A PyTorch implementation of Inception-v4 and Inception-ResNet-v2.
An inofficial PyTorch implementation of Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
All the results reported here are based on this repo, and 50000 ImageNet validation sets。
Top-1 and top-5 accuracy with blacklisted entities
Model | top-1(TF) | top-1(this repo) | top-5(TF) | top-5(this repo) |
---|---|---|---|---|
Inception-v4 | 0.801 | 0.801 | 0.952 | 0.950 |
Inception-ResNet-v2 | 0.804 | 0.803 | 0.953 | 0.951 |
Other hyper-parameters in Inception-v4
eps
in BatchNorm2d and count_include_pad
in AvgPool2d
Config | #top-1 | top-1 | #top-5 | top-5 |
---|---|---|---|---|
eps=0.001, count_include_pad=False | 40041 | 0.801 | 47445 | 0.949 |
eps=0.001, count_include_pad=True | 39970 | 0.799 | 47395 | 0.948 |
eps=1e-5, count_include_pad=False | 40036 | 0.801 | 47438 | 0.949 |
Model parameters and FLOPs
Model | Params(M) | FLOPs(G) |
---|---|---|
Inception-v4 | 42.68 | 6.31 |
Inception-ResNet-v2 | 55.84 | 6.65 |
Average inference time(RTX 2080Ti)
Model | Single inference time(ms) |
---|---|
Inception-v4 | 40.54 |
Inception-ResNet-v2 | 61.62 |
Top-1 and top-5 accuracy(bottom-10 classes)
Inception-v4
Top-1 accuracy | Classes | Top-5 accuracy | Classes |
---|---|---|---|
0.16 | n04152593 : screen, CRT screen | 0.62 | n03692522 : loupe, jeweler's loupe |
0.22 | n04286575 : spotlight, spot | 0.64 | n04286575 : spotlight, spot |
0.22 | n02123159 : tiger cat | 0.64 | n04525038 : velvet |
0.22 | n03642806 : laptop, laptop computer | 0.68 | n04081281 : restaurant, eating house, eating place, eatery |
0.22 | n04355933 : sunglass | 0.72 | n03532672 : hook, claw |
0.24 | n04560804 : water jug | 0.72 | n03658185 : letter opener, paper knife, paperknife |
0.26 | n04525038 : velvet | 0.74 | n03476684 : hair slide |
0.26 | n02979186 : cassette player | 0.74 | n02910353 : buckle |
0.28 | n02107908 : Appenzeller | 0.76 | n02776631 : bakery, bakeshop, bakehouse |
0.34 | n03710637 : maillot | 0.76 | n03347037 : fire screen, fireguard |
Inception-ResNet-v2
Top-1 accuracy | Classes | Top-5 accuracy | Classes |
---|---|---|---|
0.18 | n04152593 : screen, CRT screen | 0.6 | n04286575 : spotlight, spot |
0.22 | n03710637 : maillot | 0.64 | n04525038 : velvet |
0.22 | n02123159 : tiger cat | 0.64 | n03692522 : loupe, jeweler's loupe |
0.28 | n02979186 : cassette player | 0.66 | n03658185 : letter opener, paper knife, paperknife |
0.28 | n04008634 : projectile, missile | 0.7 | n04081281 : restaurant, eating house, eating place, eatery |
0.28 | n04355933 : sunglass | 0.72 | n03532672 : hook, claw |
0.3 | n03658185 : letter opener, paper knife, paperknife | 0.74 | n04591157 : Windsor tie |
0.3 | n03642806 : laptop, laptop computer | 0.74 | n03016953 : chiffonier, commode |
0.3 | n04286575 : spotlight, spot | 0.74 | n04239074 : sliding door |
0.32 | n02089973 : English foxhound | 0.74 | n03476684 : hair slide |
Stem
Overall schema
The output of the last Inception-ResNet-C layer has no ReLU activation.