Merge pull request #39 from keisen/release/v0.6.0

Release v0.6.0

.github/workflows/python-package.yml

@@ -19,13 +19,15 @@ jobs:
     strategy:
       matrix:
         python-version: [3.6, 3.7, 3.8]
-        tensorflow: [2.0.3, 2.1.2, 2.2.1, 2.3.1, 2.4.0]
+        tensorflow: [2.0.4, 2.1.3, 2.2.2, 2.3.2, 2.4.1, 2.5.0]
+        include:
+          - python-version: 3.9
+            tensorflow: 2.5.0
         exclude:
           - python-version: 3.8
-            tensorflow: 2.0.3
+            tensorflow: 2.0.4
           - python-version: 3.8
-            tensorflow: 2.1.2
-
+            tensorflow: 2.1.3
     steps:
     - uses: actions/checkout@v2
     - name: Set up Python ${{ matrix.python-version }}

.github/workflows/python-publish.yml

@@ -21,7 +21,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --no-cache-dir --upgrade pip
-        python -m pip install --no-cache-dir setuptools wheel twine
+        python -m pip install --no-cache-dir --upgrade setuptools wheel twine
     - name: Build and publish
       env:
         TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}

.gitignore

@@ -105,10 +105,13 @@ venv.bak/
 
 # Add by keisen
 *.swp
-examples/core*
-examples/sandbox.ipynb
-examples/workspace.ipynb
+/examples/core*
+/examples/sandbox.ipynb
+/examples/workspace.ipynb
 /*.ipynb
 .node-version
 *.nbconvert.ipynb
+Untitled.ipynb
 /temp/
+.DS_Store
+/dockerfiles/docker-compose.yml

README.md

@@ -11,8 +11,8 @@ Currently supported methods for visualization include:
 * Class Activation Maps
    - [GradCAM](https://arxiv.org/pdf/1610.02391v1.pdf)
    - [GradCAM++](https://arxiv.org/pdf/1710.11063.pdf)
-   - [ScoreCAM](https://arxiv.org/pdf/1910.01279.pdf) :new::zap:
-   - [Faster-ScoreCAM](https://github.com/tabayashi0117/Score-CAM/blob/master/README.md#faster-score-cam) :new::zap:
+   - [ScoreCAM](https://arxiv.org/pdf/1910.01279.pdf)
+   - [Faster-ScoreCAM](https://github.com/tabayashi0117/Score-CAM/blob/master/README.md#faster-score-cam)
 * Saliency Maps
    - [Vanilla Saliency](https://arxiv.org/pdf/1312.6034.pdf)
    - [SmoothGrad](https://arxiv.org/pdf/1706.03825.pdf)
@@ -28,11 +28,11 @@ All visualizations have the features as follows:
 
 ## Visualizations
 
-### Visualize Dense Layer
+### Visualizing Dense Layer
 
 <img src='https://github.com/keisen/tf-keras-vis/raw/master/examples/images/visualize-dense-layer.png' width='600px' />
 
-### Visualize Convolutional Filer
+### Visualizing Convolutional Filer
 
 <img src='https://github.com/keisen/tf-keras-vis/raw/master/examples/images/visualize-filters.png' width='600px' />
 
@@ -51,7 +51,7 @@ The images above are generated by `SmoothGrad`.
 
 ## Requirements
 
-* Python 3.6-3.8
+* Python 3.6-3.9
 * tensorflow>=2.0.2
 
 
@@ -66,13 +66,15 @@ $ pip install tf-keras-vis tensorflow
 * Docker (container that run Jupyter Notebook)
 
 ```bash
-$ docker run -itd -p 8888:8888 keisen/tf-keras-vis:0.5.0
+$ cd tf-keras-vis
+$ docker build -t <TAG> -f dockerfiles/gpu.Dockerfile .
+$ docker run --gpus all --privileged -itd -p 8888:8888 <TAG>
 ```
 
-If you have GPU processors,
+Or
 
 ```bash
-$ docker run -itd --runtime=nvidia -p 8888:8888 keisen/tf-keras-vis:0.5.0-gpu
+$ docker run --gpus all --privileged -itd -p 8888:8888 keisen/tf-keras-vis:0.5.0-gpu
 ```
 
 > You can find other images at [Docker Hub](https://hub.docker.com/repository/docker/keisen/tf-keras-vis/tags).
@@ -96,15 +98,16 @@ But please note that tf-keras-vis APIs does NOT have compatibility with keras-vi
 ### Guides (ToDo)
 
 * Visualizing multiple attention or activation images at once utilizing batch-system of model
-* Define various loss functions
+* Define various score functions
 * Visualizing attentions with multiple inputs models
 * Visualizing attentions with multiple outputs models
-* Advanced loss functions
+* Advanced score functions
 * Tuning Activation Maximization
 * Visualizing attentions for N-dim image inputs
 
 
 ## ToDo
+
 * Guide documentations
 * API documentations
 * We're going to add some methods such as below.
@@ -117,4 +120,11 @@ But please note that tf-keras-vis APIs does NOT have compatibility with keras-vi
 * With InceptionV3, ActivationMaximization doesn't work well, that's, it might generate meaninglessly blur image.
 * With cascading model, Gradcam and Gradcam++ don't work well, that's, it might occur some error. So we recommend, in this case, to use FasterScoreCAM.
 * `channels-first` models and data is unsupported.
+* With a `mixed-precision` model that has a layer which are set float32 dtype exlicitly, ActivationMaximization may raise a error.
+* With a `mixed-precision` model, Regurarization values that is calculated by ActivationMaximization may be NaN.
+
+
+## Use Cases
 
+* [chitra](https://github.com/aniketmaurya/chitra)
+   * A Deep Learning Computer Vision library for easy data loading, model building and model interpretation with GradCAM/GradCAM++.

dockerfiles/cpu.Dockerfile

@@ -1,23 +1,23 @@
-FROM tensorflow/tensorflow:2.2.0
+FROM tensorflow/tensorflow:2.4.1
 
 # Default ENV Settings
-ARG TF_KERAS_VIS_VERSION=0.5.0
+ARG TF_KERAS_VIS_VERSION=0.6.0
 ARG JUPYTER_ALLOW_IP="0.0.0.0"
 ARG JUPYTER_TOKEN=""
 
 # Setting for jupyter
-RUN export JUPYTER_HOME=/root/.jupyter                             && \
+RUN export JUPYTER_HOME=/etc/jupyter                               && \
     export JUPYTER_CONF=$JUPYTER_HOME/jupyter_notebook_config.py   && \
     mkdir -p $JUPYTER_HOME                                         && \
     touch $JUPYTER_CONF                                            && \
     echo 'c.NotebookApp.allow_root = True' >> $JUPYTER_CONF        && \
     echo "c.NotebookApp.ip = '$JUPYTER_ALLOW_IP'" >> $JUPYTER_CONF && \
-    echo "c.NotebookApp.token = '$JUPYTER_TOKEN'" >> $JUPYTER_CONF
+    echo "c.NotebookApp.token = '$JUPYTER_TOKEN'" >> $JUPYTER_CONF && \
+    echo "c.NotebookApp.terminado_settings =                          \
+                {'shell_command': ['/bin/bash']}" >> $JUPYTER_CONF
 
 # Install essential python libraries
-RUN pip install --no-cache-dir            \
-      tf-keras-vis==$TF_KERAS_VIS_VERSION \
-      numpy scipy imageio pillow          \
-      jupyterlab matplotlib
+RUN pip install --no-cache-dir \
+      tf-keras-vis[develop,examples]==$TF_KERAS_VIS_VERSION
 
-CMD [ "jupyter", "lab" ]
+CMD jupyter lab

dockerfiles/gpu.Dockerfile

@@ -1,23 +1,22 @@
-FROM tensorflow/tensorflow:2.2.0-gpu
+FROM tensorflow/tensorflow:2.4.1-gpu
 
-# Default ENV Settings
-ARG TF_KERAS_VIS_VERSION=0.5.0
+ARG TF_KERAS_VIS_VERSION=0.6.0
 ARG JUPYTER_ALLOW_IP="0.0.0.0"
 ARG JUPYTER_TOKEN=""
 
 # Setting for jupyter
-RUN export JUPYTER_HOME=/root/.jupyter                             && \
+RUN export JUPYTER_HOME=/etc/jupyter                               && \
     export JUPYTER_CONF=$JUPYTER_HOME/jupyter_notebook_config.py   && \
     mkdir -p $JUPYTER_HOME                                         && \
     touch $JUPYTER_CONF                                            && \
     echo 'c.NotebookApp.allow_root = True' >> $JUPYTER_CONF        && \
     echo "c.NotebookApp.ip = '$JUPYTER_ALLOW_IP'" >> $JUPYTER_CONF && \
-    echo "c.NotebookApp.token = '$JUPYTER_TOKEN'" >> $JUPYTER_CONF
+    echo "c.NotebookApp.token = '$JUPYTER_TOKEN'" >> $JUPYTER_CONF && \
+    echo "c.NotebookApp.terminado_settings =                          \
+                {'shell_command': ['/bin/bash']}" >> $JUPYTER_CONF
 
 # Install essential python libraries
-RUN pip install --no-cache-dir            \
-      tf-keras-vis==$TF_KERAS_VIS_VERSION \
-      numpy scipy imageio pillow          \
-      jupyterlab matplotlib
+RUN pip install --no-cache-dir \
+      tf-keras-vis[develop,examples]==$TF_KERAS_VIS_VERSION
 
-CMD [ "jupyter", "lab" ]
+CMD jupyter lab