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training_history
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python main_small.py --train --data-folder '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/' --epoch 10
Test Set: Average DICE Coefficient: 0.2366)
num_feat = [64, 128, 256, 512]
python main_small.py \
--train \
--epoch 20 \
--modality 'base' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/512' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/neightbour_project/smallset_preprocess' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/neightbour_project/smallset_pred_output'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-20-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/512' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/neightbour_project/smallset_preprocess' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/neightbour_project/smallset_pred_output' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/neightbour_project/smallset_batch_out'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-20-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/512' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_all_nec/AllNec_gray' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_all_nec/AllNec_gray_pred_output' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_all_nec/AllNec_gray_batch_out'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-20-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/512' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_Nec_3364-2/Nec_3364-2_gray' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_Nec_3364-2/Nec_3364-2_gray_batch_out' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_Nec_3364-2/Nec_3364-2_gray_pred_output'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-20-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/512' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_none/None_gray' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_none/None_gray_batch_out' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/20180503_none/None_gray_pred_output'
Color Pathology:
python main_small.py \
--train \
--epoch 20 \
--modality 'base' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_preprocessed' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_output'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-20-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_preprocessed' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/batch_out' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_output'
python main_small.py \
--modality 'base' \
--load 'unetsmall-final-3-10-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_preprocessed' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/batch_out' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_output'
python main_small.py \
--train \
--batch-size 4 \
--test-batch-size 8 \
--epoch 15 \
--modality 'wsi' \
--channels 3 \
--save-model 'wsi-augment-' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_preprocessed' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_output'
python main_small.py \
--modality 'wsi' \
--channels 3 \
--load 'wsi-augment-unetsmall-final-4-10-0.001' \
--data-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color' \
--pred-input '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_preprocessed' \
--batch-out-folder '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/batch_out' \
--pred-output '/mnt/DATA/datasets/Pathology/Necrosis_Segmentation/color/pred_output'
Tiantan 2017-11
python main_small.py \
--train \
--epoch 10 \
--modality 't2' \
--channels 1 \
--save-model 'Tiantan-2017-11-' \
--data-folder '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/' \
--pred-input '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/test' \
--pred-output '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/test_pred_output'
python main_small.py \
--load 'Tiantan-2017-11-unetsmall-final-3-10-0.001' \
--modality 't2' \
--channels 1 \
--data-folder '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/' \
--pred-input '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/1_tumor_layer_prediction' \
--batch-out-folder '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/2_tumor_segmentation_batch' \
--pred-output '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/3_tumor_segmentation_prediction'
python main_bdclstm.py \
--train \
--epoc 10 \
--modality 't2' \
--channels 1 \
--unet 'Tiantan-2017-11-unetsmall-final-3-10-0.001' \
--data-folder '/mnt/DATA/datasets/all-t2/1-doctors-segmentation-png/512/' \
python main.py \
--train \
--epoch 10 \
--modality 't2' \
--channels 1 \
--save-model 'Tiantan-2017-11-' \
--data-folder '/mnt/960EVO/datasets/tiantan/2017-11/tiantan_preprocessed_png/512/' \