Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Evaluation batch inference with same image size #2965

Open
mmeendez8 opened this issue Apr 28, 2023 · 3 comments
Open

Evaluation batch inference with same image size #2965

mmeendez8 opened this issue Apr 28, 2023 · 3 comments
Assignees

Comments

@mmeendez8
Copy link
Contributor

I understand the problematic of batch inference with different image sizes. But we should be able to do this on a dataset with constant image size. Is there any plan of supporting this feature?

@irabanillo91
Copy link

I agree, I find it quite limiting not being able to run inference on batches since it slows down a lot the processing in production. Would it be possible to remove this assert and let the user deal with it?

@edsml-hmc122
Copy link

Any update on this?

@joihn
Copy link

joihn commented Jul 13, 2023

l also feel like this is a big limitation. My workflow involve a validation epoch after each train epoch, and with batch_size=1 it is quite slow.

One workaround is to write my own CustomSegDataPreProcessor class which will be inherited from SegDataPreProcessor

xiexinch added a commit that referenced this issue Jul 20, 2023
Thanks for your contribution and we appreciate it a lot. The following
instructions would make your pull request more healthy and more easily
get feedback. If you do not understand some items, don't worry, just
make the pull request and seek help from maintainers.

## Motivation

#3181
#2965
#2644
#1645
#1444
#1370
#125

## Modification

Remove the assertion at data_preprocessor

## BC-breaking (Optional)

Does the modification introduce changes that break the
backward-compatibility of the downstream repos?
If so, please describe how it breaks the compatibility and how the
downstream projects should modify their code to keep compatibility with
this PR.

## Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases
here, and update the documentation.

## Checklist

1. Pre-commit or other linting tools are used to fix the potential lint
issues.
2. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
4. The documentation has been modified accordingly, like docstring or
example tutorials.
nahidnazifi87 pushed a commit to nahidnazifi87/mmsegmentation_playground that referenced this issue Apr 5, 2024
Thanks for your contribution and we appreciate it a lot. The following
instructions would make your pull request more healthy and more easily
get feedback. If you do not understand some items, don't worry, just
make the pull request and seek help from maintainers.

## Motivation

open-mmlab#3181
open-mmlab#2965
open-mmlab#2644
open-mmlab#1645
open-mmlab#1444
open-mmlab#1370
open-mmlab#125

## Modification

Remove the assertion at data_preprocessor

## BC-breaking (Optional)

Does the modification introduce changes that break the
backward-compatibility of the downstream repos?
If so, please describe how it breaks the compatibility and how the
downstream projects should modify their code to keep compatibility with
this PR.

## Use cases (Optional)

If this PR introduces a new feature, it is better to list some use cases
here, and update the documentation.

## Checklist

1. Pre-commit or other linting tools are used to fix the potential lint
issues.
2. The modification is covered by complete unit tests. If not, please
add more unit test to ensure the correctness.
3. If the modification has potential influence on downstream projects,
this PR should be tested with downstream projects, like MMDet or
MMDet3D.
4. The documentation has been modified accordingly, like docstring or
example tutorials.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

5 participants