Add: server name variable

setting.sh

@@ -1,42 +1,64 @@
-# 1. Initial Setting & Jupyter notebook
-## Access to server
-ssh -L 8888:localhost:8888 p3-tokyo-ml
+# 0. Initialize
+## Prepare two tabs, one for train, one for transfer data and tensorboard
+## AMI: Ubuntu deeplearning ami 
+## Storage: 100gib
+
+
+# 1. Initial Setting for both tabs
+export SERVER_NAME=virginia-dl
+export SERVER_NAME=ohio-dl
+export SERVER_NAME=oregon-dl
+export SERVER_NAME=canada-dl
+export SERVER_NAME=london-dl
+export SERVER_NAME=frankfurt-dl
+
+## Access to server in first tab
+ssh ${SERVER_NAME}
 
 ## Deeplearning EC2 Setup
 sudo locale-gen ko_KR.UTF-8
 sudo apt-get install tmux unzip
-
-## Fetch Dishi detection and mask rcnn file
-git clone https://github.com/zaiyou12/Gatten_sushi_dishi_detection.git
-
-## Run jupyter notebook
-cd Gatten_sushi_dishi_detection
 source activate tensorflow_p36
 pip install --upgrade pip
-## jupyter notebook
 
-# 2. Setting for Trainning model
+
+# 2. Send Data to server in second tab
 ## local to remote
-export SERVER_NAME=oregon-dl
-scp data.zip mask_rcnn_coco.h5 ${SERVER_NAME}:/home/ubuntu/Gatten_sushi_dishi_detection/
-cd Gatten_sushi_dishi_detection
+cd ~/Desktop/gatten/
+scp -r dish_server/* ${SERVER_NAME}:/home/ubuntu
+
+
+# 3. Unzip data in first tab
 unzip *.zip
 rm -rf data.zip
+exit
+
 
-## Start Trainning
+# 4. Reconnect EC2 for trainning in first tab
+ssh ${SERVER_NAME}
+
+## change data if needed
+## vim dish.py
 tmux new -s train
+
 source activate tensorflow_p36
 pip install imgaug opencv-python
-python3 dish.py train --dataset=${PWD}/data --weights=coco --pairs BACKBONE=resnet50
-python3 dish.py train --dataset=${PWD}/data --weights=last;mail -s 'Finished' zaiyou12@gmail.com; sudo shutdown now;
+python3 dish.py train --dataset=${PWD}/data --weights=coco --pairs BACKBONE=resnet101
+
+
+# 5. Run TensorBoard in second tab
+ssh -L 6006:localhost:6006 ${SERVER_NAME}
 
-# 3. Run TensorBoard
-ssh -L 6006:localhost:6006 p3-tokyo-ml
-cd Gatten_sushi_dishi_detection
 source activate tensorflow_p36
 tensorboard --logdir=${PWD}/logs
 
+
 # 9. Run in tensorflow docker
-nvidia-docker run -d -p 8888:8888 -p 6006:6006 -e PASSWORD=1111 -v ${PWD}:/notebooks/works tensorflow/tensorflow:latest-gpu-py3
+cd ~/Desktop/gatten/Gatten_sushi_dishi_detection
+nvidia-docker run -d -p 8888:8888 -p 6006:6006 -e PASSWORD=1111 --name board -v ${PWD}:/notebooks/works tensorflow/tensorflow:latest-gpu-py3
+nvidia-docker exec -it board bash
+
+cd works
 pip install scikit-image==0.13.1 imgaug opencv-python
 apt-get install -y libsm6 libxext6 libxrender-dev
+tensorboard --logdir=${PWD}/models