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cbst's Issues

simple_bind error

Hello,

Thanks for your great work, I am trying to running your code.
When I try to run
image
when goes into line 806 in solver_ST.py, I meet this error:
image

Have you ever meet same error? or do you have any suggestions to debug?

About the basenet

Sorry to bother you again,I am very interested about your ECCV PAPERDomain Adaptation for Semantic Segmentation via Class-Balanced Self-Training.I found that you have choosed both FCN8s-VGG16,and RESNET-38 as basenet, and this project is based on the RESNET. If I want to reproduce the same result base in FCN8s-VGG16,how can I change your code? It's very pleasant if you can answer me more explicitly since I am a freshman.

About label definition of SYNTHIA

As the label maps in labels_synthia.py and labels_cityscapes_synthia.py show, there is 16 classes in both training and testing phase for SYNTHIA16 settings. And the results in paper show SYNTHIA13 is just evaluated among 13 classes based on SYNTHIA16 results.
I'm just making sure that for SYNTHIA16 and SYNTHIA13, there are 16 classes in training and testing, not 19 or 13. Am I right?

File mine_id.npy and mine_id_priority.npy

I was trying to run the code solve_AO.py . When the subprocess calls the solve_ST.py, it asks for these specific files which I cannot find anywhere in the repo. Can I ask how can I get these files?
image

About label format of GTA

@Chrisding @yzou2, what is the expected format of labels for GTA5 training, source only script? I used the labels.py script in order to transform themt o cityscapes format (valid labels 0-18) and the rest 255. Nevertheless, when i start training i got loss values with NaNs.

Training Problem

Hi, thanks for sharing code! As I follow the tutorial setting , when I run the gta2Cityscapes self-training code, it reports the error as follow. May I get some helpful information from you?

self-training

About the finetuning of self-training

I used your command of
"python issegm/solve_AO.py --num-round 6 --test-scales 1850 --scale-rate-range 0.7,1.3 --dataset gta --dataset-tgt cityscapes --split train --split-tgt val --data-root DATA_ROOT_GTA5 --data-root-tgt DATA_ROOT_CITYSCAPES --output gta2city/cbst --model cityscapes_rna-a1_cls19_s8 --weights models/gta_rna-a1_cls19_s8_ep-0000.params --batch-images 2 --crop-size 500 --origin-size-tgt 2048 --init-tgt-port 0.15 --init-src-port 0.03 --seed-int 0 --mine-port 0.8 --mine-id-number 3 --mine-thresh 0.001 --base-lr 1e-4 --to-epoch 2 --source-sample-policy cumulative --self-training-script issegm/solve_ST.py --kc-policy cb --prefetch-threads 2 --gpus 0 --with-prior False"
in GTA-to-Cityscapes setting and find your code use validation set(cityscapes) instead of training set(cityscapes) to produce pseudo-labels.
Does this accord with your experiment in eccv paper?

SYNTHIA-RAND-CITYSCAPES dataset

Hi, I downloaded SYNTHIA-RAND-CITYSCAPES from the link you provided, but found that the foder doesn't include image and labels. Do you know why? Thanks!

Pytorch version?

Hi, first of all congratulations for the great work. Do you plan to release a Pytorch version of your implementation? Do you have any estimated release date? Thanks in advance

VGG16 code

Thanks for sharing the code! I am just wondering if you could also share the code for vgg16 structure?

BDD-V

Could you provide the link of BDD-V dataset as your discription in the paper ?

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