Custom dataset

[y0un0]

Hello,
Thank you for sharing your work.
Can you provide the different custom RGB-D dataset (indoor vs outdoor, object scale, background clutter, ...) ?

[taozh2017]

Ok. I will upload them as soon.

[y0un0]

Can you upload it this week ?

[taozh2017]

I have updated it on the readme page:

Attribute-based Evaluation:
Downloading attribute datasets Baidu Drive (Code: tktz) or Google Drive.

Besides, for scale evaluation, just using: obj_size = length(find(gt~=0)) / (size(gt,1)*size(gt,2)), to compute metrics for different sacles.

[y0un0]

Thank you. Just one more question. When you did the training, you trained each model once on a dataset of randomly selected samples (700 from NLPR, 1500 from NJU2K) ? For the testing, you just used the custom datasets without retraining the models right ?

[taozh2017]

Yes, without retraining. y0un0 ***@***.***> 于2021年11月10日周三 下午11:34写道：

…

Thank you. Just one more question. When you did the training, you trained each model once on a dataset of randomly selected samples (700 from NLPR, 1500 from NJU2K) ? For the testing, you just used the custom datasets without retraining the models right ? — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#5 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AHT5QRL6EJO4IJZX4FHIIZTULKGJTANCNFSM5HKG3J4A> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.

-- Best, Tao.

[y0un0]

Ok thank you