Comments (11)
from u-2-net.
Hi @kamalkantamaity
checkout this discussion:
#19 (comment)
I am also have same issues.
from u-2-net.
Hi @kamalkantamaity
checkout this discussion:
#19 (comment)I am also have same issues.
Hi @muhammadabdullah34907 can you tell me how did you solve the issue an also I would like to tell you that I am only looking to make the input size to 640x640 not more than that
from u-2-net.
+1
from u-2-net.
@Nathanua where exactly are you referring to use this ?
from u-2-net.
Hi, Recently, we did literature survey on the high resolution image segmentation. We found that combining our U^2-Net with Cascaded PSPNet (https://github.com/hkchengrex/CascadePSP) is a good option for high resolution image segmentation. The only issue is that cascaded pspnet will cost a bit more time. This combination will perform better than changing the input size and retrain the network.
…
On Sep 16, 2020, at 2:26 AM, Cenk Bircanoğlu @.***> wrote: +1 — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#41 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADSGORLH2I3VAXLZJ4VPY53SGBZB5ANCNFSM4OKBGSSQ.
So what do you mean by with cascadePSP, is the pipeline like this, input size still keeps 320 but using cascadePSP as post-process method, or changes the input size larger and do the following~
Quite interested in this topic, cause still find some error of u-2-net when comparing with other method, e.g hrnet+ocr, which is some kind of plan to do high-resolution image segmentation( two-classes).
from u-2-net.
Have you experimented with the idea, how did it go?
from u-2-net.
from u-2-net.
Thanks for your interest. It depends on the dataset resolution. Larger input size will help with retraining details of those images with larger sizes. In our next paper, we will provide you another model for larger size input. It will be ready soon, please be aware of our updates.
…
On Mon, Dec 13, 2021 at 4:51 PM Jiang Ji @.***> wrote: Have you experimented with the idea, how did it go? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#41 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADSGORK34F7KWJF73V5MXL3UQXT47ANCNFSM4OKBGSSQ . 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.
-- Xuebin Qin PhD Department of Computing Science University of Alberta, Edmonton, AB, Canada Homepage:https://webdocs.cs.ualberta.ca/~xuebin/
Thanks, I made it work and tested on a few examples, it truly works amazing. the only problem is the speed, the u2net step takes less than 1 second on a 6 core CPU, but the CascadePSP step would take at least 15 seconds even when I set fast=False. But still, it's really impressive. looking forward to the new paper ;)
from u-2-net.
Thanks for your interest. It depends on the dataset resolution. Larger input size will help with retraining details of those images with larger sizes. In our next paper, we will provide you another model for larger size input. It will be ready soon, please be aware of our updates.
…
On Mon, Dec 13, 2021 at 4:51 PM Jiang Ji @.***> wrote: Have you experimented with the idea, how did it go? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#41 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADSGORK34F7KWJF73V5MXL3UQXT47ANCNFSM4OKBGSSQ . 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.
-- Xuebin Qin PhD Department of Computing Science University of Alberta, Edmonton, AB, Canada Homepage:https://webdocs.cs.ualberta.ca/~xuebin/Thanks, I made it work and tested on a few examples, it truly works amazing. the only problem is the speed, the u2net step takes less than 1 second on a 6 core CPU, but the CascadePSP step would take at least 15 seconds even when I set fast=False. But still, it's really impressive. looking forward to the new paper ;)
Hi, I looked at you repo . Could not find the code which merges the both. Can you please provide either a Notebook or the code? @jorjiang
from u-2-net.
Thanks for your interest. It depends on the dataset resolution. Larger input size will help with retraining details of those images with larger sizes. In our next paper, we will provide you another model for larger size input. It will be ready soon, please be aware of our updates.
…
On Mon, Dec 13, 2021 at 4:51 PM Jiang Ji @.***> wrote: Have you experimented with the idea, how did it go? — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#41 (comment)>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ADSGORK34F7KWJF73V5MXL3UQXT47ANCNFSM4OKBGSSQ . 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.
-- Xuebin Qin PhD Department of Computing Science University of Alberta, Edmonton, AB, Canada Homepage:https://webdocs.cs.ualberta.ca/~xuebin/Thanks, I made it work and tested on a few examples, it truly works amazing. the only problem is the speed, the u2net step takes less than 1 second on a 6 core CPU, but the CascadePSP step would take at least 15 seconds even when I set fast=False. But still, it's really impressive. looking forward to the new paper ;)
Hi, I looked at you repo . Could not find the code which merges the both. Can you please provide either a Notebook or the code? @jorjiang
hey, was just a quick test on a notebook and i did not save it afterwards, but it's pretty straight forward. you just need to check how those two repos work and feed the output of the u2net into CascadePSP, if you understand the output of u2net and the input of CascadePSP, you can do it
from u-2-net.
Related Issues (20)
- 模型训练时间过长
- 对u2netp模型进行qat量化
- How can I input video or webcam in the test.py script?
- 能否麻烦将整个项目打个包(包含运行文件和预训练模型),集成一个 .bat 文件,点击运行即可使用? HOT 2
- 请问该模型只能输出二分类结果么?可以输出为多分类么?比如三分类 HOT 1
- Is it support person segmentation now? HOT 2
- 如何添加评价指标
- ImportError: cannot import name 'U2NET' from 'model' HOT 2
- Can' Access Human Segmentation Model Weights HOT 1
- Usage on cross platform mobile devices using tenser flow or pytourch ( Special on Flutter )
- 请问大家,我需要前景而非mask,该怎样修改代码呢,感谢
- /alueror: At least one stride in the given numpy aray is mepative, ad tensors with nepative strides are not curently suported. (You can probably work around this by making a copy of your array with array.copy( ).)
- u2net_train.py returning ValueError HOT 1
- the effect of replacing background with U-2-Net is not as expected, anyone can offer a help
- can tell me , label mask must be 0 or 1,if 0 or 1,why binary is smooth, if dataset mask edge in (0,1),it can work? HOT 1
- The results are not good when the object has small holes. HOT 1
- 有什么办法只保留抠图部分尺寸,不需要原图尺寸大小,谢谢 HOT 1
- num_workers=1
- u2net for semantic segmentation
- 自己数据训练的u2net,归一化尺寸320,但是抠图效果边缘锯齿明显
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from u-2-net.