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View Code? Open in Web Editor NEWCode for <Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training> in ECCV18
License: Other
Code for <Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training> in ECCV18
License: Other
Hi,@yzou2,saving confidence scores of target domain as class-wise vectors as the type of numpy, Isn’t it too big? In my experiment, the cpu utilization reached 200% and it was never unable to continue.
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?
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?
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!
I found that your source model of gta is corrupted. Can you check it and provide the completed one?
https://www.dropbox.com/s/idnnk398hf6u3x9/gta_rna-a1_cls19_s8_ep-0000.params?dl=0
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
@yzou2
Are your results of cityscapes from validation set or test set?
Thanks for sharing the code! I am just wondering if you could also share the code for vgg16 structure?
@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.
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.
Hi, I am encountering difficulties in downloading the dataset from the provided links on this website: https://synthia-dataset.net/downloads/. I have tried accessing the download links multiple times, but unfortunately, they seem to be inactive or not working properly.
Could you please provide guidance on how I can download the dataset?
Could you provide the link of BDD-V dataset as your discription in the paper ?
Hi @yzou2 , Can you provide script for prior array generation. Thanks!!
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