This shows you the differences between two versions of the page.
Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
downloads:cryolo_1 [2019/07/11 11:25] twagner [General PhosaurusNet models] |
downloads:cryolo_1 [2019/07/29 15:33] twagner [crYOLO boxmanager] |
||
---|---|---|---|
Line 34: | Line 34: | ||
====crYOLO==== | ====crYOLO==== | ||
- | Version: 1.4.0 | + | Version: 1.4.1 |
- | Uploaded: | + | Uploaded: |
- | [[ftp://ftp.gwdg.de/pub/misc/sphire/ | + | [[https://pypi.org/project/cryolo/#files|DOWNLOAD]] |
Please see [[downloads: | Please see [[downloads: | ||
Line 44: | Line 44: | ||
====crYOLO boxmanager==== | ====crYOLO boxmanager==== | ||
- | Version: 1.2.3 | + | Version: 1.2.6 |
- | Uploaded: | + | Uploaded: |
- | [[ftp://ftp.gwdg.de/pub/misc/sphire/ | + | [[https://pypi.org/project/cryoloBM/#files|DOWNLOAD]] |
[{{ : | [{{ : | ||
Line 76: | Line 76: | ||
< | < | ||
- | Plase plas pdlasdas dasd | + | The performance of the general model based on JANNI denoised data compared to low-pass filtered data did not improve. The average AUC on the validation data was in both cases the same (0.85). But this might be because of the data selected for the general model. I assume that especially on very noisy micrographs JANNI will improve the results. |
</ | </ | ||
Line 97: | Line 97: | ||
* Issue 0: Training on multiple GPUs sometimes lead to worse performance (higher loss). We currently recommend to train on single gpus. | * Issue 0: Training on multiple GPUs sometimes lead to worse performance (higher loss). We currently recommend to train on single gpus. | ||
* Issue 17: On the fly filtering (%%--%%otf) is slower than using it not, as the filtering is not parallelized in this case. | * Issue 17: On the fly filtering (%%--%%otf) is slower than using it not, as the filtering is not parallelized in this case. | ||
+ | * Issue 22: Since crYOLO 1.4.0 it sometimes take long until it starts picking. The reason seems to be the tensorflow update. | ||
+ | * Issue 23: Fine-tune mode does not start (cannot find layer model_3). Will be fixed in 1.4.1. | ||
<hidden Closed issues> | <hidden Closed issues> | ||
* < | * < | ||
Line 145: | Line 147: | ||
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 cython | + | conda create -n cryolo -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 |
</ | </ | ||
Line 151: | Line 153: | ||
< | < | ||
source activate cryolo | source activate cryolo | ||
- | </ | ||
- | |||
- | Install fast numpy from conda: | ||
- | < | ||
- | conda install numpy==1.15.4 | ||
</ | </ | ||
In case you run **crYOLO on a GPU** run: | In case you run **crYOLO on a GPU** run: | ||
< | < | ||
- | pip install cryolo-X.Y.Z.tar.gz[gpu] | + | pip install |
</ | </ | ||
But if you want to run **crYOLO on a CPU** run: | But if you want to run **crYOLO on a CPU** run: | ||
< | < | ||
- | pip install cryolo-X.Y.Z.tar.gz[cpu] | + | pip install |
</ | </ | ||
- | Finally | + | < |
- | < | + | During the installtion of crYOLO |
- | pip install cryoloBM-X.Y.Z.tar.gz | + | '' |
- | </code> | + | However, you can ignore it. It is actually also working with numpy==1.14.5 |
+ | </note> | ||
**That' | **That' | ||
Line 194: | Line 192: | ||
====crYOLO==== | ====crYOLO==== | ||
+ | |||
+ | **crYOLO 1.4.1:** | ||
+ | * Downgrade the dependencies to tensorflow 1.10.1 and numpy 1.14.5 as some users reported long initialization times. (Thanks to Shaun Rawson) | ||
+ | * The initialization weights are not longer shipped with the package and downloaded on-the-fly (because they are big and pypi does not allow such big packages) | ||
+ | * crYOLO is installed through pypi | ||
+ | * crYOLO box manager is installed through pypi and automatically shipped with the crYOLO package | ||
+ | * Fix fine-tune mode (Thanks to Antoine Koehl) | ||
+ | * Fixed normalization function for YOLO backend (Thanks to Wolfgang Lugmayr) | ||
+ | |||
+ | <hidden **Old crYOLO change logs**> | ||
**crYOLO 1.4.0:** | **crYOLO 1.4.0:** | ||
Line 201: | Line 209: | ||
* Update numpy from 1.14.5 to 1.15.4 to make crYOLO compatible with JANNI | * Update numpy from 1.14.5 to 1.15.4 to make crYOLO compatible with JANNI | ||
- | <hidden **Old crYOLO change logs**> | ||
**crYOLO 1.3.6:** | **crYOLO 1.3.6:** | ||
* Changed filament search radius factor from 0.8 to 1.41 (this fixed issue 21) | * Changed filament search radius factor from 0.8 to 1.41 (this fixed issue 21) | ||
Line 340: | Line 347: | ||
</ | </ | ||
====crYOLO Boxmanager==== | ====crYOLO Boxmanager==== | ||
- | **crYOLO Boxmanager Version 1.2.3:** | + | **crYOLO Boxmanager Version 1.2.6:** |
* Make it compatible with current new environment | * Make it compatible with current new environment | ||
<hidden **Old crYOLO Boxmanager change logs**> | <hidden **Old crYOLO Boxmanager change logs**> | ||
+ | |||
+ | **crYOLO Boxmanager Version 1.2.3:** | ||
+ | * Make it compatible with current new environment | ||
+ | |||
**crYOLO Boxmanager Version 1.2.2:** | **crYOLO Boxmanager Version 1.2.2:** | ||
* Makes sure that the correct version of MatplotLib is used. | * Makes sure that the correct version of MatplotLib is used. |