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)
- issue about portrait function
- Cannot Import U2NET
- onnx result wrong HOT 5
- [Question] Trained model for proprietary use
- Ai
- RuntimeError: unexpected EOF, The file might be corrupted
- 大佬,可以提供一下验证模型相关指标的代码吗? HOT 1
- RescaleT:Why not prioritize maintaining the aspect ratio
- Hi, when I run this code, I get strange errors in other detection tasks.The following is the warning where the error occurs
- Continue training, train my own model with U-2-Net, in between due to some reasons the training was interrupted or I want to strengthen an existing model, what should I do? Can you provide a 'Continue-training.py'? HOT 4
- Inference speed HOT 1
- 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
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from u-2-net.