cryolo_1_4

Testing the release candidate for 1.4.1

Changes:

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