jitdee-ai/darmo

PyTorch image classification models pre-trained

DARMO

Darts family models pre-trained

What's New

May 17, 2023

• Add Vision GNN ImageNet-1k models, Thank from Vision GNN

Feb 2, 2022

• Add AutoFormerV2 ImageNet-1k models, Thank from AutoFormerV2

Oct 6, 2021

• Add PNASNet5 ImageNet-1k models, Thank from PNASNet5

Sep 26, 2021

• Add ResT ImageNet-1k models, Thank from ResT

Sep 20, 2021

• Add OFA-595 ImageNet-1k and ImageNet-21k, Thank from 21k-weight
• Add TResNet-M ImageNet-21k, Thank from 21k-weight

Sep 5, 2021

• Add ResNet50 ImageNet-1k and ImageNet-21k, Thank from 21k-weight

Aug 17, 2021

• Add EEEA-Net-C1 model

Aug 3, 2021

• Add EEEA-Net-C2 model

July 20, 2021

• Add test imagenet sctipt and result

April 5, 2021

• Add NASNet model
• Set params auxiliary

Oct 27, 2020

• Add DARTSv2, PDART, RelativeNAS models

Supported Models

• nasnet
• dartsv2
• pdarts
• relative_nas
• eeea_c1, eeea_c2
• resnet50_1k, resnet50_21k
• ofa595_1k, ofa595_21k
• tresnet_m_21k
• rest_lite, rest_small, rest_base, rest_large
• pnas5
• autoformerv2_tiny, autoformerv2_small, autoformerv2_base
• pvig_ti_224_gelu, pvig_s_224_gelu, pvig_m_224_gelu, pvig_b_224_gelu

Install

The library can be installed with pip:

pip install darmo

Create models

import darmo

# just change -> "dartsv2", "pdarts", "relative_nas", "nasnet", "eeea_c2", "eeea_c1"
model = darmo.create_model("dartsv2", num_classes=1000, pretrained=True, auxiliary=True)

Supported Transfer learning

# create model with ImageNet pretrained
model = darmo.create_model("dartsv2", num_classes=1000, pretrained=True, auxiliary=True)

# Reset classifier layer with add dropout before classifier layer
model.reset_classifier(num_classes=100, dropout=0.2)

Test model on ImageNet

git clone https://github.com/jitdee-ai/darmo/
cd darmo
python test_imagenet.py --arch relative_nas --data [path of imagenet include val folder]

Results of ImageNet

Model	Top-1 Acc	Top-5 Acc
dartsv2	73.59	91.40
pdarts	75.94	92.74
eeea_c1	74.19	91.49
eeea_c2	76.17	92.66

Citations this source code

@software{chakkrit_termritthikun_2020_4139755,
author       = {Chakkrit Termritthikun},
title        = {jitdee-ai/darmo: pre-trained models for darts},
month        = oct,
year         = 2020,
publisher    = {Zenodo},
version      = {0.0.4},
doi          = {10.5281/zenodo.4139755},
url          = {https://doi.org/10.5281/zenodo.4139755}
}