traning on multi-objects images [ more than one object ]

[gaebw]

Hi Xuebin Qin,
Great work. Thanks.
Questions 1: Is it ok to build model/train on multi-object images? or it has to be images with one object each?

Question 2: Training on Windows 10 failed message:
DIS\IS-Net>python train_valid_inference_main.py

building model...
batch size: 8
--- create training dataloader ---
------------------------------ train --------------------------------
--->>> train dataset 0 / 1 DIS5K-TR <<<---
-im- DIS5K-TR ../DIS5K/DIS-TR/im : 959
-gt- DIS5K-TR ../DIS5K/DIS-TR/gt : 959
Traceback (most recent call last):
File "train_valid_inference_main.py", line 722, in
main(train_datasets,
File "train_valid_inference_main.py", line 527, in main
train_dataloaders, train_datasets = create_dataloaders(train_nm_im_gt_list,
File DIS\IS-Net\data_loader_cache.py", line 95, in create_dataloaders
gos_dataloaders.append(DataLoader(gos_dataset, batch_size=batch_size, shuffle=shuffle, num_workers=num_workers_))
File "Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 268, in init
sampler = RandomSampler(dataset, generator=generator)
File "Anaconda3\lib\site-packages\torch\utils\data\sampler.py", line 102, in init
raise ValueError("num_samples should be a positive integer "
ValueError: num_samples should be a positive integer value, but got num_samples=0

Thanks,
Gabew

[xuebinqin]

Hello, thanks for your interest. The model itself should be able to handle multiple object segmentation. But the output will still be binary and objects will not be separated. As for the error, I think you need to change the data path from "../DIS5K/DIS-TR/im" to e.g., "D\\DIS5K\\DIS-TR\\TR", where windows use different os.sep with ubuntu.

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On Thu, Aug 11, 2022 at 7:56 AM gaebw ***@***.***> wrote: Hi Xuebin Qin, Great work. Thanks. Questions 1: Is it ok to build model/train on multi-object images? or it has to be images with one object each? Question 2: Training on Windows 10 failed message: DIS\IS-Net>python train_valid_inference_main.py building model... batch size: 8 --- create training dataloader --- ------------------------------ train -------------------------------- --->>> train dataset 0 / 1 DIS5K-TR <<<--- -im- DIS5K-TR ../DIS5K/DIS-TR/im : 959 -gt- DIS5K-TR ../DIS5K/DIS-TR/gt : 959 Traceback (most recent call last): File "train_valid_inference_main.py", line 722, in main(train_datasets, File "train_valid_inference_main.py", line 527, in main train_dataloaders, train_datasets = create_dataloaders(train_nm_im_gt_list, File DIS\IS-Net\data_loader_cache.py", line 95, in create_dataloaders gos_dataloaders.append(DataLoader(gos_dataset, batch_size=batch_size, shuffle=shuffle, num_workers=num_workers_)) File "Anaconda3\lib\site-packages\torch\utils\data\dataloader.py", line 268, in *init* sampler = RandomSampler(dataset, generator=generator) File "Anaconda3\lib\site-packages\torch\utils\data\sampler.py", line 102, in *init* raise ValueError("num_samples should be a positive integer " ValueError: num_samples should be a positive integer value, but got num_samples=0 Thanks, Gabew — Reply to this email directly, view it on GitHub <#26>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ADSGORJMIPZVM3LANPUFYJDVYUIALANCNFSM56IPPHZA> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

-- Xuebin Qin PhD Department of Computing Science University of Alberta, Edmonton, AB, Canada Homepage: https://xuebinqin.github.io/