[NEW] v0.6.1

.circleci/config.yml

@@ -107,6 +107,32 @@ jobs:
             export NEURAL_STYLE_TRANSFER_RELEASE_VERSION=$(python scripts/parse_package_version.py)
             tox -e deploy -vv
 
+  run-algorithm:
+    executor: ubuntu-1604-vm
+    environment:
+      NST_OUTPUT: /nst-output
+      IMAGE: boromir674/neural-style-transfer
+      IMAGE_1: /app/tests/data/canoe_water_w300-h225.jpg
+      IMAGE_2: /app/tests/data/blue-red_w300-h225.jpg
+      ITER: 100
+    steps:
+      - run:
+          name: Create a directory to store the generated images
+          command: sudo mkdir $NST_OUTPUT
+      - run:
+          name: Pull an image (using docker) where both code and a pretrained model are present
+          command: docker pull $IMAGE
+      - run:
+          name: Run a Neural Style Transfer Algorithm for 22 iterations (using the pretrained VGG Deep Neural Network)
+          command: docker run -it --rm -v $NST_OUTPUT:$NST_OUTPUT $IMAGE $IMAGE_1 $IMAGE_2 --iterations $ITER --location $NST_OUTPUT
+      - store_artifacts:
+          path: /nst-output
+          destination: nst-output
+      - persist_to_workspace:
+          root: /
+          paths:
+            - nst-output
+
   integration-test:
     executor: py38-docker-image
     steps:
@@ -148,10 +174,12 @@ workflows:
   version: 2
   build_accept:
     jobs:
+
       - build_n_test:
           filters:
             tags:
               only: /.*/  # runs for all branches and all tags
+
       - send-coverage-to-codacy:
           requires:
             - build_n_test
@@ -164,13 +192,30 @@ workflows:
           filters:
             tags:
               only: /.*/
+      - run-algorithm:
+          requires:
+            - build_n_test
+          filters:
+            branches:
+              only:
+                - regression-test
+      - inspect-previous-artifacts:
+          type: approval
+          requires:
+           - run-algorithm
+          filters:
+            branches:
+              only:
+                - regression-test
+
       - visualize_dependency_graphs:
           filters:
             branches:
               only:
                 - master
                 - dev
                 - release-staging
+
       # - build-documentation:
       #     filters:
       #       branches:

.dockerignore

@@ -0,0 +1,48 @@
+*/__pycache__
+htmlcov
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+.Python
+env
+pip-log.txt
+pip-delete-this-directory.txt
+.tox
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.log
+.git
+.mypy_cache
+.pytest_cache
+.hypothesis
+
+node_modules
+pretrained*
+style-images
+local/
+output/
+nst_output/
+env/
+env-dev/
+dist/
+build/
+test-results/
+dependency-graphs/
+uml-diagrams
+.circleci
+.vscode
+.bettercodehub.yml
+.gitignore
+.prospector.yml
+.pylintrc
+
+mypy.ini
+package.json
+package-lock.json
+tox.ini
+Dockerfile

.gitignore

@@ -13,3 +13,4 @@ build/
 *output
 uml-diagrams
 dependency-graphs
+coverage.xml

.prospector.yml

@@ -72,8 +72,9 @@ pep257:
 mypy:
   run: false
   options:
-    ignore-missing-imports: true
-    follow-imports: skip
+    ignore-missing-imports: false
+    follow-imports: normal
+
 
 vulture:
   run: false

.pylintrc

@@ -225,8 +225,9 @@ contextmanager-decorators=contextlib.contextmanager
 
 # List of members which are set dynamically and missed by pylint inference
 # system, and so shouldn't trigger E1101 when accessed. Python regular
-# expressions are accepted.
-generated-members=_transform|self\.objects|self\._observers
+# expressions are accepted. Things coming from a metaclass or a dynamic attribute set.
+# Can solve E1101: Class 'X' has no 'y' member (no-member)
+generated-members=self\.objects|self\._observers|compute_gram|_content_image|_style_image|adapter_type|mapping
 
 # Tells whether missing members accessed in mixin class should be ignored. A
 # mixin class is detected if its name ends with "mixin" (case insensitive).
@@ -349,13 +350,22 @@ function-naming-style=snake_case
 #function-rgx=
 
 # Good variable names which should always be accepted, separated by a comma.
+# Can solve C0103: Variable name "x" doesn't conform to snake_case naming style (invalid-name)
 good-names=i,
            j,
            k,
            ex,
            Run,
            _,
-           T
+           T,
+           a_C,
+           a_G,
+           a_S,
+           n_H,
+           n_W,
+           n_C,GS,GG,J_style,J_content,J_style_layer,W,b,
+           Js,Jt,Jc,
+           im
 
 # Good variable names regexes, separated by a comma. If names match any regex,
 # they will always be accepted

CHANGELOG.rst

@@ -0,0 +1,19 @@
+0.6.1 (2021-12-01)
+------------------
+
+Changes
+^^^^^^^
+
+test
+""""
+- test algorithm & conditionally mock production pretrained model
+
+
+documentation
+"""""""""""""
+- document how to use the docker image hosted on docker hub
+
+
+ci
+""
+- run regression test on ci server

Dockerfile

@@ -0,0 +1,18 @@
+FROM python:3.8-slim
+
+WORKDIR /app
+
+ADD imagenet-vgg-verydeep-19.mat.tar .
+
+
+COPY requirements/dev.txt reqs.txt
+RUN pip install -r reqs.txt
+
+COPY . .
+
+RUN pip install -e .
+
+COPY tests tests
+
+ENV AA_VGG_19 /app/pretrained_model_bundle/imagenet-vgg-verydeep-19.mat
+ENTRYPOINT [ "neural-style-transfer" ]

README.rst

@@ -29,7 +29,7 @@ This Python package runs a Neural Style Tranfer algorithm on input `content` and
       - | |docker| |image_size|
 
     * - code quality
-      - |better_code_hub| |code_climate| |maintainability| |codacy| |scrutinizer|
+      - |better_code_hub| |codacy| |code_climate| |maintainability| |scrutinizer|
 
 
 
@@ -147,9 +147,12 @@ and the pretrained model are present. That way you can immediately start creatin
 
     docker pull boromir674/neural-style-transfer
 
-    mkdir nst-output
+    export NST_OUTPUT=/home/$USER/nst-output
 
-    docker run -it --rm -v nst-output:/app/nst-output boromir674/neural-style-transfer
+    CONTENT=/path/to/content-image.jpg
+    STYLE=/path/to/style-image.jpg
+
+    docker run -it --rm -v $NST_OUTPUT:/nst-output boromir674/neural-style-transfer $STYLE $CONTENT --iteratins 200 --location /nst-output
 
 
 
@@ -161,7 +164,7 @@ and the pretrained model are present. That way you can immediately start creatin
 
 .. |codecov| image:: https://codecov.io/gh/boromir674/neural-style-transfer/branch/master/graph/badge.svg?token=3POTVNU0L4
     :alt: Codecov
-    :target: https://codecov.io/gh/boromir674/neural-style-transfer
+    :target: https://app.codecov.io/gh/boromir674/neural-style-transfer/branch/master
 
 
 
@@ -177,32 +180,28 @@ and the pretrained model are present. That way you can immediately start creatin
     :alt: PyPI - Python Version
     :target: https://pypi.org/project/artificial-artwork
 
-.. |commits_since| image:: https://img.shields.io/github/commits-since/boromir674/neural-style-transfer/v0.6/master?color=blue&logo=Github
+.. |commits_since| image:: https://img.shields.io/github/commits-since/boromir674/neural-style-transfer/v0.6.1/master?color=blue&logo=Github
     :alt: GitHub commits since tagged version (branch)
-    :target: https://github.com/boromir674/neural-style-transfer/compare/v0.6..master
+    :target: https://github.com/boromir674/neural-style-transfer/compare/v0.6.1..master
 
 
 
 .. |better_code_hub| image:: https://bettercodehub.com/edge/badge/boromir674/neural-style-transfer?branch=master
     :alt: Better Code Hub
     :target: https://bettercodehub.com/
 
-
 .. |codacy| image:: https://app.codacy.com/project/badge/Grade/07b27ac547a94708aefc5e845d2b6d01
     :alt: Codacy
     :target: https://www.codacy.com/gh/boromir674/neural-style-transfer/dashboard?utm_source=github.com&utm_medium=referral&utm_content=boromir674/neural-style-transfer&utm_campaign=Badge_Grade
 
-
 .. |code_climate| image:: https://api.codeclimate.com/v1/badges/2ea98633f88b75e87d1a/maintainability
    :alt: Maintainability
    :target: https://codeclimate.com/github/boromir674/neural-style-transfer/maintainability
 
-
 .. |maintainability| image:: https://img.shields.io/codeclimate/tech-debt/boromir674/neural-style-transfer?logo=CodeClimate
     :alt: Technical Debt
     :target: https://codeclimate.com/github/boromir674/neural-style-transfer/maintainability
 
-
 .. |scrutinizer| image:: https://img.shields.io/scrutinizer/quality/g/boromir674/neural-style-transfer/master?logo=scrutinizer-ci
     :alt: Scrutinizer code quality
     :target: https://scrutinizer-ci.com/g/boromir674/neural-style-transfer/?branch=master
@@ -213,9 +212,9 @@ and the pretrained model are present. That way you can immediately start creatin
     :alt: PyPI Package latest release
     :target: https://pypi.org/project/topic-modeling-toolkit
 
-.. |python_versions| image:: https://img.shields.io/pypi/pyversions/topic-modeling-toolkit.svg
+.. |python_versions| image:: https://img.shields.io/pypi/pyversions/artificial-artwork.svg
     :alt: Supported versions
-    :target: https://pypi.org/project/topic-modeling-toolkit
+    :target: https://pypi.org/project/artificial-artwork/
 
 
 

setup.cfg

@@ -1,7 +1,7 @@
 [metadata]
 ## Setuptools specific information
 name = artificial_artwork
-version = 0.6
+version = 0.6.1
 description = Create artificial artwork by transfering the appearance of one image (eg a famous painting) to another user-supplied image (eg your favourite photograph).
 long_description = file: README.rst
 long_description_content_type = text/x-rst
@@ -14,6 +14,7 @@ author_email = k.lampridis@hotmail.com
 # represents the web home page of the project
 url = https://github.com/boromir674/neural-style-transfer
 
+download_url = https://github.com/boromir674/neural-style-transfer/archive/v0.6.1.tar.gz
 
 ## PyPi specific information
 project_urls =
@@ -78,8 +79,11 @@ skip = .tox,venv,env,env-dev
 default_section = THIRDPARTY
 known_first_party = src,tests
 
+
 [semantic_release]
 version_variable = src/artificial_artwork/__version__.py:__version__
+version_source=source
+
 
 [check-manifest]
 ignore =

src/artificial_artwork/__version__.py

@@ -0,0 +1 @@
+__version__ = '0.6.1'

src/artificial_artwork/algorithm.py

@@ -1,7 +1,5 @@
 import attr
 
-from .style_layer_selector import NSTLayersSelection
-
 
 @attr.s
 class NSTAlgorithm:
@@ -10,11 +8,7 @@ class NSTAlgorithm:
 
 @attr.s
 class AlogirthmParameters:
-    # TODO remove content and style images and output_path
-    # retain only algorithm parameters (variables governing how the algo will behave)
-    # from the algo input (runtime objects that are the INPUT to the algo)
     content_image = attr.ib()
     style_image = attr.ib()
-    style_layers = attr.ib(converter=NSTLayersSelection.from_tuples)
     termination_condition = attr.ib()
     output_path = attr.ib()