You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
120 lines
3.5 KiB
120 lines
3.5 KiB
3 years ago
|
# Gluon ResNeXt
|
||
3 years ago
|
|
||
|
|
A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations) $C$, as an essential factor in addition to the dimensions of depth and width.
|
||
|
|
|
||
|
3 years ago
|
The weights from this model were ported from [Gluon](https://cv.gluon.ai/model_zoo/classification.html).
|
||
|
3 years ago
|
|
||
|
|
{% include 'code_snippets.md' %}
|
||
|
|
|
||
|
|
## How do I train this model?
|
||
|
|
|
||
|
|
You can follow the [timm recipe scripts](https://rwightman.github.io/pytorch-image-models/scripts/) for training a new model afresh.
|
||
|
|
|
||
|
|
## Citation
|
||
|
|
|
||
|
|
```BibTeX
|
||
|
|
@article{DBLP:journals/corr/XieGDTH16,
|
||
|
|
author = {Saining Xie and
|
||
|
|
Ross B. Girshick and
|
||
|
|
Piotr Doll{\'{a}}r and
|
||
|
|
Zhuowen Tu and
|
||
|
|
Kaiming He},
|
||
|
|
title = {Aggregated Residual Transformations for Deep Neural Networks},
|
||
|
|
journal = {CoRR},
|
||
|
|
volume = {abs/1611.05431},
|
||
|
|
year = {2016},
|
||
|
|
url = {http://arxiv.org/abs/1611.05431},
|
||
|
|
archivePrefix = {arXiv},
|
||
|
|
eprint = {1611.05431},
|
||
|
|
timestamp = {Mon, 13 Aug 2018 16:45:58 +0200},
|
||
|
|
biburl = {https://dblp.org/rec/journals/corr/XieGDTH16.bib},
|
||
|
|
bibsource = {dblp computer science bibliography, https://dblp.org}
|
||
|
|
}
|
||
|
|
```
|
||
|
|
|
||
|
|
<!--
|
||
|
|
Models:
|
||
|
|
- Name: gluon_resnext50_32x4d
|
||
|
|
Metadata:
|
||
|
|
FLOPs: 5472648192
|
||
|
|
Training Data:
|
||
|
|
- ImageNet
|
||
|
|
Architecture:
|
||
|
|
- 1x1 Convolution
|
||
|
|
- Batch Normalization
|
||
|
|
- Convolution
|
||
|
|
- Global Average Pooling
|
||
|
|
- Grouped Convolution
|
||
|
|
- Max Pooling
|
||
|
|
- ReLU
|
||
|
|
- ResNeXt Block
|
||
|
|
- Residual Connection
|
||
|
|
- Softmax
|
||
|
|
File Size: 100441719
|
||
|
|
Tasks:
|
||
|
|
- Image Classification
|
||
|
|
ID: gluon_resnext50_32x4d
|
||
|
|
Crop Pct: '0.875'
|
||
|
|
Image Size: '224'
|
||
|
|
Interpolation: bicubic
|
||
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/gluon_resnet.py#L185
|
||
|
|
In Collection: Gloun ResNeXt
|
||
|
|
- Name: gluon_resnext101_32x4d
|
||
|
|
Metadata:
|
||
|
|
FLOPs: 10298145792
|
||
|
|
Training Data:
|
||
|
|
- ImageNet
|
||
|
|
Architecture:
|
||
|
|
- 1x1 Convolution
|
||
|
|
- Batch Normalization
|
||
|
|
- Convolution
|
||
|
|
- Global Average Pooling
|
||
|
|
- Grouped Convolution
|
||
|
|
- Max Pooling
|
||
|
|
- ReLU
|
||
|
|
- ResNeXt Block
|
||
|
|
- Residual Connection
|
||
|
|
- Softmax
|
||
|
|
File Size: 177367414
|
||
|
|
Tasks:
|
||
|
|
- Image Classification
|
||
|
|
ID: gluon_resnext101_32x4d
|
||
|
|
Crop Pct: '0.875'
|
||
|
|
Image Size: '224'
|
||
|
|
Interpolation: bicubic
|
||
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/gluon_resnet.py#L193
|
||
|
|
In Collection: Gloun ResNeXt
|
||
|
|
- Name: gluon_resnext101_64x4d
|
||
|
|
Metadata:
|
||
|
|
FLOPs: 19954172928
|
||
|
|
Training Data:
|
||
|
|
- ImageNet
|
||
|
|
Architecture:
|
||
|
|
- 1x1 Convolution
|
||
|
|
- Batch Normalization
|
||
|
|
- Convolution
|
||
|
|
- Global Average Pooling
|
||
|
|
- Grouped Convolution
|
||
|
|
- Max Pooling
|
||
|
|
- ReLU
|
||
|
|
- ResNeXt Block
|
||
|
|
- Residual Connection
|
||
|
|
- Softmax
|
||
|
|
File Size: 334737852
|
||
|
|
Tasks:
|
||
|
|
- Image Classification
|
||
|
|
ID: gluon_resnext101_64x4d
|
||
|
|
Crop Pct: '0.875'
|
||
|
|
Image Size: '224'
|
||
|
|
Interpolation: bicubic
|
||
|
|
Code: https://github.com/rwightman/pytorch-image-models/blob/d8e69206be253892b2956341fea09fdebfaae4e3/timm/models/gluon_resnet.py#L201
|
||
|
|
In Collection: Gloun ResNeXt
|
||
|
|
Collections:
|
||
|
|
- Name: Gloun ResNeXt
|
||
|
|
Paper:
|
||
|
|
title: Aggregated Residual Transformations for Deep Neural Networks
|
||
|
3 years ago
|
url: https://paperswithcode.com//paper/aggregated-residual-transformations-for-deep
|
||
|
3 years ago
|
type: model-index
|
||
|
|
Type: model-index
|
||
|
|
-->
|