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new afc1496 [WIP]Update resnet pretrained models (#11327)
afc1496 is described below
commit afc14963480f4b20db903f839740cebd92eadfba
Author: Tong He <[email protected]>
AuthorDate: Wed Jun 20 19:19:17 2018 -0700
[WIP]Update resnet pretrained models (#11327)
* update resnet pretrained models
* Trigger CI
* add resnet152 models
* add hash
---
docs/api/python/gluon/model_zoo.md | 20 ++++++++++----------
python/mxnet/gluon/model_zoo/model_store.py | 20 ++++++++++----------
2 files changed, 20 insertions(+), 20 deletions(-)
diff --git a/docs/api/python/gluon/model_zoo.md
b/docs/api/python/gluon/model_zoo.md
index 453fe8d..6e3fb50 100644
--- a/docs/api/python/gluon/model_zoo.md
+++ b/docs/api/python/gluon/model_zoo.md
@@ -46,16 +46,16 @@ The following table summarizes the available models.
| mobilenetv2_0.75 | [MobileNetV2 0.75](https://arxiv.org/abs/1801.04381)
| 2,653,864 | 0.6961 | 0.8895 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
| mobilenetv2_0.5 | [MobileNetV2 0.5](https://arxiv.org/abs/1801.04381)
| 1,983,104 | 0.6449 | 0.8547 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
| mobilenetv2_0.25 | [MobileNetV2 0.25](https://arxiv.org/abs/1801.04381)
| 1,526,856 | 0.5074 | 0.7456 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
-| resnet18_v1 | [ResNet-18 V1](http://arxiv.org/abs/1512.03385)
| 11,699,112 | 0.7039 | 0.8959 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
-| resnet34_v1 | [ResNet-34 V1](http://arxiv.org/abs/1512.03385)
| 21,814,696 | 0.7411 | 0.9184 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
-| resnet50_v1 | [ResNet-50 V1](http://arxiv.org/abs/1512.03385)
| 25,629,032 | 0.7540 | 0.9266 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
-| resnet101_v1 | [ResNet-101 V1](http://arxiv.org/abs/1512.03385)
| 44,695,144 | 0.7693 | 0.9334 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
-| resnet152_v1 | [ResNet-152 V1](http://arxiv.org/abs/1512.03385)
| 60,404,072 | 0.7727 | 0.9353 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
-| resnet18_v2 | [ResNet-18 V2](https://arxiv.org/abs/1603.05027)
| 11,695,796 | 0.7037 | 0.8962 |
Trained with
[script](https://github.com/dmlc/gluon-cv/blob/15ed8a4c71d411b878f0d71d1c7afdce6710c913/scripts/classification/imagenet/train_imagenet.py)
|
-| resnet34_v2 | [ResNet-34 V2](https://arxiv.org/abs/1603.05027)
| 21,811,380 | 0.7389 | 0.9178 |
Trained with
[script](https://github.com/dmlc/gluon-cv/blob/15ed8a4c71d411b878f0d71d1c7afdce6710c913/scripts/classification/imagenet/train_imagenet.py)
|
-| resnet50_v2 | [ResNet-50 V2](https://arxiv.org/abs/1603.05027)
| 25,595,060 | 0.7622 | 0.9297 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
-| resnet101_v2 | [ResNet-101 V2](https://arxiv.org/abs/1603.05027)
| 44,639,412 | 0.7747 | 0.9375 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
-| resnet152_v2 | [ResNet-152 V2](https://arxiv.org/abs/1603.05027)
| 60,329,140 | 0.7833 | 0.9409 |
Trained with
[script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)
|
+| resnet18_v1 | [ResNet-18 V1](http://arxiv.org/abs/1512.03385)
| 11,699,112 | 0.7093 | 0.8992 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet34_v1 | [ResNet-34 V1](http://arxiv.org/abs/1512.03385)
| 21,814,696 | 0.7437 | 0.9187 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet50_v1 | [ResNet-50 V1](http://arxiv.org/abs/1512.03385)
| 25,629,032 | 0.7647 | 0.9313 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet101_v1 | [ResNet-101 V1](http://arxiv.org/abs/1512.03385)
| 44,695,144 | 0.7834 | 0.9401 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet152_v1 | [ResNet-152 V1](http://arxiv.org/abs/1512.03385)
| 60,404,072 | 0.7900 | 0.9438 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet18_v2 | [ResNet-18 V2](https://arxiv.org/abs/1603.05027)
| 11,695,796 | 0.7100 | 0.8992 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet34_v2 | [ResNet-34 V2](https://arxiv.org/abs/1603.05027)
| 21,811,380 | 0.7440 | 0.9208 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet50_v2 | [ResNet-50 V2](https://arxiv.org/abs/1603.05027)
| 25,595,060 | 0.7711 | 0.9343 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet101_v2 | [ResNet-101 V2](https://arxiv.org/abs/1603.05027)
| 44,639,412 | 0.7853 | 0.9417 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
+| resnet152_v2 | [ResNet-152 V2](https://arxiv.org/abs/1603.05027)
| 60,329,140 | 0.7921 | 0.9431 |
Trained with
[script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)
|
| squeezenet1.0 | [SqueezeNet 1.0](https://arxiv.org/abs/1602.07360)
| 1,248,424 | 0.5611 | 0.7909 |
Converted from pytorch vision
|
| squeezenet1.1 | [SqueezeNet
1.1](https://github.com/DeepScale/SqueezeNet/tree/master/SqueezeNet_v1.1) |
1,235,496 | 0.5496 | 0.7817 | Converted from pytorch vision
|
| vgg11 | [VGG-11](https://arxiv.org/abs/1409.1556)
| 132,863,336 | 0.6662 | 0.8734 |
Converted from pytorch vision
|
diff --git a/python/mxnet/gluon/model_zoo/model_store.py
b/python/mxnet/gluon/model_zoo/model_store.py
index cbd95cf..fb66a71 100644
--- a/python/mxnet/gluon/model_zoo/model_store.py
+++ b/python/mxnet/gluon/model_zoo/model_store.py
@@ -39,16 +39,16 @@ _model_sha1 = {name: checksum for checksum, name in [
('e2be7b72a79fe4a750d1dd415afedf01c3ea818d', 'mobilenetv2_0.75'),
('aabd26cd335379fcb72ae6c8fac45a70eab11785', 'mobilenetv2_0.5'),
('ae8f9392789b04822cbb1d98c27283fc5f8aa0a7', 'mobilenetv2_0.25'),
- ('e54b379f50fa4b10bbd2506237e3bd74e6164778', 'resnet18_v1'),
- ('c1dc0967a3d25ee9127e03bc1046a5d44d92e2ba', 'resnet34_v1'),
- ('c940b1a062b32e3a5762f397c9d1e178b5abd007', 'resnet50_v1'),
- ('d992389084bc5475c370e9b52c3561706e755799', 'resnet101_v1'),
- ('48ce7775d375987d019ec9aa96bc43b98165dfcb', 'resnet152_v1'),
- ('84f666402577b5b79cd59eba5d3ba0bc1edf2152', 'resnet18_v2'),
- ('5da34c2772893e9d680d5fa0bd6d432eba8689c9', 'resnet34_v2'),
- ('81a4e66af7859a5aa904e2b4051aa0d3bc472b2f', 'resnet50_v2'),
- ('7eb2b3cde097883c11941b927048a705ed334294', 'resnet101_v2'),
- ('64c75ac8c292f6ac54f873f9ef62e0531105878b', 'resnet152_v2'),
+ ('a0666292f0a30ff61f857b0b66efc0228eb6a54b', 'resnet18_v1'),
+ ('48216ba99a8b1005d75c0f3a0c422301a0473233', 'resnet34_v1'),
+ ('0aee57f96768c0a2d5b23a6ec91eb08dfb0a45ce', 'resnet50_v1'),
+ ('d988c13d6159779e907140a638c56f229634cb02', 'resnet101_v1'),
+ ('671c637a14387ab9e2654eafd0d493d86b1c8579', 'resnet152_v1'),
+ ('a81db45fd7b7a2d12ab97cd88ef0a5ac48b8f657', 'resnet18_v2'),
+ ('9d6b80bbc35169de6b6edecffdd6047c56fdd322', 'resnet34_v2'),
+ ('ecdde35339c1aadbec4f547857078e734a76fb49', 'resnet50_v2'),
+ ('18e93e4f48947e002547f50eabbcc9c83e516aa6', 'resnet101_v2'),
+ ('f2695542de38cf7e71ed58f02893d82bb409415e', 'resnet152_v2'),
('264ba4970a0cc87a4f15c96e25246a1307caf523', 'squeezenet1.0'),
('33ba0f93753c83d86e1eb397f38a667eaf2e9376', 'squeezenet1.1'),
('dd221b160977f36a53f464cb54648d227c707a05', 'vgg11'),
