downloads:cryolo_1
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downloads:cryolo_1 [2019/05/17 08:29] twagner [crYOLO] |
downloads:cryolo_1 [2019/07/09 19:58] twagner [Run it on the CPU] |
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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:// | ||
| Line 34: | Line 38: | ||
| Uploaded: | Uploaded: | ||
| - | [[ftp:// | + | [[ftp:// |
| - | [[ftp://ftp.gwdg.de/ | + | Please see install instruction how to get it running on the CPU. |
| ====crYOLO boxmanager==== | ====crYOLO boxmanager==== | ||
| Line 52: | Line 56: | ||
| === For cryo images === | === For cryo images === | ||
| - | Number of datasets: 38 real, 10 simulated, 10 particle free datasets on various grids with contaminations | + | Number of datasets: 38 real, 10 simulated, 10 particle free datasets on various grids with contamination |
| Uploaded: 17. May 2019 | Uploaded: 17. May 2019 | ||
| Line 125: | Line 129: | ||
| 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 |
| </ | </ | ||
| Line 135: | Line 139: | ||
| Install crYOLO: | Install crYOLO: | ||
| < | < | ||
| - | conda install numpy==1.14.5 | + | 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 | ||
| </ | </ | ||
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| ===== Run it on the CPU ==== | ===== Run it on the CPU ==== | ||
| - | There is also a way to run crYOLO on CPU. To use it, just install | + | There is also a way to run crYOLO on CPU. To use it, just follow |
| 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. | ||
| Line 164: | Line 172: | ||
| **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) | ||
| - | * Add search radius factor[[pipeline: | + | * Add search radius factor |
| * Improved error message in case of corrupted config file | * 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. | * Fixed issue 22: If absolute paths are used in the field “train_image” in your configuration file, filtering is skipped. | ||
downloads/cryolo_1.txt · Last modified: 2021/02/19 09:43 by twagner
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