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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2018/05/10 04:40:44 UTC

[GitHub] piiswrong closed pull request #10879: add mobilenetv2 pretrained models

piiswrong closed pull request #10879: add mobilenetv2 pretrained models
URL: https://github.com/apache/incubator-mxnet/pull/10879
 
 
   

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diff --git a/docs/api/python/gluon/model_zoo.md b/docs/api/python/gluon/model_zoo.md
index 950e2c02c2d..453fe8d4bdd 100644
--- a/docs/api/python/gluon/model_zoo.md
+++ b/docs/api/python/gluon/model_zoo.md
@@ -42,9 +42,12 @@ The following table summarizes the available models.
 | mobilenet0.5  | [MobileNet 0.5](https://arxiv.org/abs/1704.04861)                                     | 1,342,536    | 0.6307         | 0.8475         | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)              |
 | mobilenet0.75 | [MobileNet 0.75](https://arxiv.org/abs/1704.04861)                                    | 2,601,976    | 0.6738         | 0.8782         | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)              |
 | mobilenet1.0  | [MobileNet 1.0](https://arxiv.org/abs/1704.04861)                                     | 4,253,864    | 0.7105         | 0.9006         | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py)              |
-| mobilenetv2_1.0 | [MobileNetV2 1.0](https://arxiv.org/abs/1801.04381)                                 | 3,539,136    | 0.7159         | 0.9047         | Trained with [script](https://github.com/dmlc/gluon-cv/blob/15ed8a4c71d411b878f0d71d1c7afdce6710c913/scripts/classification/imagenet/train_imagenet.py) |
-| resnet18_v1   | [ResNet-18 V1](http://arxiv.org/abs/1512.03385)                                       | 11,699,112   | 0.7039         | 0.8959         | Trained with [script](https://github.com/dmlc/gluon-cv/blob/15ed8a4c71d411b878f0d71d1c7afdce6710c913/scripts/classification/imagenet/train_imagenet.py) |
-| resnet34_v1   | [ResNet-34 V1](http://arxiv.org/abs/1512.03385)                                       | 21,814,696   | 0.7411         | 0.9184         | Trained with [script](https://github.com/dmlc/gluon-cv/blob/15ed8a4c71d411b878f0d71d1c7afdce6710c913/scripts/classification/imagenet/train_imagenet.py) |
+| mobilenetv2_1.0  | [MobileNetV2 1.0](https://arxiv.org/abs/1801.04381)                                | 3,539,136    | 0.7192         | 0.9056         | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification)                                      |
+| 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)              |
@@ -205,6 +208,9 @@ The following table summarizes the available models.
     mobilenet0_5
     mobilenet0_25
     mobilenet_v2_1_0
+    mobilenet_v2_0_75
+    mobilenet_v2_0_5
+    mobilenet_v2_0_25
 ```
 
 ```eval_rst
diff --git a/python/mxnet/gluon/model_zoo/model_store.py b/python/mxnet/gluon/model_zoo/model_store.py
index 14ec8d0a236..cbd95cfcc8b 100644
--- a/python/mxnet/gluon/model_zoo/model_store.py
+++ b/python/mxnet/gluon/model_zoo/model_store.py
@@ -35,7 +35,10 @@
     ('8e9d539cc66aa5efa71c4b6af983b936ab8701c3', 'mobilenet0.5'),
     ('529b2c7f4934e6cb851155b22c96c9ab0a7c4dc2', 'mobilenet0.75'),
     ('6b8c5106c730e8750bcd82ceb75220a3351157cd', 'mobilenet1.0'),
-    ('3ab4967b7a12a9246a144c9dfff74506cb78a526', 'mobilenetv2_1.0'),
+    ('36da4ff1867abccd32b29592d79fc753bca5a215', 'mobilenetv2_1.0'),
+    ('e2be7b72a79fe4a750d1dd415afedf01c3ea818d', 'mobilenetv2_0.75'),
+    ('aabd26cd335379fcb72ae6c8fac45a70eab11785', 'mobilenetv2_0.5'),
+    ('ae8f9392789b04822cbb1d98c27283fc5f8aa0a7', 'mobilenetv2_0.25'),
     ('e54b379f50fa4b10bbd2506237e3bd74e6164778', 'resnet18_v1'),
     ('c1dc0967a3d25ee9127e03bc1046a5d44d92e2ba', 'resnet34_v1'),
     ('c940b1a062b32e3a5762f397c9d1e178b5abd007', 'resnet50_v1'),


 

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