Add training script sample

appendix/train_cunet_art.sh

@@ -0,0 +1,66 @@
+#!/bin/sh
+
+MODEL_DIR=models/test/cunet_release/
+THREADS=16
+mkdir -p ${MODEL_DIR}
+
+# convert data
+th convert_data.lua -max_training_image_size 1600
+
+# scale
+th train.lua -method scale -save_history 1 -model upcunet -downsampling_filters "Box,Box,Box,Box,Sinc,Sinc,Sinc,Sinc,Catrom" -model_dir ${MODEL_DIR} -test query/scale_test.png -thread ${THREADS} -backend cudnn -oracle_rate 0.0 -max_size 512 -loss aux_lbp -update_criterion loss -crop_size 104 -validation_crops 64 -inner_epoch 2 -epoch 200 -patches 32 -batch_size 8 > ${MODEL_DIR}/train.log 2>&1 
+
+# noise scale 0
+th train.lua -save_history 1 -model upcunet -method noise_scale -noise_level 0 -style art \
+-downsampling_filters "Box,Box,Box,Box,Sinc,Sinc,Sinc,Sinc,Catrom" -model_dir ${MODEL_DIR} -test query/noise_test.jpg -thread ${THREADS} -backend cudnn -oracle_rate 0.1 -max_size 512 -loss aux_lbp -update_criterion loss -crop_size 104 -validation_crops 64 -inner_epoch 4 -epoch 30 -patches 32 -batch_size 8 \
+-resume ${MODEL_DIR}/scale2.0x_model.t7 \
+ > ${MODEL_DIR}/train_noise_scale0.log 2>&1 
+
+# noise scale 1
+th train.lua -save_history 1 -model upcunet -method noise_scale -noise_level 1 -style art \
+-downsampling_filters "Box,Box,Box,Box,Sinc,Sinc,Sinc,Sinc,Catrom" -model_dir ${MODEL_DIR} -test query/noise_test.jpg -thread ${THREADS} -backend cudnn -oracle_rate 0.1 -max_size 512 -loss aux_lbp -update_criterion loss -crop_size 104 -validation_crops 64 -inner_epoch 4 -epoch 30 -patches 32 -batch_size 8 \
+-resume ${MODEL_DIR}/scale2.0x_model.t7 \
+ > ${MODEL_DIR}/train_noise_scale1.log 2>&1 
+
+# noise scale 2
+th train.lua -save_history 1 -model upcunet -method noise_scale -noise_level 2 -style art \
+-downsampling_filters "Box,Box,Box,Box,Sinc,Sinc,Sinc,Sinc,Catrom" -model_dir ${MODEL_DIR} -test query/noise_test.jpg -thread ${THREADS} -backend cudnn -oracle_rate 0.1 -max_size 512 -loss aux_lbp -update_criterion loss -crop_size 104 -validation_crops 64 -inner_epoch 4 -epoch 30 -patches 32 -batch_size 8 \
+-resume ${MODEL_DIR}/scale2.0x_model.t7 \
+ > ${MODEL_DIR}/train_noise_scale2.log 2>&1 
+
+
+# noise scale 3
+th train.lua -save_history 1 -model upcunet -method noise_scale -noise_level 3 -style art \
+-downsampling_filters "Box,Box,Box,Box,Sinc,Sinc,Sinc,Sinc,Catrom" -model_dir ${MODEL_DIR} -test query/noise_test.jpg -thread ${THREADS} -backend cudnn -oracle_rate 0.1 -max_size 512 -loss aux_lbp -update_criterion loss -crop_size 104 -validation_crops 64 -inner_epoch 4 -epoch 30 -patches 32 -batch_size 8 -nr_rate 1 \
+-resume ${MODEL_DIR}/scale2.0x_model.t7 \
+ > ${MODEL_DIR}/train_noise_scale3.log 2>&1 
+
+
+# noise 0
+th train.lua -save_history 1 -model cunet -method noise -noise_level 0 -model_dir ${MODEL_DIR} -test query/noise_test.jpg -backend cudnn -thread ${THREADS} -style art \
+-crop_size 88 -validation_crops 64 -patches 16 -batch_size 8 -epoch 50 -max_size 512 \
+-loss aux_lbp -update_criterion loss \
+-oracle_rate 0.1 \
+> ${MODEL_DIR}/train_noise0.log 2>&1 
+
+# noise 1
+th train.lua -save_history 1 -model cunet -method noise -noise_level 1 -model_dir ${MODEL_DIR} -test query/noise_test.jpg -backend cudnn -thread ${THREADS} -style art \
+-crop_size 88 -validation_crops 64 -patches 16 -batch_size 8 -epoch 50 -max_size 512 \
+-loss aux_lbp -update_criterion loss \
+-oracle_rate 0.1 \
+> ${MODEL_DIR}/train_noise1.log 2>&1 
+
+# noise 2
+th train.lua -save_history 1 -model cunet -method noise -noise_level 2 -model_dir ${MODEL_DIR} -test query/noise_test.jpg -backend cudnn -thread ${THREADS} -style art \
+-crop_size 88 -validation_crops 64 -patches 16 -batch_size 8 -epoch 50 -max_size 512 \
+-loss aux_lbp -update_criterion loss \
+-oracle_rate 0.1 \
+> ${MODEL_DIR}/train.log 2>&1 
+
+# noise3
+
+th train.lua -save_history 1 -model cunet -method noise -noise_level 3 -model_dir ${MODEL_DIR} -test query/noise_test.jpg -backend cudnn -thread ${THREADS} -style art -nr_rate 1 \
+-crop_size 88 -validation_crops 64 -patches 16 -batch_size 8 -epoch 50 -max_size 512 \
+-loss aux_lbp -update_criterion loss \
+-oracle_rate 0.1 \
+> ${MODEL_DIR}/train_noise3.log 2>&1