updated build files and README. updated packaged pretrained models to…

… be state_dict for better cross pytorch version compatability

Dockerfile

@@ -20,7 +20,7 @@ RUN curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-la
 
 ENV PATH /opt/conda/bin:$PATH
 ENV PATH /opt/conda/envs/$NAME/bin:$PATH
-RUN conda install --name $NAME -c soumith pytorch=0.2.0 torchvision cuda80
+RUN conda install --name $NAME -c pytorch pytorch torchvision
 
 # setup topaz install directory
 WORKDIR /opt/topaz

README.md

@@ -1,6 +1,12 @@
 # Topaz
 A pipeline for particle detection in cryo-electron microscopy images using convolutional neural networks trained from positive and unlabeled examples.
 
+## New in v0.2.0
+
+- Topaz now supports the newest versions of pytorch (>= 0.4.0). If you have pytorch installed for an older version of topaz, it will need to be upgraded. See installation instructions for details.
+- Added __topaz denoise__, a command for denoising micrographs using neural networks.
+- Usability improvements to the GUI.
+
 # Prerequisites
 
 - An Nvidia GPU with CUDA support for GPU acceleration.
@@ -25,20 +31,43 @@ More information on conda environments can be found [here](https://conda.io/docs
 
 To install the precompiled Topaz package and its dependencies, including pytorch:
 ```
-conda install topaz -c tbepler -c soumith
+conda install topaz -c tbepler -c pytorch
 ```
-This installs pytorch from the soumith channel. To install pytorch for cuda 8.0, you also need to install the 'cuda80' package:
+This installs pytorch from the official channel. To install pytorch for specific cuda versions, you will need to add the 'cudatoolkit=X.X' package. E.g. to install pytorch for CUDA 9.1:
 ```
-conda install cuda80 -c soumith
+conda install cudatoolkit=9.1 -c pytorch
 ```
 or combined into a single command:
 ```
-conda install topaz cuda80 -c tbepler -c soumith
+conda install topaz cudatoolkit=9.1 -c tbepler -c pytorch
 ```
+See [here](https://pytorch.org/get-started/locally/) for additional pytorch installation instructions.
+
 That's it! Topaz is now installed in your anaconda environment.
 
 </p></details>
 
+**<details><summary> Click here to install *using Pip*</summary><p>**
+
+We strongly recommend installing Topaz into a _virtual environment_. See [installation instructions](https://virtualenv.pypa.io/en/latest/installation/) and [user guide](https://virtualenv.pypa.io/en/latest/userguide/) for virtualenv.
+
+## Install Topaz
+
+To install Topaz for Python 3.X
+```
+pip3 install topaz
+```
+
+for Python 2.7
+```
+pip install topaz
+```
+See [here](https://pytorch.org/get-started/locally/) for additional pytorch installation instructions, including how to install pytorch for specific CUDA versions.
+
+That's it! Topaz is now installed through pip.
+
+</p></details>
+
 **<details><summary>Click here to install *using Docker*</summary><p>**
 
 **<details><summary>Do you have Docker installed? If not, *click here*</summary><p>**
@@ -117,7 +146,7 @@ Easy installation of dependencies with conda
 conda install numpy pandas scikit-learn
 conda install -c pytorch pytorch torchvision
 ```
-For more info on installing pytorch for your CUDA version see http://pytorch.org
+For more info on installing pytorch for your CUDA version see https://pytorch.org/get-started/locally/
 
 #### Download the source code
 ```

conda-build/meta-v0.1.0.yaml

@@ -0,0 +1,33 @@
+package:
+    name: "topaz"
+    version: {{ GIT_DESCRIBE_TAG }}
+
+source:
+    git_url: https://github.com/tbepler/topaz.git
+    git_tag: v0.1.0
+
+requirements:
+    build:
+        - python
+        - setuptools
+    run:
+        - python
+        - argparse #[py26]
+        - numpy>=0.11
+        - pandas
+        - scikit-learn>=0.19.0
+        - pillow
+        - pytorch=0.2.0
+        - torchvision
+
+
+build:
+    noarch: python
+    number: 0 
+    script: "{{ PYTHON }} setup.py install --single-version-externally-managed --record=record.txt"
+
+
+about:
+    home: https://github.com/tbepler/topaz
+    license: GPLv3
+    license_file: LICENSE

conda-build/meta.yaml

@@ -19,7 +19,7 @@ requirements:
         - pandas
         - scikit-learn>=0.19.0
         - pillow
-        - pytorch=0.2.0
+        - pytorch>=0.4.0
         - torchvision
 
 

setup.py

@@ -1,7 +1,7 @@
 from setuptools import setup, find_packages
 
 name = 'topaz'
-version = '0.1.0'
+version = '0.2.0a'
 
 description = 'Particle picking with positive-unlabeled CNNs'
 long_description = 'Particle picking software for single particle cryo-electron microscopy using convoluational neural networks and positive-unlabeled learning.'

topaz/_version.py

@@ -1 +1 @@
-__version__ = "0.2.0"
+__version__ = "0.2.0a"

topaz/commands/denoise.py

@@ -17,7 +17,7 @@
 import topaz.mrc as mrc
 
 name = 'denoise'
-help = 'denoise micrographs using different denoising algorithms'
+help = 'denoise micrographs with various denoising algorithms'
 
 def add_arguments(parser):
 

topaz/denoise.py

@@ -21,7 +21,9 @@ def load_model(name):
     path = 'pretrained/denoise/' + name
     f = pkg_resources.resource_stream(pkg, path)
 
-    model = torch.load(f)
+    state_dict = torch.load(f)
+    model = UDenoiseNet()
+    model.load_state_dict(state_dict)
 
     return model