cryolo_1_4_1 []

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=== 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:
<code>
conda env remove --name cryolo
</code>
After that, create a new virtual environment:
<code>
conda create -n cryolo -c anaconda python=3.6 pyqt=5 cudnn=7.1.2 cython
</code>

Activate the environment:
<code>
source activate cryolo
</code>

Install fast numpy from conda:
<code>
conda install numpy==1.14.5
</code>

In case you run **crYOLO on a GPU** run:
<code>
pip install 'cryolo[gpu]==1.4.1rc3' 
</code>

But if you want to run **crYOLO on a CPU** run:
<code>
pip install 'cryolo[cpu]==1.4.1rc3' 
</code>

<note>
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
</note>

**Thats it**
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