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====== Just Another Noise 2 Noise Implementation (JANNI) ====== | ====== Just Another Noise 2 Noise Implementation (JANNI) ====== | ||
- | JANNI implements a neural network denoising tool described in NVIDIA' | + | JANNI implements a neural network denoising tool described in NVIDIA' |
- | [[https:// | + | |
It can be trained on your data without the need of ground truth images. It supports MRC and TIFF format. | It can be trained on your data without the need of ground truth images. It supports MRC and TIFF format. | ||
- | JANNI can be used a command line tool but also provides an simple interface to integrate into other programs (see [[janni_tutorial# | + | JANNI can be used a command line tool but also provides an simple interface to integrate into other programs (see [[:janni_tutorial# |
- | < | + | |
* **License**: | * **License**: | ||
- | * **GitHub repository**: | + | * **GitHub repository**: |
- | </ | + | </ |
- | This is an example where we applied JANNI: | + | |
- | {{ :: | + | {{ : |
+ | |||
+ | <note important> | ||
- | <note important> | ||
- | The denoised micrographs are likely bad to use for further processing besides picking. | ||
- | </ | ||
==== Download ==== | ==== Download ==== | ||
+ | |||
=== JANNI === | === JANNI === | ||
- | Version: 0.2 | ||
- | Uploaded: | + | Version: 0.3.1 |
+ | |||
+ | Uploaded: | ||
[[https:// | [[https:// | ||
=== JANNI General Model === | === JANNI General Model === | ||
+ | |||
Version: 20190703 (Trained on 1xFalcon 2, 3x Falcon 3, 7xK2 datasets from Arctica / Krios) | Version: 20190703 (Trained on 1xFalcon 2, 3x Falcon 3, 7xK2 datasets from Arctica / Krios) | ||
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[[https:// | [[https:// | ||
+ | |||
==== Known Issues ==== | ==== Known Issues ==== | ||
+ | |||
- < | - < | ||
==== Installation ==== | ==== Installation ==== | ||
- | The following instructions assume that pip and anaconda or miniconda are available. | ||
- | 1. In case you have a old JANNI environment installed, you might want to remove the old one with: | + | The following instructions assume that pip and anaconda or miniconda are available. |
+ | |||
+ | 1. In case you have a old JANNI environment installed, you might want to remove the old one with: | ||
< | < | ||
conda env remove --name janni | conda env remove --name janni | ||
+ | |||
</ | </ | ||
- | 2. After that, create a new virtual environment: | + | 2. After that, create a new virtual environment: |
< | < | ||
- | conda create -n janni -c anaconda python=3.6 cudnn=7.1.2 libtiff wxPython=4.0.4 | + | conda create -n janni -c conda-forge |
</ | </ | ||
- | 3. Activate the environment: | + | 3. Activate the environment: |
< | < | ||
source activate janni | source activate janni | ||
+ | |||
</ | </ | ||
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< | < | ||
pip install janni[gpu] | pip install janni[gpu] | ||
+ | |||
</ | </ | ||
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< | < | ||
pip install janni[cpu] | pip install janni[cpu] | ||
+ | |||
</ | </ | ||
+ | |||
==== Getting started ==== | ==== Getting started ==== | ||
- | [[janni_tutorial|Here you can find a tutorial how to denoise your micrograghs | + | |
+ | [[:janni_tutorial|Here you can find a tutorial how to denoise your micrographs | ||
==== How to cite ==== | ==== How to cite ==== | ||
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You can cite JANNI using the Zenodo DOI: | You can cite JANNI using the Zenodo DOI: | ||
- | < | + | < |
- | <a href=" | + | |
- | </ | + | |
==== Changelog ==== | ==== Changelog ==== | ||
+ | |||
+ | **JANNI 0.3.1:** | ||
+ | |||
+ | * Fix dependency issue with protobuf (Thanks to Tapu Shaikh) | ||
+ | |||
+ | **JANNI 0.3:** | ||
+ | |||
+ | * Update dependencies and fix setup. | ||
+ | |||
+ | **JANNI 0.2.2:** | ||
+ | |||
+ | * Fix an issue that JANNI can't denoise a single image (it only worked for folders) (Thanks to Sony Malhotra) | ||
+ | |||
+ | **JANNI 0.2.1:** | ||
+ | |||
+ | * Because of an libary update, JANNI was not working anymore (No supported model) (Thanks to | ||
+ | |||
+ | Sony Malhotra) . | ||
+ | |||
+ | **JANNI 0.2** | ||
+ | |||
+ | * Added support for binning. In case you recorded your movies in super resolution mode, but later want to apply JANNI to binned images, you need to bin your images during training. This now happens when ' | ||
+ | * JANNI now allows to choose between two loss functions: mean squared error (mse) or mean absolute error (mae). The latter is the new default. | ||
+ | |||
**JANNI 0.1.2** | **JANNI 0.1.2** | ||
+ | |||
* Fix installation procedure. | * Fix installation procedure. | ||
**JANNI 0.1.0** | **JANNI 0.1.0** | ||
+ | |||
* Add GUI | * Add GUI | ||
* API changes for crYOLO 1.5 | * API changes for crYOLO 1.5 | ||
**JANNI 0.0.5** | **JANNI 0.0.5** | ||
+ | |||
* Downgrade tensorflow and numpy again as it leads to long initialization times for some users. | * Downgrade tensorflow and numpy again as it leads to long initialization times for some users. | ||
- | * | + | * |
**JANNI 0.0.4** | **JANNI 0.0.4** | ||
+ | |||
* Improved selection of validation data | * Improved selection of validation data | ||
* Add more data augmentation | * Add more data augmentation | ||
* Updated libraries (To Tensorflow 1.12.3 and numpy 1.15.4) to make it compatible with crYOLO | * Updated libraries (To Tensorflow 1.12.3 and numpy 1.15.4) to make it compatible with crYOLO | ||
+ | |||
+ |