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# test command
### MAE finetune model test command [vit_base_patch16]
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=224
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=326
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=512
### MAE ensemble post cross attention model finetune test command [vit_base_patch16]
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention
# using label smoothing，mixup and model_ema for training
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --use_model_ema
## test_kind = patch_test
### MAE finetune model test command [vit_base_patch16]
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=224 --test_kind=patch_test
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=326 --test_kind=patch_test
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=512 --test_kind=patch_test
### MAE ensemble post cross attention model finetune test command [vit_base_patch16]
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --test_kind=patch_test
# using label smoothing，mixup and model_ema for training
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --test_kind=patch_test
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=32 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --use_model_ema --test_kind=patch_test
## test_kind = tiff_refine3_test, tiff_file=dataset/tiff_refine3.txt
### MAE finetune model test command [vit_base_patch16]
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=224 --test_kind=tiff_refine3_test --tiff_file=dataset/tiff_refine3.txt
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=326 --test_kind=tiff_refine3_test --tiff_file=dataset/tiff_refine3.txt
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=512 --test_kind=tiff_refine3_test --tiff_file=dataset/tiff_refine3.txt
### MAE ensemble model finetune test command [vit_base_patch16]
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=1 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --test_kind=tiff_refine3_test --tiff_file=dataset/tiff_refine3.txt
## test_kind = tiff_xiangya_test, tiff_file=dataset/tiff_xiangya.txt
### MAE finetune model test command [vit_base_patch16]
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=224 --test_kind=tiff_xiangya_test --tiff_file=dataset/tiff_xiangya.txt
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=326 --test_kind=tiff_xiangya_test --tiff_file=dataset/tiff_xiangya.txt
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=512 --test_kind=tiff_xiangya_test --tiff_file=dataset/tiff_xiangya.txt
### MAE ensemble model finetune test command [vit_base_patch16]
python test.py ----test_mode=fine_tune --augmentation=mae_fine_tune_train --batch_size=1 --model_name=vit_base_patch16_ensemble_post_cross_attention --image_size=224 --patch_size=16 --ensemble --cross_attention --test_kind = tiff_xiangya_test --tiff_file=dataset/tiff_xiangya.txt
## test_kind = tiff_huaxi_test, tiff_file=dataset/tiff_huaxi.txt
### MAE finetune model test command [vit_base_patch16]
python test.py --model_name=vit_base_patch16 --test_mode=fine_tune --augmentation=mae_fine_tune_train --image_size=326 --test_kind=tiff_huaxi_test --tiff_file=dataset/tiff_huaxi.txt
## test_kind = patch_test_expert
python test.py --test_kind=patch_test_expert
## test_kind = tiff_xiangya_expert
python test.py --test_kind=tiff_xiangya_expert