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This repository contains the program used to train and evaluate a Branched DNN capable of early-exit semantic segmentation, suited for an edge-cloud co-inference scenario in smart cities..

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Name		Name	Last commit message	Last commit date
Latest commit History 12 Commits
CITATION.cff		CITATION.cff
README.md		README.md
allocate_cuda_device.py		allocate_cuda_device.py
branchy_seg_losses.py		branchy_seg_losses.py
common_torch.py		common_torch.py
compute_mIoU.py		compute_mIoU.py
deepv3_funcs.py		deepv3_funcs.py
ee_dnn_op.py		ee_dnn_op.py
ee_dnn_op_ne.py		ee_dnn_op_ne.py
eval_br_ent.py		eval_br_ent.py
eval_br_images.py		eval_br_images.py
eval_br_sim.py		eval_br_sim.py
eval_flops.py		eval_flops.py
eval_image.py		eval_image.py
eval_mIoU.py		eval_mIoU.py
from_deepv3.py		from_deepv3.py
from_deepv3_new.py		from_deepv3_new.py
funcs.py		funcs.py
get_seg_datasets.py		get_seg_datasets.py
lovaszsoftmax.py		lovaszsoftmax.py
main_bradeepv3.py		main_bradeepv3.py
main_bradeepv3_ce.py		main_bradeepv3_ce.py
module_variables.py		module_variables.py
my_layers.py		my_layers.py
my_pixelwise_xentropy.py		my_pixelwise_xentropy.py
new_seg_losses.py		new_seg_losses.py
seg_metrics.py		seg_metrics.py
sim_metrics.py		sim_metrics.py
train_funcs.py		train_funcs.py

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brandeeplabv3

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This repository contains the program used to train and evaluate a Branched DNN capable of early-exit semantic segmentation, suited for an edge-cloud co-inference scenario in smart cities..

semantic-segmentation edge-computing early-exiting

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