Improved pretrained weights usage

[C-Achard]

• Incompatible weights in training are now ignored
• If weights already exist, the download step is skipped

Further improvements that could be made:

• Show the expected size of the images from the weights that were downloaded (extract from .pth or manually ?)
• Add an "always update weights" toggle to allow people to update their local weights easily

[codecov-commenter]

Codecov Report

Merging #24 (487560d) into main (1709528) will decrease coverage by 0.17%.
The diff coverage is 18.60%.

@@            Coverage Diff             @@
##             main      #24      +/-   ##
==========================================
- Coverage   37.51%   37.34%   -0.18%     
==========================================
  Files          37       37              
  Lines        3417     3449      +32     
==========================================
+ Hits         1282     1288       +6     
- Misses       2135     2161      +26     

Impacted Files	Coverage Δ
napari_cellseg3d/models/model_SegResNet.py	45.45% <ø> (ø)
napari_cellseg3d/models/model_TRAILMAP.py	27.08% <ø> (ø)
napari_cellseg3d/models/model_VNet.py	42.85% <ø> (ø)
napari_cellseg3d/plugin_model_inference.py	0.00% <0.00%> (ø)
napari_cellseg3d/plugin_model_training.py	63.36% <0.00%> (-0.17%)	⬇️
napari_cellseg3d/utils.py	33.05% <ø> (ø)
napari_cellseg3d/model_workers.py	16.13% <18.18%> (+0.03%)	⬆️
napari_cellseg3d/log_utility.py	29.78% <25.00%> (+0.51%)	⬆️

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[deprecated-napari-hub-preview-bot]

Preview page for your plugin is ready here:
https://preview.napari-hub.org/AdaptiveMotorControlLab/CellSeg3d/24
Created: 2022-07-18T14:59:30.290868