The CSBDeep plugin can be installed from the ImageJ update site http://sites.imagej.net/CSBDeep/
. See the CSBDeep Wiki Pages for more details.
- Clone this repository.
- Run the following command from inside the repo:
mvn -Dimagej.app.directory=/path/to/Fiji.app/ -Ddelete.other.versions=true
- Download the examplary image data
- Open Fiji.
- Open an example image, e.g.
tribolium.tif
. - Run the plugin via
Plugins > CSBDeep > Demo
. - Run the plugin by pressing
Ok
.
If all goes well, an image will be displayed representing the result of the model execution.
See the CSBDeep Wiki Pages for more details.
- Use the python code to train your network with your data. Export it as ZIP.
- Open Fiji.
- Open an image.
- Run the plugin for any network via
Plugins > CSBDeep > Run your network
. - Load your exported network by pressing
Browse
on theImport model (.zip)
line. - Run the plugin by pressing
Ok
.
If all goes well, an image will be displayed representing the result of the model execution.
See the CSBDeep Wiki Page for more details.
If you use eclipse you can import our code formatter doc/eclipse-code-formatter.xml
, code cleanup (doc/eclipse-code-clean-up.xml
) and import order (eclipse-import-order.importorder
) settings.
For GPU support we load the TensorFlow JNI with GPU support manually when a command is initialized. This means that the GPU version of the TensorFLow JNI must be accessible in the java library path (For example Fiji.app/lib/linux64
in a Fiji installation).
See the according CSBDeep Wiki page for a detailed installation guide.
See the according CSBDeep Wiki page.
This project is licensed under the BSD 2-clause "Simplified" License -- see the LICENSE.txt file for details.