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downloads:cryolo_1 [2019/03/18 08:13] twagner [Change log] |
downloads:cryolo_1 [2019/07/09 19:50] twagner [crYOLO] |
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You can find more technical details in our paper: | You can find more technical details in our paper: | ||
+ | Nature Communications Biology: | ||
+ | [[https:// | ||
+ | |||
+ | Preprint: | ||
[[https:// | [[https:// | ||
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====crYOLO==== | ====crYOLO==== | ||
- | Version: 1.3.1 | + | Version: 1.3.6 |
+ | |||
+ | Uploaded: | ||
- | Uploaded: 18. March 2019 | + | [[ftp://ftp.gwdg.de/ |
- | [[ftp://ftp.gwdg.de/ | + | Please see install instruction how to get it running on the CPU. |
====crYOLO boxmanager==== | ====crYOLO boxmanager==== | ||
- | Version: 1.2.0 | + | Version: 1.2.2 |
- | Uploaded: | + | Uploaded: |
- | [[ftp:// | + | [[ftp:// |
[{{ : | [{{ : | ||
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=== For cryo images === | === For cryo images === | ||
- | Number of datasets: | + | Number of datasets: |
- | Uploaded: | + | Uploaded: |
- | [[ftp:// | + | [[ftp:// |
|DOWNLOAD]] | |DOWNLOAD]] | ||
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* < | * < | ||
* < | * < | ||
- | * < | + | * < |
+ | * < | ||
+ | * Issue 17: On the fly filtering (%%--%%otf) is slower than using it not, as the filtering is not parallelized in this case. | ||
+ | * < | ||
+ | * < | ||
+ | * < | ||
+ | * < | ||
+ | * < | ||
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**Install crYOLO!** | **Install crYOLO!** | ||
- | The following instructions assume that pip and [[https:// | + | The following instructions assume that pip and [[https:// |
In case you have a old cryolo environment installed, first remove the old one with: | In case you have a old cryolo environment installed, first remove the old one with: | ||
< | < | ||
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After that, create a new virtual environment: | After that, create a new virtual environment: | ||
< | < | ||
- | conda create -n cryolo -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 | + | conda create -n cryolo -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 |
</ | </ | ||
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Install crYOLO: | Install crYOLO: | ||
< | < | ||
- | pip install numpy | + | conda install numpy==1.15.4 |
- | pip install cryolo-X.Y.Z.tar.gz | + | #IN CASE YOU WANT TO INSTALL THE GPU VERSION: |
+ | pip install cryolo-X.Y.Z.tar.gz[gpu] | ||
+ | #IN CASE YOU WANT TO INSTALL THE CPU VERSION: | ||
+ | pip install cryolo-X.Y.Z.tar.gz[cpu] | ||
pip install cryoloBM-X.Y.Z.tar.gz | pip install cryoloBM-X.Y.Z.tar.gz | ||
</ | </ | ||
- | That's it! | + | **That's it!** |
+ | |||
+ | You might want to check if everything is running as expected. Here is a reference example: | ||
+ | |||
+ | [[http:// | ||
===== Run it on the CPU ==== | ===== Run it on the CPU ==== | ||
- | There is also a way to run crYOLO on CPU. This is especially usefull when you would like to apply the generalized model and don't have a NVIDIA GPU. | + | There is also a way to run crYOLO on CPU. To use it, just install the CPU version as provided in the download section. This is especially usefull when you would like to apply the generalized model and don't have a NVIDIA GPU. |
Picking with crYOLO is also quite fast on the CPU. On my local machine (Intel i9) it takes roughly 1 second per micrograph and on our low-performance notebooks (Intel i3) 4 seconds. | Picking with crYOLO is also quite fast on the CPU. On my local machine (Intel i9) it takes roughly 1 second per micrograph and on our low-performance notebooks (Intel i3) 4 seconds. | ||
Training crYOLO is much more computational expensive. Training a model with 14 micrographs from scratch on my local machine take 34 minutes per epoch on the CPU. Given that you often need 25 epochs until convergence it is a task to do overnight (~ 12 hours). However, you might want to try [[pipeline: | Training crYOLO is much more computational expensive. Training a model with 14 micrographs from scratch on my local machine take 34 minutes per epoch on the CPU. Given that you often need 25 epochs until convergence it is a task to do overnight (~ 12 hours). However, you might want to try [[pipeline: | ||
- | |||
- | **Here is how you prepare your crYOLO setup for using it on the CPU:** | ||
- | |||
- | After you followed the crYOLO installation instructions just replace tensorflow-gpu by tensorflow: | ||
- | < | ||
- | pip uninstall tensorflow-gpu | ||
- | pip install tensorflow==1.10.1 | ||
- | </ | ||
- | |||
- | Now crYOLO should work on the CPU as well! | ||
====== Start picking! ====== | ====== Start picking! ====== | ||
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Use the **__'' | Use the **__'' | ||
- | ===== Change log ===== | + | ====== Change log ====== |
====crYOLO==== | ====crYOLO==== | ||
- | **crYOLO 1.3.0:** | + | **crYOLO 1.3.6:** |
- | * Fix Issue 15: -g was ignored when --gpu_fraction was used. | + | * Changed filament search radius factor from 0.8 to 1.41 (this fixed issue 21) |
+ | * Add search radius factor as [[pipeline: | ||
+ | * Improved error message in case of corrupted config file | ||
+ | * Fixed issue 22: If absolute paths are used in the field “train_image” in your configuration file, filtering is skipped. | ||
+ | |||
+ | **crYOLO 1.3.5:** | ||
+ | * Fixed issue 20: During training the images are normalized separately, but during prediction is done batch wise. The lead to confusing results: some micrographs were perfectly picked, some totally unreasonable, | ||
+ | * Remove unnecessary dependencies | ||
+ | * Add %%__%%version%%__%% to %%__%%init%%__%%.py for easy access to package version. | ||
+ | |||
+ | **crYOLO 1.3.4:** | ||
+ | * Support for SPHIRE 1.2 | ||
+ | * Changed the minimum threshold for cbox files from 0.01 to 0.1. Much faster in many cases but still low enough. If -t is lower than 0.1, the new threshold is used as minimum. | ||
+ | * Installation now checks if python 3 is used. | ||
+ | * Fix issue 19: Filtering does not work if target image directory is absolute path. | ||
+ | * Fix crash when %%--%%otf was specified but filtering was not specified in the config file | ||
+ | |||
+ | **crYOLO 1.3.3:** | ||
+ | * Fix issue 18: Prediction is broken in 1.3.2. It removes all particles as it claim they are not fully immersed in the image. | ||
+ | |||
+ | **crYOLO 1.3.2:** | ||
+ | * Speedup prediction: Vectorized some parts of the code and optimized the creation of the cbox files. 30% speed up picking / 15% faster training compared to 1.3.1/ | ||
+ | * Bug fix in merging of filaments that sometimes throw " | ||
+ | * Fix in cryolo_evaluation: | ||
+ | * Change library requirement to PILLOW version 6.0.0 | ||
+ | * Fix issue 16: %%--%%gpu_fraction only works for prediction, not for training. | ||
+ | |||
+ | **crYOLO 1.3.1:** | ||
+ | * Fix Issue 15: -g was ignored when --gpu_fraction was used. | ||
**crYOLO 1.3.0:** | **crYOLO 1.3.0:** | ||
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====crYOLO Boxmanager==== | ====crYOLO Boxmanager==== | ||
+ | **crYOLO Boxmanager Version 1.2.2:** | ||
+ | * Makes sure that the correct version of MatplotLib is used. | ||
+ | |||
+ | **crYOLO Boxmanager Version 1.2.1:** | ||
+ | * Press " | ||
+ | * Fix for loading different box sets with different colors for the case that on of the box sets are cbox files. | ||
+ | |||
**crYOLO Boxmanager Version 1.2: | **crYOLO Boxmanager Version 1.2: | ||
* Add interactive threshold selection using cbox files | * Add interactive threshold selection using cbox files | ||
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==== General PhosaurusNet model ==== | ==== General PhosaurusNet model ==== | ||
+ | **Version 20190516: | ||
+ | * Added four more inhouse datasets | ||
+ | * Added SNRNP (Thanks to Clement Charenton) | ||
+ | |||
**Version 20190315: | **Version 20190315: | ||
* Added KLH | * Added KLH |