readme

README.md

@@ -36,39 +36,52 @@ __Features:__
 The directory structure of your new project looks like this:
 
 ```
-├── LICENSE
-├── Makefile           <- Makefile with commands like `make data` or `make train`
-├── README.md          <- The top-level README for developers using this project.
-├── data
-│   ├── external       <- Data from third party sources.
-│   ├── interim        <- Intermediate data that has been transformed.
-│   ├── processed      <- The final, canonical data sets for modeling.
-│   └── raw            <- The original, immutable data dump.
-│
-├── docs               <- A default Sphinx project; see sphinx-doc.org for details
-│
-├── models             <- Trained and serialized models, model predictions, or model summaries
-│
-├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
-│                         the creator's initials, and a short `-` delimited description, e.g.
-│                         `1.0-jqp-initial-data-exploration`.
-│
-├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
-│   └── figures        <- Generated graphics and figures to be used in reporting
-│
-├── .pre-commit-config.yaml <- Stores pre-commit settings
-│
-├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
-│                         generated with `pip freeze > requirements.txt`
-│
-├── __init__.py
-│
-└── nets     <- Source code for nets and other stuff use in this project.
-    ├── __init__.py    <- Makes {{cookiecutter.repo_name}} a Python module
-    │    
-    ├── settings.py <- illustrates how to use .env file
-    │
-    └── models         <- Scripts to train models and then use trained models to make
-        │                 predictions
-        └── train.py
+
+│   .pre-commit-config.yaml <- Stores pre-commit settings
+│   LICENSE
+│   Makefile                <- Makefile with commands like `make data` or `make train`
+│   README.md               <- The top-level README for developers using this project.
+│   requirements.txt        <- The requirements file for reproducing the analysis environment, e.g.
+│   setup.py                
+│   test_environment.py
+│   tox.ini                <- tox file with settings for running tox; see tox.testrun.org
+│   __init__.py
+├───app                    <- Folder for wrapper, api, applications and other buisness stuff
+│       api.py
+│       app.py
+│       main.py
+│       __init__.py
+├───data                    <- Folder to store data
+│   │   README.md           <- Desription about data 
+│   ├───processed           <- The final, canonical data sets for modeling.
+│   └───raw                 <- The original, immutable data dump.
+│       ├───external        <- Data from third party sources.
+│       └───interim         <- Intermediate data that has been transformed.
+├── docs                    <- A default Sphinx project; see sphinx-doc.org for details
+├───logs                    <- To store logs from for example tensorboard
+├── models                  <- Trained and serialized models, model predictions, or model summaries
+├── notebooks               <- Jupyter notebooks. Naming convention is a number (for ordering),
+│                           the creator's initials, and a short `-` delimited description, e.g.
+│                           `1.0-jqp-initial-data-exploration`.
+├── references              <- Data dictionaries, manuals, and all other explanatory materials.
+├── reports                 <- Generated analysis as HTML, PDF, LaTeX, etc.
+│   ├───figures             <- Generated analysis as HTML, PDF, LaTeX, etc.
+│   └───images              <- Images for reports
+└───{{ cookiecutter.repo_name }}<- Source code for use in this project.
+    │   settings.py         <- illustrates how to use .env file
+    │   __init__.py         <- Makes {{cookiecutter.repo_name}} a Python module
+    ├───nets                <- Code of your models and nets
+    │       nets.py         <- Nets
+    │       predict.py      <- Evaluation sctript
+    │       train.py        <- Train script
+    │       __init__.py
+    ├───pipelines           <- To store dvc pipelines
+    ├───utils               <- Different utils functions
+    │       featurize.py    <- To create features of dataset
+    │       make_dataset.py <- To create final dataset
+    │       utils.py        <- Different helpers
+    │       __init__.py
+    └───visualization       <- To visualize stuff
+            visualization.py
+            __init__.py
 ```

{{ cookiecutter.repo_name }}/Makefile

@@ -65,14 +65,14 @@ endif
 ## Upload to minio
 sync_data_to_minio:
 ifeq (default,$(MINIOPROFILE))
-	rclone sync data/ $(MINIO)/$(PROJECT_NAME)/data/ --stats-one-line -P --stats 2s
-	rclone sync models/ $(MINIO)/$(PROJECT_NAME)/models/ --stats-one-line -P --stats 2s
+	rclone sync data/ $(MINIO):$(PROJECT_NAME)/data/ --stats-one-line -P --stats 2s
+	rclone sync models/ $(MINIO):$(PROJECT_NAME)/models/ --stats-one-line -P --stats 2s
 
 ## Download from minio
 sync_data_from_minio:
 ifeq (default,$(MINIOPROFILE))
-	rclone sync $(MINIO)/$(PROJECT_NAME)/data/ data/ --stats-one-line -P --stats 2s
-	rclone sync $(MINIO)/$(PROJECT_NAME)/models/ models/ --stats-one-line -P --stats 2s
+	rclone sync $(MINIO):$(PROJECT_NAME)/data/ data/ --stats-one-line -P --stats 2s
+	rclone sync $(MINIO):$(PROJECT_NAME)/models/ models/ --stats-one-line -P --stats 2s
 
 
 ## Initial set up of python interpreter environment, version control and pre-commit hooks