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This version (2019/07/24 13:32) was approved by twagner.The Previously approved version (2019/07/23 10:50) is available.Diff

Testing the release candidate for 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)

As the dependencies changed again, I recommend to use a fresh environmen:

conda env remove --name cryolo

After that, create a new virtual environment:

conda create -n cryolo -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 cython

Activate the environment:

source activate cryolo

Install fast numpy from conda:

conda install numpy==1.14.5

In case you run crYOLO on a GPU run:

pip install 'cryolo[gpu]==1.4.1rc3' 

But if you want to run crYOLO on a CPU run:

pip install 'cryolo[cpu]==1.4.1rc3' 
During the installtion of crYOLO you will see the following error message: ERROR: imagecodecs-lite 2019.2.22 has requirement numpy>=1.15.4, but you'll have numpy 1.14.5 which is incompatible. However, you can ignore it. It is actually also working with numpy==1.14.5

Thats it

cryolo_1_4_1.txt ยท Last modified: 2019/07/24 13:32 by twagner