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forked from megk96/multispectral-maskrcnn

The goal of this project is to ascertain the role of intensity and depth channels in instance segmentation of traffic signs. It has been shown that secondary channels, like intensity and depth, provide complementary information to the neural net and can thus boost the efficiency of a model. The project aims to explore the ramifications of experi…

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weicrane/multispectral-maskrcnn

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alplab.py

alplab.py

 
 

cityscapes.py

cityscapes.py

 
 

cityscapes_create_tfrecords.py

cityscapes_create_tfrecords.py

 
 

create_a9_lassnitzhoehe_from_shape_tsl_tf_record.py

create_a9_lassnitzhoehe_from_shape_tsl_tf_record.py

 
 

depth-intensity.py

depth-intensity.py

 
 

final-mask-lines.py

final-mask-lines.py

 
 

mask-lines.py

mask-lines.py

 
 

project_shp_to_instance_image.py

project_shp_to_instance_image.py

 
 

shapefile-projection.py

shapefile-projection.py

 
 

shp_rgbdi.py

shp_rgbdi.py

 
 

signs_from_shpfile.py

signs_from_shpfile.py

 
 

warp-image.py

warp-image.py

 
 

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The goal of this project is to ascertain the role of intensity and depth channels in instance segmentation of traffic signs. It has been shown that secondary channels, like intensity and depth, provide complementary information to the neural net and can thus boost the efficiency of a model. The project aims to explore the ramifications of experi…

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  • Python 100.0%