Fix: config method

dish.py

@@ -114,7 +114,7 @@ class DishConfig(Config):
     # Max number of final detections per image
     DETECTION_MAX_INSTANCES = 100
 
-    def __init__(self, **kwargs):
+    def add_args(self, **kwargs):
         self.__dict__.update(kwargs)
 
 
@@ -389,7 +389,8 @@ def detect_and_color_splash(model, image_path=None, video_path=None):
 
     # Configurations
     if args.command == "train":
-        config = DishConfig(**dict(args.pairs))
+        dish_config = DishConfig()
+	config = dish_config.add_args(**dict(args.pairs))
     else:
         config = DishIngerenceConfig()
     config.display()

setting.sh

@@ -12,21 +12,21 @@ git clone https://github.com/zaiyou12/Gatten_sushi_dishi_detection.git
 ## Run jupyter notebook
 cd Gatten_sushi_dishi_detection
 source activate tensorflow_p36
-pip3 install --upgrade pip
-jupyter notebook
+pip install --upgrade pip
+## jupyter notebook
 
 # 2. Setting for Trainning model
-## (after copy data to server)
-ssh p3-tokyo-ml
+## local to remote
+scp data.zip mask_rcnn_coco.h5 p2-tokyo-ml:/home/ubuntu/Gatten_sushi_dishi_detection/
+## ssh p2-tokyo-ml
 cd Gatten_sushi_dishi_detection && unzip *.zip
-rm -rf __MACOSX/ data.zip
+rm -rf data.zip
 tmux new -s train
 source activate tensorflow_p36
-pip install imgaug
-pip install opencv-python
+pip install imgaug opencv-python
 
 ## Start Trainning
-python3 dish.py train --dataset=${PWD}/data --weights=coco
+python3 dish.py train --dataset=${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;
 
 # 3. Run TensorBoard