[MXNET] Updated http://data.dmlc.ml/ links to http://data.mxnet.io/ (apache#15065)

* changed http://data.dmlc.ml/ links to http://data.mxnet.io/

* Update get_data.R

* Update get_inception_model.sh

* Update CatsDogsFinetune.Rmd

* Update README.md

Updated pretrained ImageNet model links

Author: IvyBazan

docs/model_zoo/index.md

@@ -53,14 +53,14 @@ For instructions on using these models, see [the python tutorial on using pre-tr
 
 | Model Definition | Dataset | Model Weights | Research Basis | Contributors |
 | --- | --- | --- | --- | --- |
-| [CaffeNet](http://data.dmlc.ml/mxnet/models/imagenet/caffenet/caffenet-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/caffenet/caffenet-0000.params) |   [Krizhevsky, 2012](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) | @jspisak |
-| [Network in Network (NiN)](http://data.dmlc.ml/models/imagenet/nin/nin-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/nin/nin-0000.params) |  [Lin et al.., 2014](https://arxiv.org/pdf/1312.4400v3.pdf) | @jspisak |
-| [SqueezeNet v1.1](http://data.dmlc.ml/models/imagenet/squeezenet/squeezenet_v1.1-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/squeezenet/squeezenet_v1.1-0000.params) | [Iandola et al.., 2016](https://arxiv.org/pdf/1602.07360v4.pdf) | @jspisak |
-| [VGG16](http://data.dmlc.ml/models/imagenet/vgg/vgg16-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/vgg/vgg16-0000.params)| [Simonyan et al.., 2015](https://arxiv.org/pdf/1409.1556v6.pdf) | @jspisak |
-| [VGG19](http://data.dmlc.ml/models/imagenet/vgg/vgg19-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/vgg/vgg19-0000.params) | [Simonyan et al.., 2015](https://arxiv.org/pdf/1409.1556v6.pdf) | @jspisak |
-| [Inception w/ BatchNorm](http://data.dmlc.ml/models/imagenet/inception-bn/Inception-BN-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/inception-bn/Inception-BN-0126.params) | [Szegedy et al.., 2015](https://arxiv.org/pdf/1502.03167.pdf) | @jspisak |
-| [ResidualNet152](http://data.dmlc.ml/models/imagenet/resnet/152-layers/resnet-152-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/resnet/152-layers/resnet-152-0000.params) | [He et al.., 2015](https://arxiv.org/pdf/1512.03385v1.pdf) | @jspisak |
-| [ResNext101-64x4d](http://data.dmlc.ml/models/imagenet/resnext/101-layers/resnext-101-64x4d-symbol.json) | ImageNet | [Param File](http://data.dmlc.ml/models/imagenet/resnext/101-layers/resnext-101-64x4d-0000.params) | [Xie et al.., 2016](https://arxiv.org/pdf/1611.05431.pdf) | @Jerryzcn |
+| [CaffeNet](http://data.mxnet.io/mxnet/models/imagenet/caffenet/caffenet-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/caffenet/caffenet-0000.params) |   [Krizhevsky, 2012](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) | @jspisak |
+| [Network in Network (NiN)](http://data.mxnet.io/models/imagenet/nin/nin-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/nin/nin-0000.params) |  [Lin et al.., 2014](https://arxiv.org/pdf/1312.4400v3.pdf) | @jspisak |
+| [SqueezeNet v1.1](http://data.mxnet.io/models/imagenet/squeezenet/squeezenet_v1.1-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/squeezenet/squeezenet_v1.1-0000.params) | [Iandola et al.., 2016](https://arxiv.org/pdf/1602.07360v4.pdf) | @jspisak |
+| [VGG16](http://data.mxnet.io/models/imagenet/vgg/vgg16-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/vgg/vgg16-0000.params)| [Simonyan et al.., 2015](https://arxiv.org/pdf/1409.1556v6.pdf) | @jspisak |
+| [VGG19](http://data.mxnet.io/models/imagenet/vgg/vgg19-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/vgg/vgg19-0000.params) | [Simonyan et al.., 2015](https://arxiv.org/pdf/1409.1556v6.pdf) | @jspisak |
+| [Inception w/ BatchNorm](http://data.mxnet.io/models/imagenet/inception-bn/Inception-BN-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/inception-bn/Inception-BN-0126.params) | [Szegedy et al.., 2015](https://arxiv.org/pdf/1502.03167.pdf) | @jspisak |
+| [ResidualNet152](http://data.mxnet.io/models/imagenet/resnet/152-layers/resnet-152-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/resnet/152-layers/resnet-152-0000.params) | [He et al.., 2015](https://arxiv.org/pdf/1512.03385v1.pdf) | @jspisak |
+| [ResNext101-64x4d](http://data.mxnet.io/models/imagenet/resnext/101-layers/resnext-101-64x4d-symbol.json) | ImageNet | [Param File](http://data.mxnet.io/models/imagenet/resnext/101-layers/resnext-101-64x4d-0000.params) | [Xie et al.., 2016](https://arxiv.org/pdf/1611.05431.pdf) | @Jerryzcn |
 | Fast-RCNN | PASCAL VOC | [Param File] | [Girshick, 2015](https://arxiv.org/pdf/1504.08083v2.pdf) | |
 | Faster-RCNN | PASCAL VOC | [Param File] | [Ren et al..,2016](https://arxiv.org/pdf/1506.01497v3.pdf) | |
 | Single Shot Detection (SSD) | PASCAL VOC | [Param File] | [Liu et al.., 2016](https://arxiv.org/pdf/1512.02325v4.pdf) | |

example/rcnn/README.md

@@ -43,8 +43,8 @@ Make a directory `data` and follow `py-faster-rcnn` for data preparation instruc
 * [MSCOCO](http://mscoco.org/dataset/) should be in `data/coco` containing `train2017`, `val2017` and `annotations/instances_train2017.json`, `annotations/instances_val2017.json`.
 
 ### Download pretrained ImageNet models
-* [VGG16](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) should be at `model/vgg16-0000.params` from [MXNet model zoo](http://data.dmlc.ml/models/imagenet/vgg/).
-* [ResNet](https://github.com/tornadomeet/ResNet) should be at `model/resnet-101-0000.params` from [MXNet model zoo](http://data.dmlc.ml/models/imagenet/resnet/).
+* [VGG16](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) should be at [/vgg/vgg16-0000.params](http://data.mxnet.io/mxnet/models/imagenet/vgg/vgg16-0000.params) from MXNet model zoo.
+* [ResNet](https://github.com/tornadomeet/ResNet) should be at [/resnet/101-layers/resnet-101-0000.params](http://data.mxnet.io/mxnet/models/imagenet/resnet/101-layers/resnet-101-0000.params) from MXNet model zoo.
 
 ### Training and evaluation
 Use `python3 train.py --dataset $Dataset$ --network $Network$ --pretrained $IMAGENET_MODEL_FILE$ --gpus $GPUS$` to train,