Dev (#142)

* added gmean tta, experimented with thresholding (#125)

* Dev repo cleanup (#138)

* initial restructure

* clean structure (#126)

* clean structure

* correct readme

* further cleaning

* Dev apply transformer (#131)

* clean structure

* correct readme

* further cleaning

* resizer docstring

* couple docstrings

* make apply transformer, memory cache

* fixes

* postprocessing docstrings

* fixes in PR

* Dev repo cleanup (#132)

* cleanup

* remove src.

* Dev clean tta (#134)

* added resize padding, refactored inference pipelines

* refactored piepliens

* added color shift augmentation

* reduced caching to just mask_resize

* updated config

* Dev-repo_cleanup models and losses docstrings (#135)

* models and losses docstrings

* small fixes in docstrings

* resolve conflicts in with TTA PR (#137)

* refactor in stream mode (#139)

* hot fix of mask_postprocessing in tta with new make transformer

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* local

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Dev preparation path fix (#140)

* local

* cleaned up paths in the masks and metadata generation

* dropped debug stuff

* Dev non trainable transformer flag (#141)

* local

* added is_trainable flag to models

Author: jakubczakon

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.5
+
+RUN apt-get update
+RUN pip3 install http://download.pytorch.org/whl/cpu/torch-0.3.1-cp35-cp35m-linux_x86_64.whl && \
+    pip3 install torchvision
+
+COPY requirements.txt requirements.txt
+RUN pip install -r requirements.txt
+
+#ADD ./src /opt/src
+#ADD ./model_weights /opt/model_weights
+
+WORKDIR /opt/src

README.md

@@ -203,7 +203,7 @@ $ neptune data upload YOUR/DATA/FOLDER
     * local pure python
 
     ```bash
-    $ python main.py train --pipeline_name unet_weighted
+    $ python main.py -- train --pipeline_name unet_weighted
     ```
 
 7. evaluate model and predict on test data:
@@ -237,7 +237,7 @@ $ neptune data upload YOUR/DATA/FOLDER
     * local pure python
 
     ```bash
-    $ python main.py evaluate_predict --pipeline_name unet_tta --chunk_size 1000
+    $ python main.py -- evaluate_predict --pipeline_name unet_tta --chunk_size 1000
     ```
 
 ## User support