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Image classification and segmentation models for PyTorch

Project description

Computer vision models on PyTorch

PyPI Downloads

This is a collection of image classification, segmentation, detection, and pose estimation models. Many of them are pretrained on ImageNet-1K, CIFAR-10/100, SVHN, CUB-200-2011, Pascal VOC2012, ADE20K, Cityscapes, and COCO datasets and loaded automatically during use. All pretrained models require the same ordinary normalization. Scripts for training/evaluating/converting models are in the imgclsmob repo.

List of implemented models

Installation

To use the models in your project, simply install the pytorchcv package with torch (>=0.4.1 is recommended):

pip install pytorchcv torch>=0.4.0

To enable/disable different hardware supports such as GPUs, check out PyTorch installation instructions.

Usage

Example of using a pretrained ResNet-18 model:

from pytorchcv.model_provider import get_model as ptcv_get_model
import torch
from torch.autograd import Variable

net = ptcv_get_model("resnet18", pretrained=True)
x = Variable(torch.randn(1, 3, 224, 224))
y = net(x)

Pretrained models

ImageNet-1K

Some remarks:

  • Top1/Top5 are the standard 1-crop Top-1/Top-5 errors (in percents) on the validation subset of the ImageNet-1K dataset.
  • FLOPs/2 is the number of FLOPs divided by two to be similar to the number of MACs.
  • Remark Converted from GL model means that the model was trained on MXNet/Gluon and then converted to PyTorch.
  • You may notice that quality estimations are quite different from ones for the corresponding models in other frameworks. This is due to the fact that the quality is estimated on the standard TorchVision stack of image transformations. Using OpenCV Resize transformation instead of PIL one quality evaluation results will be similar to ones for the Gluon models.
  • ResNet(A) is an average downsampled ResNet intended for use as an feature extractor in some pose estimation networks.
  • ResNet(D) is a dilated ResNet intended for use as an feature extractor in some segmentation networks.
  • Models with *-suffix use non-standard preprocessing (see the training log).
Model Top1 Top5 Params FLOPs/2 Remarks
AlexNet 38.50 16.64 62,378,344 1,132.33M Converted from GL model (log)
AlexNet-b 39.74 17.47 61,100,840 714.83M Converted from GL model (log)
ZFNet 39.79 17.27 62,357,608 1,170.33M Converted from GL model (log)
ZFNet-b 36.37 14.90 107,627,624 2,479.13M Converted from GL model (log)
VGG-11 29.90 10.36 132,863,336 7,615.87M Converted from GL model (log)
VGG-13 28.76 9.75 133,047,848 11,317.65M Converted from GL model (log)
VGG-16 26.98 8.65 138,357,544 15,480.10M Converted from GL model (log)
VGG-19 25.74 7.90 143,667,240 19,642.55M Converted from GL model (log)
BN-VGG-11 29.01 9.61 132,866,088 7,630.21M Converted from GL model (log)
BN-VGG-13 27.83 9.13 133,050,792 11,341.62M Converted from GL model (log)
BN-VGG-16 25.72 7.79 138,361,768 15,506.38M Converted from GL model (log)
BN-VGG-19 24.13 7.12 143,672,744 19,671.15M Converted from GL model (log)
BN-VGG-11b 29.56 9.96 132,868,840 7,630.72M Converted from GL model (log)
BN-VGG-13b 28.47 9.24 133,053,736 11,342.14M Converted from GL model (log)
BN-VGG-16b 25.97 7.95 138,365,992 15,507.20M Converted from GL model (log)
BN-VGG-19b 25.13 7.46 143,678,248 19,672.26M Converted from GL model (log)
BN-Inception 25.37 7.74 11,295,240 2,048.06M Converted from GL model (log)
ResNet-10 32.76 12.93 5,418,792 894.04M Converted from GL model (log)
ResNet-12 32.10 12.23 5,492,776 1,126.25M Converted from GL model (log)
ResNet-14 30.51 11.09 5,788,200 1,357.94M Converted from GL model (log)
ResNet-BC-14b 29.43 10.74 10,064,936 1,479.12M Converted from GL model (log)
ResNet-16 28.74 10.09 6,968,872 1,589.34M Converted from GL model (log)
ResNet-18 x0.25 39.62 17.85 3,937,400 270.94M Converted from GL model (log)
ResNet-18 x0.5 33.80 13.27 5,804,296 608.70M Converted from GL model (log)
ResNet-18 x0.75 30.40 11.06 8,476,056 1,129.45M Converted from GL model (log)
ResNet-18 26.94 8.96 11,689,512 1,820.41M Converted from GL model (log)
ResNet-26 26.16 8.49 17,960,232 2,746.79M Converted from GL model (log)
ResNet-BC-26b 25.09 7.97 15,995,176 2,356.67M Converted from GL model (log)
ResNet-34 24.84 7.80 21,797,672 3,672.68M Converted from GL model (log)
ResNet-BC-38b 23.69 7.00 21,925,416 3,234.21M Converted from GL model (log)
ResNet-50 22.28 6.33 25,557,032 3,877.95M Converted from GL model (log)
ResNet-50b 22.39 6.38 25,557,032 4,110.48M Converted from GL model (log)
ResNet-101 20.79 5.40 44,549,160 7,597.95M Converted from GL model (log)
ResNet-101b 20.59 5.30 44,549,160 7,830.48M Converted from GL model (log)
ResNet-152 19.29 4.68 60,192,808 11,321.85M Converted from GL model (log)
ResNet-152b 19.01 4.45 60,192,808 11,554.38M Converted from GL model (log)
PreResNet-10 35.11 14.21 5,417,128 894.19M Converted from GL model (log)
PreResNet-12 33.86 13.48 5,491,112 1,126.40M Converted from GL model (log)
PreResNet-14 32.64 12.39 5,786,536 1,358.09M Converted from GL model (log)
PreResNet-BC-14b 31.29 11.81 10,057,384 1,476.62M Converted from GL model (log)
PreResNet-16 30.53 11.08 6,967,208 1,589.49M Converted from GL model (log)
PreResNet-18 x0.25 40.06 18.11 3,935,960 270.93M Converted from GL model (log)
PreResNet-18 x0.5 34.00 13.40 5,802,440 608.73M Converted from GL model (log)
PreResNet-18 x0.75 30.23 11.05 8,473,784 1,129.51M Converted from GL model (log)
PreResNet-18 28.43 9.72 11,687,848 1,820.56M Converted from GL model (log)
PreResNet-26 26.33 8.51 17,958,568 2,746.94M Converted from GL model (log)
PreResNet-BC-26b 25.48 8.03 15,987,624 2,354.16M Converted from GL model (log)
PreResNet-34 24.89 7.74 21,796,008 3,672.83M Converted from GL model (log)
PreResNet-BC-38b 22.92 6.57 21,917,864 3,231.70M Converted from GL model (log)
PreResNet-50 22.40 6.47 25,549,480 3,875.44M Converted from GL model (log)
PreResNet-50b 22.51 6.55 25,549,480 4,107.97M Converted from GL model (log)
PreResNet-101 20.81 5.63 44,541,608 7,595.44M Converted from GL model (log)
PreResNet-101b 21.04 5.56 44,541,608 7,827.97M Converted from GL model (log)
PreResNet-152 19.36 4.64 60,185,256 11,319.34M Converted from GL model (log)
PreResNet-152b 19.23 4.59 60,185,256 11,551.87M Converted from GL model (log)
PreResNet-200b 19.07 4.68 64,666,280 15,068.63M Converted from GL model (log)
PreResNet-269b 20.35 5.27 102,065,832 20,101.11M Converted from GL model (log)
ResNeXt-14 (16x4d) 31.94 12.48 7,127,336 1,045.77M Converted from GL model (log)
ResNeXt-14 (32x2d) 32.58 12.81 7,029,416 1,031.32M Converted from GL model (log)
ResNeXt-14 (32x4d) 30.32 11.46 9,411,880 1,603.46M Converted from GL model (log)
ResNeXt-26 (32x2d) 26.63 8.87 9,924,136 1,461.06M Converted from GL model (log)
ResNeXt-26 (32x4d) 24.14 7.46 15,389,480 2,488.07M Converted from GL model (log)
ResNeXt-50 (32x4d) 21.08 5.60 25,028,904 4,255.86M Converted from GL model (log)
ResNeXt-101 (32x4d) 18.78 4.34 44,177,704 8,003.45M Converted from GL model (log)
ResNeXt-101 (64x4d) 19.08 4.52 83,455,272 15,500.27M Converted from GL model (log)
SE-ResNet-10 31.76 12.02 5,463,332 894.27M Converted from GL model (log)
SE-ResNet-12 31.93 12.00 5,537,896 1,126.58M Converted from GL model (log)
SE-ResNet-14 30.73 11.28 5,835,504 1,358.33M Converted from GL model (log)
SE-ResNet-16 28.72 9.98 7,024,640 1,589.76M Converted from GL model (log)
SE-ResNet-18 28.18 9.61 11,778,592 1,820.88M Converted from GL model (log)
SE-ResNet-26 25.67 8.24 18,093,852 2,747.49M Converted from GL model (log)
SE-ResNet-BC-26b 23.59 7.03 17,395,976 2,359.58M Converted from GL model (log)
SE-ResNet-BC-38b 21.60 5.95 24,026,616 3,238.58M Converted from GL model (log)
SE-ResNet-50 21.22 5.75 28,088,024 3,883.25M Converted from GL model (log)
SE-ResNet-50b 20.79 5.39 28,088,024 4,115.78M Converted from GL model (log)
SE-ResNet-101 19.24 4.60 49,326,872 7,602.76M Converted from GL model (log)
SE-ResNet-101b 19.70 4.87 49,326,872 7,839.75M Converted from GL model (log)
SE-ResNet-152 18.72 4.39 66,821,848 11,328.52M Converted from GL model (log)
SE-PreResNet-10 32.83 12.57 5,461,668 894.42M Converted from GL model (log)
SE-PreResNet-12 32.07 12.03 5,536,232 1,126.73M Converted from GL model (log)
SE-PreResNet-16 28.77 9.75 7,022,976 1,589.91M Converted from GL model (log)
SE-PreResNet-18 27.43 9.09 11,776,928 1,821.03M Converted from GL model (log)
SE-PreResNet-26 26.20 8.22 18,092,188 2,747.64M Converted from GL model (log)
SE-PreResNet-BC-26b 23.22 6.60 17,388,424 2,357.07M Converted from GL model (log)
SE-PreResNet-BC-38b 21.60 5.78 24,019,064 3,236.07M Converted from GL model (log)
SE-PreResNet-50b 20.85 5.49 28,080,472 4,113.27M Converted from GL model (log)
SE-ResNeXt-50 (32x4d) 18.94 4.51 27,559,896 4,261.16M Converted from GL model (log)
SE-ResNeXt-101 (32x4d) 19.36 4.67 48,955,416 8,012.73M Converted from GL model (log)
SE-ResNeXt-101 (64x4d) 18.66 4.28 88,232,984 15,509.54M Converted from GL model (log)
SENet-16 25.65 8.20 31,366,168 5,081.30M Converted from GL model (log)
SENet-28 21.94 5.98 36,453,768 5,732.71M Converted from GL model (log)
SENet-154 18.85 4.55 115,088,984 20,745.78M Converted from GL model (log)
ResNeSt(A)-BC-14 22.46 6.47 10,611,688 2,767.37M Converted from GL model (log)
ResNeSt(A)-18 23.68 7.07 12,763,784 2,587.50M Converted from GL model (log)
ResNeSt(A)-BC-26 19.56 4.76 17,069,448 3,646.57M Converted from GL model (log)
ResNeSt(A)-50 19.00 4.49 27,483,240 5,403.11M Converted from GL model (log)
ResNeSt(A)-101 17.83 4.03 48,275,016 10,247.88M From dmlc/gluon-cv (log)
ResNeSt(A)-152 18.87 4.63 65,316,040 13,976.34M Converted from GL model (log)
ResNeSt(A)-200 16.87 3.39 70,201,544 22,857.88M From dmlc/gluon-cv (log)
ResNeSt(A)-269 16.47 3.38 110,929,480 46,012.95M From dmlc/gluon-cv (log)
IBN-ResNet-50 21.61 5.76 25,557,032 4,110.48M Converted from GL model (log)
IBN-ResNet-101 19.97 5.07 44,549,160 7,830.48M Converted from GL model (log)
IBN(b)-ResNet-50 21.79 5.97 25,558,568 4,112.89M Converted from GL model (log)
IBN-ResNeXt-101 (32x4d) 20.10 5.12 44,177,704 8,003.45M Converted from GL model (log)
IBN-DenseNet-121 23.58 6.73 7,978,856 2,872.13M Converted from GL model (log)
IBN-DenseNet-169 22.42 6.19 14,149,480 3,403.89M Converted from GL model (log)
AirNet50-1x64d (r=2) 20.63 5.32 27,425,864 4,772.11M Converted from GL model (log)
AirNet50-1x64d (r=16) 21.24 5.60 25,714,952 4,399.97M Converted from GL model (log)
AirNeXt50-32x4d (r=2) 20.14 5.15 27,604,296 5,339.58M Converted from GL model (log)
BAM-ResNet-50 20.91 5.47 25,915,099 4,196.09M Converted from GL model (log)
CBAM-ResNet-50 20.17 5.05 28,089,624 4,116.97M Converted from GL model (log)
SCNet-50 21.22 5.47 25,564,584 3,951.06M Converted from GL model (log)
SCNet-101 19.91 4.84 44,565,416 7,204.24M Converted from GL model (log)
SCNet(A)-50 19.53 4.68 25,583,816 4,715.84M From MCG-NKU/SCNet (log)
RegNetX-200MF 30.20 10.66 2,684,792 203.33M Converted from GL model (log)
RegNetX-400MF 26.44 8.66 5,157,512 403.45M Converted from GL model (log)
RegNetX-600MF 24.96 7.91 6,196,040 608.37M Converted from GL model (log)
RegNetX-800MF 24.21 7.40 7,259,656 809.49M Converted from GL model (log)
RegNetX-1.6GF 22.44 6.37 9,190,136 1,618.99M Converted from GL model (log)
RegNetX-3.2GF 21.48 5.92 15,296,552 3,199.55M Converted from GL model (log)
RegNetX-4.0GF 19.69 4.88 22,118,248 3,986.29M Converted from GL model (log)
RegNetX-6.4GF 19.50 4.68 26,209,256 6,491.01M Converted from GL model (log)
RegNetX-8.0GF 19.75 4.86 39,572,648 8,017.94M Converted from GL model (log)
RegNetX-12GF 20.02 5.32 46,106,056 12,124.22M Converted from GL model (log)
RegNetX-16GF 19.29 4.77 54,278,536 15,986.64M Converted from GL model (log)
RegNetX-32GF 18.00 4.13 107,811,560 31,790.24M Converted from GL model (log)
RegNetY-200MF 28.66 9.80 3,162,996 203.99M Converted from GL model (log)
RegNetY-400MF 25.02 7.69 4,344,144 410.35M Converted from GL model (log)
RegNetY-600MF 23.79 7.12 6,055,160 610.37M Converted from GL model (log)
RegNetY-800MF 22.67 6.60 6,263,168 808.62M Converted from GL model (log)
RegNetY-1.6GF 21.41 5.81 11,202,430 1,629.48M Converted from GL model (log)
RegNetY-3.2GF 18.04 4.04 19,436,338 3,199.15M From rwightman/pyt...models (log)
RegNetY-4.0GF 19.56 4.70 20,646,656 3,999.16M Converted from GL model (log)
RegNetY-6.4GF 19.03 4.56 30,583,252 6,388.91M Converted from GL model (log)
RegNetY-8.0GF 18.91 4.48 39,180,068 7,996.54M Converted from GL model (log)
RegNetY-12GF 18.67 4.42 51,822,544 12,132.55M Converted from GL model (log)
RegNetY-16GF 18.82 4.44 83,590,140 15,944.53M Converted from GL model (log)
RegNetY-32GF 17.92 3.83 145,046,770 32,317.66M Converted from GL model (log)
PyramidNet-101 (a=360) 20.53 5.43 42,455,070 8,743.54M Converted from GL model (log)
DiracNetV2-18 31.47 11.70 11,511,784 1,796.62M From szagoruyko/diracnets (log)
DiracNetV2-34 28.75 9.93 21,616,232 3,646.93M From szagoruyko/diracnets (log)
DenseNet-121 23.48 7.04 7,978,856 2,872.13M Converted from GL model (log)
DenseNet-161 21.91 6.06 28,681,000 7,793.16M Converted from GL model (log)
DenseNet-169 22.42 6.29 14,149,480 3,403.89M Converted from GL model (log)
DenseNet-201 21.78 6.12 20,013,928 4,347.15M Converted from GL model (log)
CondenseNet-74 (C=G=4) 26.25 8.28 4,773,944 546.06M From ShichenLiu/CondenseNet (log)
CondenseNet-74 (C=G=8) 28.93 10.06 2,935,416 291.52M From ShichenLiu/CondenseNet (log)
PeleeNet 29.41 10.04 2,802,248 514.87M Converted from GL model (log)
WRN-50-2 22.25 6.26 68,849,128 11,405.42M Converted from GL model (log)
DRN-C-26 24.61 7.23 21,126,584 16,993.90M Converted from GL model (log)
DRN-C-42 22.37 6.28 31,234,744 25,093.75M Converted from GL model (log)
DRN-C-58 20.65 5.27 40,542,008 32,489.94M Converted from GL model (log)
DRN-D-22 24.86 7.58 16,393,752 13,051.33M Converted from GL model (log)
DRN-D-38 22.94 6.43 26,501,912 21,151.19M Converted from GL model (log)
DRN-D-54 20.40 5.17 35,809,176 28,547.38M Converted from GL model (log)
DRN-D-105 20.62 5.48 54,801,304 43,442.43M From fyu/drn (log)
DPN-68 23.24 6.79 12,611,602 2,351.84M Converted from GL model (log)
DPN-98 18.44 4.30 61,570,728 11,716.51M Converted from GL model (log)
DPN-131 19.62 5.03 79,254,504 16,076.15M Converted from GL model (log)
DarkNet Tiny 40.74 17.84 1,042,104 500.85M Converted from GL model (log)
DarkNet Ref 38.58 17.18 7,319,416 367.59M Converted from GL model (log)
DarkNet-53 21.33 5.58 41,609,928 7,133.86M Converted from GL model (log)
i-RevNet-301 25.98 8.41 125,120,356 14,453.87M From jhjacobsen/pytorch-i-revnet (log)
BagNet-9 49.15 25.76 15,688,744 16,049.19M Converted from GL model (log)
BagNet-17 36.88 15.51 16,213,032 15,768.77M Converted from GL model (log)
BagNet-33 29.82 10.70 18,310,184 16,371.52M Converted from GL model (log)
DLA-34 24.59 7.24 15,742,104 3,071.37M Converted from GL model (log)
DLA-46-C 34.28 13.23 1,301,400 585.45M Converted from GL model (log)
DLA-X-46-C 33.26 12.69 1,068,440 546.72M Converted from GL model (log)
DLA-60 21.47 5.70 22,036,632 4,255.49M Converted from GL model (log)
DLA-X-60 21.07 5.75 17,352,344 3,543.68M Converted from GL model (log)
DLA-X-60-C 30.98 10.91 1,319,832 596.06M Converted from GL model (log)
DLA-102 20.69 5.37 33,268,888 7,190.95M Converted from GL model (log)
DLA-X-102 19.70 4.88 26,309,272 5,884.94M Converted from GL model (log)
DLA-X2-102 18.84 4.37 41,282,200 9,340.61M Converted from GL model (log)
DLA-169 19.39 4.71 53,389,720 11,593.20M Converted from GL model (log)
FishNet-150 19.26 4.75 24,959,400 6,435.05M Converted from GL model (log)
ESPNetv2 x0.5 42.32 20.15 1,241,332 35.36M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.0 33.92 13.45 1,670,072 98.09M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.25 32.06 12.18 1,965,440 138.18M From sacmehta/ESPNetv2 (log)
ESPNetv2 x1.5 30.83 11.29 2,314,856 185.77M From sacmehta/ESPNetv2 (log)
ESPNetv2 x2.0 27.94 9.61 3,498,136 306.93M From sacmehta/ESPNetv2 (log)
DiCENet x0.2 53.91 29.38 1,130,704 18.76M From sacmehta/EdgeNets (log)
DiCENet x0.5 46.16 22.58 1,214,120 30.48M From sacmehta/EdgeNets (log)
DiCENet x0.75 37.06 15.74 1,495,676 55.80M From sacmehta/EdgeNets (log)
DiCENet x1.0 33.59 13.25 1,805,604 82.17M From sacmehta/EdgeNets (log)
DiCENet x1.25 32.26 12.40 2,162,888 111.87M From sacmehta/EdgeNets (log)
DiCENet x1.5 30.55 11.23 2,652,200 151.81M From sacmehta/EdgeNets (log)
DiCENet x1.75 29.76 10.62 3,264,932 201.26M From sacmehta/EdgeNets (log)
DiCENet x2.0 28.95 10.19 3,979,044 257.95M From sacmehta/EdgeNets (log)
HRNet-W18 Small V1 26.48 9.01 13,187,464 1,615.00M Converted from GL model (log)
HRNet-W18 Small V2 21.93 6.18 15,597,464 2,618.84M Converted from GL model (log)
HRNetV2-W18 20.20 5.12 21,299,004 4,323.07M Converted from GL model (log)
HRNetV2-W30 20.35 5.21 37,712,220 8,156.82M Converted from GL model (log)
HRNetV2-W32 19.96 5.06 41,232,680 8,974.04M Converted from GL model (log)
HRNetV2-W40 19.84 4.93 57,557,160 12,752.26M Converted from GL model (log)
HRNetV2-W44 19.74 5.01 67,064,984 14,946.96M Converted from GL model (log)
HRNetV2-W48 19.67 5.00 77,469,864 17,345.39M Converted from GL model (log)
HRNetV2-W64 19.67 4.87 128,059,944 28,976.42M Converted from GL model (log)
VoVNet-27-slim 29.78 9.97 3,525,736 2,187.25M Converted from GL model (log)
VoVNet-39 21.71 5.64 22,600,296 7,086.16M Converted from GL model (log)
VoVNet-57 20.33 5.18 36,640,296 8,943.09M Converted from GL model (log)
SelecSLS-42b 21.93 6.11 32,458,248 2,980.62M Converted from GL model (log)
SelecSLS-60 20.35 5.29 30,670,768 3,591.78M Converted from GL model (log)
SelecSLS-60b 20.85 5.59 32,774,064 3,629.14M Converted from GL model (log)
HarDNet-39DS 26.83 8.81 3,488,228 437.52M Converted from GL model (log)
HarDNet-68DS 24.55 7.56 4,180,602 788.86M Converted from GL model (log)
HarDNet-68 23.51 6.99 17,565,348 4,256.32M From PingoLH/Pytorch-HarDNet (log)
HarDNet-85 22.00 5.86 36,670,212 9,088.58M Converted from GL model (log)
SqueezeNet v1.0 39.29 17.66 1,248,424 823.67M Converted from GL model (log)
SqueezeNet v1.1 39.31 17.72 1,235,496 352.02M Converted from GL model (log)
SqueezeResNet v1.0 39.77 18.09 1,248,424 823.67M Converted from GL model (log)
SqueezeResNet v1.1 40.09 18.21 1,235,496 352.02M Converted from GL model (log)
1.0-SqNxt-23 42.51 19.06 724,056 287.28M Converted from GL model (log)
1.0-SqNxt-23v5 40.77 17.85 921,816 285.82M Converted from GL model (log)
1.5-SqNxt-23 34.89 13.50 1,511,824 552.39M Converted from GL model (log)
1.5-SqNxt-23v5 33.81 13.01 1,953,616 550.97M Converted from GL model (log)
2.0-SqNxt-23 30.62 11.00 2,583,752 898.48M Converted from GL model (log)
2.0-SqNxt-23v5 29.63 10.66 3,366,344 897.60M Converted from GL model (log)
ShuffleNet x0.25 (g=1) 62.44 37.29 209,746 12.35M Converted from GL model (log)
ShuffleNet x0.25 (g=3) 61.74 36.53 305,902 13.09M Converted from GL model (log)
ShuffleNet x0.5 (g=1) 46.59 22.61 534,484 41.16M Converted from GL model (log)
ShuffleNet x0.5 (g=3) 44.16 20.80 718,324 41.70M Converted from GL model (log)
ShuffleNet x0.75 (g=1) 39.58 17.11 975,214 86.42M Converted from GL model (log)
ShuffleNet x0.75 (g=3) 38.20 16.50 1,238,266 85.82M Converted from GL model (log)
ShuffleNet x1.0 (g=1) 34.93 13.89 1,531,936 148.13M Converted from GL model (log)
ShuffleNet x1.0 (g=2) 34.25 13.63 1,733,848 147.60M Converted from GL model (log)
ShuffleNet x1.0 (g=3) 34.39 13.48 1,865,728 145.46M Converted from GL model (log)
ShuffleNet x1.0 (g=4) 34.19 13.35 1,968,344 143.33M Converted from GL model (log)
ShuffleNet x1.0 (g=8) 34.06 13.42 2,434,768 150.76M Converted from GL model (log)
ShuffleNetV2 x0.5 40.99 18.65 1,366,792 43.31M Converted from GL model (log)
ShuffleNetV2 x1.0 31.44 11.63 2,278,604 149.72M Converted from GL model (log)
ShuffleNetV2 x1.5 27.47 9.42 4,406,098 320.77M Converted from GL model (log)
ShuffleNetV2 x2.0 25.94 8.45 7,601,686 595.84M Converted from GL model (log)
ShuffleNetV2b x0.5 40.29 18.22 1,366,792 43.31M Converted from GL model (log)
ShuffleNetV2b x1.0 30.62 11.25 2,279,760 150.62M Converted from GL model (log)
ShuffleNetV2b x1.5 27.31 9.11 4,410,194 323.98M Converted from GL model (log)
ShuffleNetV2b x2.0 25.58 8.34 7,611,290 603.37M Converted from GL model (log)
108-MENet-8x1 (g=3) 43.94 20.76 654,516 42.68M Converted from GL model (log)
128-MENet-8x1 (g=4) 42.43 19.59 750,796 45.98M Converted from GL model (log)
160-MENet-8x1 (g=8) 43.84 20.84 850,120 45.63M Converted from GL model (log)
228-MENet-12x1 (g=3) 34.11 13.16 1,806,568 152.93M Converted from GL model (log)
256-MENet-12x1 (g=4) 32.65 12.52 1,888,240 150.65M Converted from GL model (log)
348-MENet-12x1 (g=3) 28.24 9.58 3,368,128 312.00M Converted from GL model (log)
352-MENet-12x1 (g=8) 31.56 12.00 2,272,872 157.35M Converted from GL model (log)
456-MENet-24x1 (g=3) 25.32 7.99 5,304,784 567.90M Converted from GL model (log)
MobileNet x0.25 46.26 22.49 470,072 44.09M Converted from GL model (log)
MobileNet x0.5 34.15 13.55 1,331,592 155.42M Converted from GL model (log)
MobileNet x0.75 30.14 10.76 2,585,560 333.99M Converted from GL model (log)
MobileNet x1.0 26.61 8.95 4,231,976 579.80M Converted from GL model (log)
MobileNetb x0.25 45.51 22.01 467,592 42.88M Converted from GL model (log)
MobileNetb x0.5 33.42 13.10 1,326,632 153.00M Converted from GL model (log)
MobileNetb x0.75 29.55 10.37 2,578,120 330.37M Converted from GL model (log)
MobileNetb x1.0 25.45 8.16 4,222,056 574.97M Converted from GL model (log)
FD-MobileNet x0.25 55.86 30.98 383,160 12.95M Converted from GL model (log)
FD-MobileNet x0.5 43.13 20.15 993,928 41.84M Converted from GL model (log)
FD-MobileNet x0.75 38.42 16.41 1,833,304 86.68M Converted from GL model (log)
FD-MobileNet x1.0 34.23 13.38 2,901,288 147.46M Converted from GL model (log)
MobileNetV2 x0.25 48.34 24.51 1,516,392 34.24M Converted from GL model (log)
MobileNetV2 x0.5 35.98 14.93 1,964,736 100.13M Converted from GL model (log)
MobileNetV2 x0.75 30.17 10.82 2,627,592 198.50M Converted from GL model (log)
MobileNetV2 x1.0 26.97 8.87 3,504,960 329.36M Converted from GL model (log)
MobileNetV2b x0.25 47.05 23.68 1,516,312 33.18M Converted from GL model (log)
MobileNetV2b x0.5 34.77 14.08 1,964,448 96.42M Converted from GL model (log)
MobileNetV2b x0.75 30.74 11.05 2,626,968 190.52M Converted from GL model (log)
MobileNetV2b x1.0 27.70 9.12 3,503,872 315.51M Converted from GL model (log)
MobileNetV3 L/224/1.0 24.55 7.44 5,481,752 227.09M Converted from GL model (log)
IGCV3 x0.25 53.70 28.71 1,534,020 41.29M Converted from GL model (log)
IGCV3 x0.5 39.75 17.32 1,985,528 111.12M Converted from GL model (log)
IGCV3 x0.75 31.05 11.40 2,638,084 210.95M Converted from GL model (log)
IGCV3 x1.0 27.91 9.20 3,491,688 340.79M Converted from GL model (log)
MnasNet-B1 24.96 7.40 4,383,312 326.30M Converted from GL model (log)
MnasNet-A1 24.39 7.20 3,887,038 326.07M Converted from GL model (log)
DARTS 25.31 7.75 4,718,752 539.86M Converted from GL model (log)
ProxylessNAS CPU 24.71 7.61 4,361,648 459.96M From MIT-HAN-LAB/ProxylessNAS (log)
ProxylessNAS GPU 24.79 7.45 7,119,848 476.08M Converted from GL model (log)
ProxylessNAS Mobile 25.41 7.80 4,080,512 332.46M From MIT-HAN-LAB/ProxylessNAS (log)
ProxylessNAS Mob-14 23.29 6.62 6,857,568 597.10M Converted from GL model (log)
FBNet-Cb 24.89 7.62 5,572,200 399.26M From rwightman/pyt...models (log)
Xception 20.35 5.16 22,855,952 8,403.63M Converted from GL model (log)
InceptionV3 20.44 5.33 23,834,568 5,743.06M Converted from GL model (log)
InceptionV4 19.83 4.88 42,679,816 12,304.93M Converted from GL model (log)
InceptionResNetV1 19.63 4.80 23,995,624 6,329.60M Converted from GL model (log)
InceptionResNetV2 19.40 4.74 55,843,464 13,188.64M Converted from GL model (log)
PolyNet 19.10 4.52 95,366,600 34,821.34M From Cadene/pretrained...pytorch (log)
NASNet-A 4@1056 25.32 8.03 5,289,978 584.90M Converted from GL model (log)
NASNet-A 6@4032 18.14 4.21 88,753,150 23,976.44M From Cadene/pretrained...pytorch (log)
PNASNet-5-Large 17.88 4.28 86,057,668 25,140.77M From Cadene/pretrained...pytorch (log)
SPNASNet 25.41 7.98 4,421,616 346.73M Converted from GL model (log)
EfficientNet-B0 24.77 7.52 5,288,548 414.31M Converted from GL model (log)
EfficientNet-B1 23.08 6.38 7,794,184 732.54M Converted from GL model (log)
EfficientNet-B0b 23.88 7.02 5,288,548 414.31M From rwightman/pyt...models (log)
EfficientNet-B1b 21.60 5.94 7,794,184 732.54M From rwightman/pyt...models (log)
EfficientNet-B2b 20.31 5.27 9,109,994 1,051.98M From rwightman/pyt...models (log)
EfficientNet-B3b 18.83 4.45 12,233,232 1,928.55M From rwightman/pyt...models (log)
EfficientNet-B4b 17.45 3.89 19,341,616 4,607.46M From rwightman/pyt...models (log)
EfficientNet-B5b 16.56 3.37 30,389,784 10,695.20M From rwightman/pyt...models (log)
EfficientNet-B6b 16.29 3.23 43,040,704 19,796.24M From rwightman/pyt...models (log)
EfficientNet-B7b 15.94 3.22 66,347,960 39,010.98M From rwightman/pyt...models (log)
EfficientNet-B0c* 22.92 6.75 5,288,548 414.31M From rwightman/pyt...models (log)
EfficientNet-B1c* 20.73 5.69 7,794,184 732.54M From rwightman/pyt...models (log)
EfficientNet-B2c* 19.85 5.03 9,109,994 1,051.98M From rwightman/pyt...models (log)
EfficientNet-B3c* 18.26 4.42 12,233,232 1,928.55M From rwightman/pyt...models (log)
EfficientNet-B4c* 16.82 3.69 19,341,616 4,607.46M From rwightman/pyt...models (log)
EfficientNet-B5c* 15.91 3.10 30,389,784 10,695.20M From rwightman/pyt...models (log)
EfficientNet-B6c* 15.47 2.96 43,040,704 19,796.24M From rwightman/pyt...models (log)
EfficientNet-B7c* 15.13 2.88 66,347,960 39,010.98M From rwightman/pyt...models (log)
EfficientNet-B8c* 14.85 2.76 87,413,142 64,541.66M From rwightman/pyt...models (log)
EfficientNet-Edge-Small-b* 22.74 6.40 5,438,392 2,378.12M From rwightman/pyt...models (log)
EfficientNet-Edge-Medium-b* 21.18 5.63 6,899,496 3,700.12M From rwightman/pyt...models (log)
EfficientNet-Edge-Large-b* 19.66 4.91 10,589,712 9,747.66M From rwightman/pyt...models (log)
MixNet-S 23.92 7.17 4,134,606 260.76M Converted from GL model (log)
MixNet-M 22.45 6.47 5,014,382 366.68M Converted from GL model (log)
MixNet-L 21.54 5.71 7,329,252 591.34M Converted from GL model (log)
ResNet(A)-10 31.29 11.90 5,438,024 1,135.86M Converted from GL model (log)
ResNet(A)-BC-14 28.06 9.90 10,084,168 1,721.57M Converted from GL model (log)
ResNet(A)-18 25.54 8.31 11,708,744 2,062.24M Converted from GL model (log)
ResNet(A)-50b 21.03 5.56 25,576,264 4,352.93M Converted from GL model (log)
ResNet(A)-101b 19.13 4.53 44,568,392 8,072.93M Converted from GL model (log)
ResNet(A)-152b 18.80 4.41 60,212,040 11,796.83M Converted from GL model (log)
ResNet(D)-50b 21.04 5.65 25,680,808 20,497.60M From dmlc/gluon-cv (log)
ResNet(D)-101b 19.59 4.73 44,672,936 35,392.65M From dmlc/gluon-cv (log)
ResNet(D)-152b 19.42 4.82 60,316,584 47,662.18M From dmlc/gluon-cv (log)

CIFAR-10

Model Error, % Params FLOPs/2 Remarks
NIN 7.43 966,986 222.97M Converted from GL model (log)
ResNet-20 5.97 272,474 41.29M Converted from GL model (log)
ResNet-56 4.52 855,770 127.06M Converted from GL model (log)
ResNet-110 3.69 1,730,714 255.70M Converted from GL model (log)
ResNet-164(BN) 3.68 1,704,154 255.31M Converted from GL model (log)
ResNet-272(BN) 3.33 2,816,986 420.61M Converted from GL model (log)
ResNet-542(BN) 3.43 5,599,066 833.87M Converted from GL model (log)
ResNet-1001 3.28 10,328,602 1,536.40M Converted from GL model (log)
ResNet-1202 3.53 19,424,026 2,857.17M Converted from GL model (log)
PreResNet-20 6.51 272,282 41.27M Converted from GL model (log)
PreResNet-56 4.49 855,578 127.03M Converted from GL model (log)
PreResNet-110 3.86 1,730,522 255.68M Converted from GL model (log)
PreResNet-164(BN) 3.64 1,703,258 255.08M Converted from GL model (log)
PreResNet-272(BN) 3.25 2,816,090 420.38M Converted from GL model (log)
PreResNet-542(BN) 3.14 5,598,170 833.64M Converted from GL model (log)
PreResNet-1001 2.65 10,327,706 1,536.18M Converted from GL model (log)
PreResNet-1202 3.39 19,423,834 2,857.14M Converted from GL model (log)
ResNeXt-29 (32x4d) 3.15 4,775,754 780.55M Converted from GL model (log)
ResNeXt-29 (16x64d) 2.41 68,155,210 10,709.34M Converted from GL model (log)
ResNeXt-272 (1x64d) 2.55 44,540,746 6,565.15M Converted from GL model (log)
ResNeXt-272 (2x32d) 2.74 32,928,586 4,867.11M Converted from GL model (log)
SE-ResNet-20 6.01 274,847 41.34M Converted from GL model (log)
SE-ResNet-56 4.13 862,889 127.19M Converted from GL model (log)
SE-ResNet-110 3.63 1,744,952 255.98M Converted from GL model (log)
SE-ResNet-164(BN) 3.39 1,906,258 256.55M Converted from GL model (log)
SE-ResNet-272(BN) 3.39 3,153,826 422.68M Converted from GL model (log)
SE-ResNet-542(BN) 3.47 6,272,746 838.01M Converted from GL model (log)
SE-PreResNet-20 6.18 274,559 41.35M Converted from GL model (log)
SE-PreResNet-56 4.51 862,601 127.20M Converted from GL model (log)
SE-PreResNet-110 4.54 1,744,664 255.98M Converted from GL model (log)
SE-PreResNet-164(BN) 3.73 1,904,882 256.32M Converted from GL model (log)
SE-PreResNet-272(BN) 3.39 3,152,450 422.45M Converted from GL model (log)
SE-PreResNet-542(BN) 3.08 6,271,370 837.78M Converted from GL model (log)
PyramidNet-110 (a=48) 3.72 1,772,706 408.37M Converted from GL model (log)
PyramidNet-110 (a=84) 2.98 3,904,446 778.15M Converted from GL model (log)
PyramidNet-110 (a=270) 2.51 28,485,477 4,730.60M Converted from GL model (log)
PyramidNet-164 (a=270, BN) 2.42 27,216,021 4,608.81M Converted from GL model (log)
PyramidNet-200 (a=240, BN) 2.44 26,752,702 4,563.40M Converted from GL model (log)
PyramidNet-236 (a=220, BN) 2.47 26,969,046 4,631.32M Converted from GL model (log)
PyramidNet-272 (a=200, BN) 2.39 26,210,842 4,541.36M Converted from GL model (log)
DenseNet-40 (k=12) 5.61 599,050 210.80M Converted from GL model (log)
DenseNet-BC-40 (k=12) 6.43 176,122 74.89M Converted from GL model (log)
DenseNet-BC-40 (k=24) 4.52 690,346 293.09M Converted from GL model (log)
DenseNet-BC-40 (k=36) 4.04 1,542,682 654.60M Converted from GL model (log)
DenseNet-100 (k=12) 3.66 4,068,490 1,353.55M Converted from GL model (log)
DenseNet-100 (k=24) 3.13 16,114,138 5,354.19M Converted from GL model (log)
DenseNet-BC-100 (k=12) 4.16 769,162 298.45M Converted from GL model (log)
DenseNet-BC-190 (k=40) 2.52 25,624,430 9,400.45M Converted from GL model (log)
DenseNet-BC-250 (k=24) 2.67 15,324,406 5,519.54M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 5.31 690,346 293.09M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 4.37 1,542,682 654.60M Converted from GL model (log)
WRN-16-10 2.93 17,116,634 2,414.04M Converted from GL model (log)
WRN-28-10 2.39 36,479,194 5,246.98M Converted from GL model (log)
WRN-40-8 2.37 35,748,314 5,176.90M Converted from GL model (log)
WRN-20-10-1bit 3.26 26,737,140 4,019.14M Converted from GL model (log)
WRN-20-10-32bit 3.14 26,737,140 4,019.14M Converted from GL model (log)
RoR-3-56 5.43 762,746 113.43M Converted from GL model (log)
RoR-3-110 4.35 1,637,690 242.07M Converted from GL model (log)
RoR-3-164 3.93 2,512,634 370.72M Converted from GL model (log)
RiR 3.28 9,492,980 1,281.08M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 5.15 541,082 81.78M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 3.17 2,923,162 428.89M Converted from GL model (log)
DIA-ResNet-20 6.22 286,866 41.54M Converted from GL model (log)
DIA-ResNet-56 5.05 870,162 129.31M Converted from GL model (log)
DIA-ResNet-110 4.10 1,745,106 264.71M Converted from GL model (log)
DIA-ResNet-164(BN) 3.50 1,923,002 343.60M Converted from GL model (log)
DIA-PreResNet-20 6.42 286,674 41.52M Converted from GL model (log)
DIA-PreResNet-56 4.83 869,970 129.28M Converted from GL model (log)
DIA-PreResNet-110 4.25 1,744,914 264.69M Converted from GL model (log)
DIA-PreResNet-164(BN) 3.56 1,922,106 343.37M Converted from GL model (log)

CIFAR-100

Model Error, % Params FLOPs/2 Remarks
NIN 28.39 984,356 224.08M Converted from GL model (log)
ResNet-20 29.64 278,324 41.30M Converted from GL model (log)
ResNet-56 24.88 861,620 127.06M Converted from GL model (log)
ResNet-110 22.80 1,736,564 255.71M Converted from GL model (log)
ResNet-164(BN) 20.44 1,727,284 255.33M Converted from GL model (log)
ResNet-272(BN) 20.07 2,840,116 420.63M Converted from GL model (log)
ResNet-542(BN) 19.32 5,622,196 833.89M Converted from GL model (log)
ResNet-1001 19.79 10,351,732 1,536.43M Converted from GL model (log)
ResNet-1202 21.56 19,429,876 2,857.17M Converted from GL model (log)
PreResNet-20 30.22 278,132 41.28M Converted from GL model (log)
PreResNet-56 25.05 861,428 127.04M Converted from GL model (log)
PreResNet-110 22.67 1,736,372 255.68M Converted from GL model (log)
PreResNet-164(BN) 20.18 1,726,388 255.10M Converted from GL model (log)
PreResNet-272(BN) 19.63 2,839,220 420.40M Converted from GL model (log)
PreResNet-542(BN) 18.71 5,621,300 833.66M Converted from GL model (log)
PreResNet-1001 18.41 10,350,836 1,536.20M Converted from GL model (log)
ResNeXt-29 (32x4d) 19.50 4,868,004 780.64M Converted from GL model (log)
ResNeXt-29 (16x64d) 16.93 68,247,460 10,709.43M Converted from GL model (log)
ResNeXt-272 (1x64d) 19.11 44,632,996 6,565.25M Converted from GL model (log)
ResNeXt-272 (2x32d) 18.34 33,020,836 4,867.20M Converted from GL model (log)
SE-ResNet-20 28.54 280,697 41.35M Converted from GL model (log)
SE-ResNet-56 22.94 868,739 127.07M Converted from GL model (log)
SE-ResNet-110 20.86 1,750,802 255.98M Converted from GL model (log)
SE-ResNet-164(BN) 19.95 1,929,388 256.57M Converted from GL model (log)
SE-ResNet-272(BN) 19.07 3,176,956 422.70M Converted from GL model (log)
SE-ResNet-542(BN) 18.87 6,295,876 838.03M Converted from GL model (log)
SE-PreResNet-20 28.31 280,409 41.35M Converted from GL model (log)
SE-PreResNet-56 23.05 868,451 127.21M Converted from GL model (log)
SE-PreResNet-110 22.61 1,750,514 255.99M Converted from GL model (log)
SE-PreResNet-164(BN) 20.05 1,928,012 256.34M Converted from GL model (log)
SE-PreResNet-272(BN) 19.13 3,175,580 422.47M Converted from GL model (log)
SE-PreResNet-542(BN) 19.45 6,294,500 837.80M Converted from GL model (log)
PyramidNet-110 (a=48) 20.95 1,778,556 408.38M Converted from GL model (log)
PyramidNet-110 (a=84) 18.87 3,913,536 778.16M Converted from GL model (log)
PyramidNet-110 (a=270) 17.10 28,511,307 4,730.62M Converted from GL model (log)
PyramidNet-164 (a=270, BN) 16.70 27,319,071 4,608.91M Converted from GL model (log)
PyramidNet-200 (a=240, BN) 16.09 26,844,952 4,563.49M Converted from GL model (log)
PyramidNet-236 (a=220, BN) 16.34 27,054,096 4,631.41M Converted from GL model (log)
PyramidNet-272 (a=200, BN) 16.19 26,288,692 4,541.43M Converted from GL model (log)
DenseNet-40 (k=12) 24.90 622,360 210.82M Converted from GL model (log)
DenseNet-BC-40 (k=12) 28.41 188,092 74.90M Converted from GL model (log)
DenseNet-BC-40 (k=24) 22.67 714,196 293.11M Converted from GL model (log)
DenseNet-BC-40 (k=36) 20.50 1,578,412 654.64M Converted from GL model (log)
DenseNet-100 (k=12) 19.64 4,129,600 1,353.62M Converted from GL model (log)
DenseNet-100 (k=24) 18.08 16,236,268 5,354.32M Converted from GL model (log)
DenseNet-BC-100 (k=12) 21.19 800,032 298.48M Converted from GL model (log)
DenseNet-BC-250 (k=24) 17.39 15,480,556 5,519.69M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 23.96 714,196 293.11M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 21.65 1,578,412 654.64M Converted from GL model (log)
WRN-16-10 18.95 17,174,324 2,414.09M Converted from GL model (log)
WRN-28-10 17.88 36,536,884 5,247.04M Converted from GL model (log)
WRN-40-8 18.03 35,794,484 5,176.95M Converted from GL model (log)
WRN-20-10-1bit 19.04 26,794,920 4,022.81M Converted from GL model (log)
WRN-20-10-32bit 18.12 26,794,920 4,022.81M Converted from GL model (log)
RoR-3-56 25.49 768,596 113.43M Converted from GL model (log)
RoR-3-110 23.64 1,643,540 242.08M Converted from GL model (log)
RoR-3-164 22.34 2,518,484 370.72M Converted from GL model (log)
RiR 19.23 9,527,720 1,283.29M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 29.22 546,932 81.79M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 18.80 2,934,772 428.90M Converted from GL model (log)
DIA-ResNet-20 27.71 292,716 41.55M Converted from GL model (log)
DIA-ResNet-56 24.35 876,012 129.32M Converted from GL model (log)
DIA-ResNet-110 22.11 1,750,956 264.72M Converted from GL model (log)
DIA-ResNet-164(BN) 19.53 1,946,132 343.62M Converted from GL model (log)
DIA-PreResNet-20 28.37 292,524 41.53M Converted from GL model (log)
DIA-PreResNet-56 25.05 875,820 129.29M Converted from GL model (log)
DIA-PreResNet-110 22.69 1,750,764 264.69M Converted from GL model (log)
DIA-PreResNet-164(BN) 19.99 1,945,236 343.39M Converted from GL model (log)

SVHN

Model Error, % Params FLOPs/2 Remarks
NIN 3.76 966,986 222.97M Converted from GL model (log)
ResNet-20 3.43 272,474 41.29M Converted from GL model (log)
ResNet-56 2.75 855,770 127.06M Converted from GL model (log)
ResNet-110 2.45 1,730,714 255.70M Converted from GL model (log)
ResNet-164(BN) 2.42 1,704,154 255.31M Converted from GL model (log)
ResNet-272(BN) 2.43 2,816,986 420.61M Converted from GL model (log)
ResNet-542(BN) 2.34 5,599,066 833.87M Converted from GL model (log)
ResNet-1001 2.41 10,328,602 1,536.40M Converted from GL model (log)
PreResNet-20 3.22 272,282 41.27M Converted from GL model (log)
PreResNet-56 2.80 855,578 127.03M Converted from GL model (log)
PreResNet-110 2.79 1,730,522 255.68M Converted from GL model (log)
PreResNet-164(BN) 2.58 1,703,258 255.08M Converted from GL model (log)
PreResNet-272(BN) 2.34 2,816,090 420.38M Converted from GL model (log)
PreResNet-542(BN) 2.36 5,598,170 833.64M Converted from GL model (log)
ResNeXt-29 (32x4d) 2.80 4,775,754 780.55M Converted from GL model (log)
ResNeXt-29 (16x64d) 2.68 68,155,210 10,709.34M Converted from GL model (log)
ResNeXt-272 (1x64d) 2.35 44,540,746 6,565.15M Converted from GL model (log)
ResNeXt-272 (2x32d) 2.44 32,928,586 4,867.11M Converted from GL model (log)
SE-ResNet-20 3.23 274,847 41.34M Converted from GL model (log)
SE-ResNet-56 2.64 862,889 127.19M Converted from GL model (log)
SE-ResNet-110 2.35 1,744,952 255.98M Converted from GL model (log)
SE-ResNet-164(BN) 2.45 1,906,258 256.55M Converted from GL model (log)
SE-ResNet-272(BN) 2.38 3,153,826 422.68M Converted from GL model (log)
SE-ResNet-542(BN) 2.26 6,272,746 838.01M Converted from GL model (log)
SE-PreResNet-20 3.24 274,559 41.35M Converted from GL model (log)
SE-PreResNet-56 2.71 862,601 127.20M Converted from GL model (log)
SE-PreResNet-110 2.59 1,744,664 255.98M Converted from GL model (log)
SE-PreResNet-164(BN) 2.56 1,904,882 256.32M Converted from GL model (log)
SE-PreResNet-272(BN) 2.49 3,152,450 422.45M Converted from GL model (log)
SE-PreResNet-542(BN) 2.47 6,271,370 837.78M Converted from GL model (log)
PyramidNet-110 (a=48) 2.47 1,772,706 408.37M Converted from GL model (log)
PyramidNet-110 (a=84) 2.43 3,904,446 778.15M Converted from GL model (log)
PyramidNet-110 (a=270) 2.38 28,485,477 4,730.60M Converted from GL model (log)
PyramidNet-164 (a=270, BN) 2.33 27,216,021 4,608.81M Converted from GL model (log)
PyramidNet-200 (a=240, BN) 2.32 26,752,702 4,563.40M Converted from GL model (log)
PyramidNet-236 (a=220, BN) 2.35 26,969,046 4,631.32M Converted from GL model (log)
PyramidNet-272 (a=200, BN) 2.40 26,210,842 4,541.36M Converted from GL model (log)
DenseNet-40 (k=12) 3.05 599,050 210.80M Converted from GL model (log)
DenseNet-BC-40 (k=12) 3.20 176,122 74.89M Converted from GL model (log)
DenseNet-BC-40 (k=24) 2.90 690,346 293.09M Converted from GL model (log)
DenseNet-BC-40 (k=36) 2.60 1,542,682 654.60M Converted from GL model (log)
DenseNet-100 (k=12) 2.60 4,068,490 1,353.55M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=24) 2.87 690,346 293.09M Converted from GL model (log)
X-DenseNet-BC-40-2 (k=36) 2.74 1,542,682 654.60M Converted from GL model (log)
WRN-16-10 2.78 17,116,634 2,414.04M Converted from GL model (log)
WRN-28-10 2.71 36,479,194 5,246.98M Converted from GL model (log)
WRN-40-8 2.54 35,748,314 5,176.90M Converted from GL model (log)
WRN-20-10-1bit 2.73 26,737,140 4,019.14M Converted from GL model (log)
WRN-20-10-32bit 2.59 26,737,140 4,019.14M Converted from GL model (log)
RoR-3-56 2.69 762,746 113.43M Converted from GL model (log)
RoR-3-110 2.57 1,637,690 242.07M Converted from GL model (log)
RoR-3-164 2.73 2,512,634 370.72M Converted from GL model (log)
RiR 2.68 9,492,980 1,281.08M Converted from GL model (log)
Shake-Shake-ResNet-20-2x16d 3.17 541,082 81.78M Converted from GL model (log)
Shake-Shake-ResNet-26-2x32d 2.62 2,923,162 428.89M Converted from GL model (log)
DIA-ResNet-20 3.23 286,866 41.54M Converted from GL model (log)
DIA-ResNet-56 2.68 870,162 129.31M Converted from GL model (log)
DIA-ResNet-110 2.47 1,745,106 264.71M Converted from GL model (log)
DIA-ResNet-164(BN) 2.44 1,923,002 343.60M Converted from GL model (log)
DIA-PreResNet-20 3.03 286,674 41.52M Converted from GL model (log)
DIA-PreResNet-56 2.80 869,970 129.28M Converted from GL model (log)
DIA-PreResNet-110 2.42 1,744,914 264.69M Converted from GL model (log)
DIA-PreResNet-164(BN) 2.56 1,922,106 343.37M Converted from GL model (log)

CUB-200-2011

Model Error, % Params FLOPs/2 Remarks
ResNet-10 27.77 5,008,392 893.63M Converted from GL model (log)
ResNet-12 27.27 5,082,376 1,125.84M Converted from GL model (log)
ResNet-14 24.77 5,377,800 1,357.53M Converted from GL model (log)
ResNet-16 23.65 6,558,472 1,588.93M Converted from GL model (log)
ResNet-18 23.33 11,279,112 1,820.00M Converted from GL model (log)
ResNet-26 23.16 17,549,832 2,746.38M Converted from GL model (log)
SE-ResNet-10 27.72 5,052,932 893.86M Converted from GL model (log)
SE-ResNet-12 26.51 5,127,496 1,126.17M Converted from GL model (log)
SE-ResNet-14 24.16 5,425,104 1,357.92M Converted from GL model (log)
SE-ResNet-16 23.32 6,614,240 1,589.35M Converted from GL model (log)
SE-ResNet-18 23.52 11,368,192 1,820.47M Converted from GL model (log)
SE-ResNet-26 22.99 17,683,452 2,747.08M Converted from GL model (log)
MobileNet x1.0 23.77 3,411,976 578.98M Converted from GL model (log)
ProxylessNAS Mobile 22.66 3,055,712 331.44M Converted from GL model (log)
NTS-Net 12.77 28,623,333 33,361.79M From yangze0930/NTS-Net (log)

Pascal VOC20102

Model Extractor Pix.Acc.,% mIoU,% Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 98.09 81.44 65,708,501 230,771.01M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 97.95 80.24 58,754,773 47,625.34M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-152b 98.11 81.20 74,398,421 59,894.87M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 97.80 80.40 52,072,917 196,562.96M From dmlc/gluon-cv (log)

ADE20K

Model Extractor Pix.Acc.,% mIoU,% Params FLOPs/2 Remarks
PSPNet ResNet(D)-50b 79.37 36.87 46,782,550 162,595.14M From dmlc/gluon-cv (log)
PSPNet ResNet(D)-101b 79.93 37.97 65,774,678 231,008.79M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-50b 79.72 37.13 39,795,798 32,756.18M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 80.21 37.84 58,787,926 47,651.23M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-50b 76.92 33.39 33,146,966 128,387.08M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 79.01 35.88 52,139,094 196,800.73M From dmlc/gluon-cv (log)

Cityscapes

Model Extractor Pix.Acc.,% mIoU,% Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 96.17 71.72 65,707,475 230,767.33M From dmlc/gluon-cv (log)
ICNet ResNet(D)-50b 95.50 64.02 47,489,184 14,253.43M From dmlc/gluon-cv (log)
SINet - 94.08 61.72 119,418 1,419.90M From clovaai/c3_sinet (log)
Fast-SCNN - 95.14 65.76 1,138,051 3493.33M From dmlc/gluon-cv (log)
DANet ResNet(D)-50b 95.91 67.99 47,586,427 180,397.43M From dmlc/gluon-cv (log)
DANet ResNet(D)-101b 96.03 68.10 66,578,555 248,811.08M From dmlc/gluon-cv (log)

COCO Semantic Segmentation

Model Extractor Pix.Acc.,% mIoU,% Params FLOPs/2 Remarks
PSPNet ResNet(D)-101b 92.05 67.41 65,708,501 230,771.01M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-101b 92.19 67.73 58,754,773 47,625.34M From dmlc/gluon-cv (log)
DeepLabv3 ResNet(D)-152b 92.24 68.99 74,398,421 275,087.91M From dmlc/gluon-cv (log)
FCN-8s(d) ResNet(D)-101b 91.44 60.11 52,072,917 196,562.96M From dmlc/gluon-cv (log)

CelebAMask-HQ

Model Extractor Params FLOPs/2 Remarks
BiSeNet ResNet-18 13,300,416 - From zllrunning/face...Torch (log)

COCO Keypoints Detection

Model Extractor OKS AP, % Params FLOPs/2 Remarks
AlphaPose Fast-SE-ResNet-101b 74.15/91.59/80.68 59,569,873 9,553.89M From dmlc/gluon-cv (log)
SimplePose ResNet-18 66.31/89.20/73.41 15,376,721 1,799.25M From dmlc/gluon-cv (log)
SimplePose ResNet-50b 71.02/91.23/78.57 33,999,697 4,041.06M From dmlc/gluon-cv (log)
SimplePose ResNet-101b 72.44/92.18/79.76 52,991,825 7,685.04M From dmlc/gluon-cv (log)
SimplePose ResNet-152b 72.53/92.14/79.61 68,635,473 11,332.86M From dmlc/gluon-cv (log)
SimplePose ResNet(A)-50b 71.70/91.31/78.66 34,018,929 4,278.56M From dmlc/gluon-cv (log)
SimplePose ResNet(A)-101b 72.97/92.24/80.81 53,011,057 7,922.54M From dmlc/gluon-cv (log)
SimplePose ResNet(A)-152b 73.44/92.27/80.72 68,654,705 11,570.36M From dmlc/gluon-cv (log)
SimplePose(Mobile) ResNet-18 66.25/89.17/74.32 12,858,208 1,960.96M From dmlc/gluon-cv (log)
SimplePose(Mobile) ResNet-50b 71.10/91.28/78.67 25,582,944 4,221.30M From dmlc/gluon-cv (log)
SimplePose(Mobile) 1.0 MobileNet-224 64.10/88.06/71.23 5,019,744 751.36M From dmlc/gluon-cv (log)
SimplePose(Mobile) 1.0 MobileNetV2b-224 63.74/88.12/71.06 4,102,176 495.95M From dmlc/gluon-cv (log)
SimplePose(Mobile) MobileNetV3 Small 224/1.0 54.34/83.67/59.35 2,625,088 236.51M From dmlc/gluon-cv (log)
SimplePose(Mobile) MobileNetV3 Large 224/1.0 63.67/88.91/70.82 4,768,336 403.97M From dmlc/gluon-cv (log)
Lightweight OpenPose 2D MobileNet 39.99/65.95/40.70 4,091,698 8,948.96M From Daniil-Osokin/lighw...ch (log)
Lightweight OpenPose 3D MobileNet 39.99/65.95/40.70 5,085,983 11,049.43M From Daniil-Osokin/li...3d...ch (log)
IBPPose - 64.87/83.62/70.13 95,827,784 57,195.91M From jialee93/Improved...Parts (log)

Mozilla Common Voice (Corpus 6.1, dev subset)

Some remarks:

  • NR means Noise Reduction.
  • LS means trained on LibriSpeech dataset.
Model Lang WER, % Params FLOPs/2 Remarks
Jasper DR 10x5 En 21.92 332,632,349 85,142.96M From NVIDIA/NeMo (log)
Jasper DR 10x5 NR En 17.92 332,632,349 85,142.96M From NVIDIA/NeMo (log)
QuartzNet 5x5 LS En 44.69 6,713,181 1,717.12M From NVIDIA/NeMo (log)
QuartzNet 15x5 En 16.79 18,924,381 4,840.29M From NVIDIA/NeMo (log)
QuartzNet 15x5 NR En 17.76 18,924,381 4,840.29M From NVIDIA/NeMo (log)
QuartzNet 15x5 De 11.67 18,927,456 4,841.08M From NVIDIA/NeMo (log)
QuartzNet 15x5 Fr 13.88 18,938,731 4,843.96M From NVIDIA/NeMo (log)
QuartzNet 15x5 It 15.02 18,934,631 4,842.91M From NVIDIA/NeMo (log)
QuartzNet 15x5 Es 12.95 18,931,556 4,842.13M From NVIDIA/NeMo (log)
QuartzNet 15x5 Ca 8.42 18,934,631 4,842.91M From NVIDIA/NeMo (log)
QuartzNet 15x5 Pl 13.59 18,929,506 4,841.60M From NVIDIA/NeMo (log)
QuartzNet 15x5 Ru 16.48 18,930,531 4,841.87M From NVIDIA/NeMo (log)
QuartzNet 15x5 Ru/34 9.69 18,929,506 4,841.60M From sberdevices/golos (log)

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