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b312e796d6
## Motivation Introducing new models and features into OpenMMLab's algorithm libraries has long been complained to be troublesome due to the rigorous requirements on code quality, which could hinder the fast iteration of SOTA models and might discourage potential contributors from sharing their latest outcome here. Ref: https://github.com/open-mmlab/mmsegmentation/pull/2412 ## Modification This PR adds a new `projects/` folder, which will be a place for some experimental models/features. Implementations inside might be not quite perfect but already fine to produce some exciting results. We hope that this PR can help us better embrace the contribution from our community. We also add the first example project to illustrate what we expect a good project to have.
16 lines
451 B
Python
16 lines
451 B
Python
# Copyright (c) OpenMMLab. All rights reserved.
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from mmseg.models import BACKBONES
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from mmseg.models.backbones import ResNetV1c
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@BACKBONES.register_module()
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class DummyResNet(ResNetV1c):
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"""Implements a dummy ResNet wrapper for demonstration purpose.
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Args:
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**kwargs: All the arguments are passed to the parent class.
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"""
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def __init__(self, **kwargs) -> None:
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print('Hello world!')
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super().__init__(**kwargs)
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