liamw96 / pytorch.room.layout

room layout estimation pytorch project
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Training and testing (phase val), but how to deploy? #5

Open kabawo opened 5 years ago

kabawo commented 5 years ago

Hello, I have successfully run your code, including images outside of the LSUN dataset. The results are very, very good. One small thing is, that I need to always have corresponding labels for the new images. Is there any way I could run the code in deployment mode? (i.e. It would not compare the size of corresponding directories and search for label.)

liamw96 commented 5 years ago

Thanks for this 'very, very good' comment. It's encouraging. For a deloy mode, it seems that one need to overload the dataloader.

kabawo commented 5 years ago

Ok. Would you be able to point me to more specific direction? If I understand correctly, we are talking about implementing changes in 'segment_rl.py'. Would you be able to add (commit) some comments to the code?

liamw96 commented 5 years ago

https://github.com/louis-she/sfd.pytorch

I think this is a good reference. There is a infer() function @ line 118 of detector.py. It loads an image, subtracts the mean values, and moves it to the gpu. Hope it helps.

chm90 commented 5 years ago

Any progress on this one @kabawo? Mind sharing any code? 😃

kabawo commented 5 years ago

Hello, short answer is: no, no progress coding-wise. I didn't have enough time to learn PyTorch and I needed quick solution, so I've just re-done 'main' as Python module and whole folder into a Python package. After that, I could import it ('main' as function) and use it in my program passing all necessary arguments like from terminal. I also overwrite txt files with the list of images to process. I put them in the lsun folder first. I also left one label image and copy it to create dummy label images, so the count of images==labels is equal. It is very hacky way, but it worked.

The plan, for me, is to learn CNN over the summer and implement Room Layout Estimator in Pytorch myself, probably based on different paper.

I'm writing from a phone, so if this approach would be enough for you, you can ask me for more info and I can paste some code samples, when on PC. Regards.

Hui-Yao commented 3 years ago

Hello, I have successfully run your code, including images outside of the LSUN dataset. The results are very, very good. One small thing is, that I need to always have corresponding labels for the new images. Is there any way I could run the code in deployment mode? (i.e. It would not compare the size of corresponding directories and search for label.)

when i run the code to get the drn-d-105,there are a error:raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden。

Hui-Yao commented 3 years ago

when i run the code to get the drn-d-105,there are a error:raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden。could you tell me how to solve it

kabawo commented 3 years ago

when i run the code to get the drn-d-105,there are a error:raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden。could you tell me how to solve it

When you try to download a pre-trained model from 'https://tigress-web.princeton.edu/~fy/drn/models/', it is no longer available on their website.

huangshizhong commented 3 years ago

when i run the code to get the drn-d-105,there are a error:raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden。could you tell me how to solve it

When you try to download a pre-trained model from 'https://tigress-web.princeton.edu/~fy/drn/models/', it is no longer available on their website.

i have the same problem,i don't know how to solve the problem:when i run the code to get the drn-d-105,there are a error:raise HTTPError(req.full_url, code, msg, hdrs, fp) urllib.error.HTTPError: HTTP Error 403: Forbidden。,can you tell me how to solve it

maheshmechengg commented 1 year ago

Thanks Guys, this was helpful & i was able to get output for my image too! & results are really good. Thanks kabawo & pytorch.room.layout guys!