update links for im2txt and slim

Author: zsdonghao

README.md

@@ -62,11 +62,11 @@ Examples can be found [in this folder](https://github.com/zsdonghao/tensorlayer/
  - VGG 19 (ImageNet). Classification task, see [tutorial_vgg19.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py).
  - InceptionV3 (ImageNet). Classification task, see [tutorial\_inceptionV3_tfslim.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py).
  - Wide ResNet (CIFAR) by [ritchieng](https://github.com/ritchieng/wideresnet-tensorlayer).
- - More CNN implementations of [TF-Slim](https://github.com/tensorflow/models/tree/master/slim#pre-trained-models) can be connected to TensorLayer via SlimNetsLayer.
+ - More CNN implementations of [TF-Slim](https://github.com/tensorflow/models/tree/master/research/slim) can be connected to TensorLayer via SlimNetsLayer.
  - [Spatial Transformer Networks](https://arxiv.org/abs/1506.02025) by [zsdonghao](https://github.com/zsdonghao/Spatial-Transformer-Nets).
  - [U-Net for brain tumor segmentation](https://github.com/zsdonghao/u-net-brain-tumor) by [zsdonghao](https://github.com/zsdonghao/u-net-brain-tumor).
  - Variational Autoencoder (VAE) for (CelebA) by [yzwxx](https://github.com/yzwxx/vae-celebA).
-- Image Captioning - Reimplementation of Google's [im2txt](https://github.com/tensorflow/models/tree/master/im2txt) by [zsdonghao](https://github.com/zsdonghao/Image-Captioning).
+- Image Captioning - Reimplementation of Google's [im2txt](https://github.com/tensorflow/models/tree/master/research/im2txt) by [zsdonghao](https://github.com/zsdonghao/Image-Captioning).
 
 ## Natural Language Processing
  - Recurrent Neural Network (LSTM). Apply multiple LSTM to PTB dataset for language modeling, see [tutorial_ptb_lstm.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_ptb_lstm.py) and [tutorial\_ptb\_lstm\_state\_is_tuple.py](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_ptb_lstm_state_is_tuple.py).

docs/user/example.rst

@@ -22,11 +22,11 @@ Computer Vision
  - VGG 19 (ImageNet). Classification task, see `tutorial_vgg19.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_vgg19.py>`_.
  - InceptionV3 (ImageNet). Classification task, see `tutorial_inceptionV3_tfslim.py <https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_inceptionV3_tfslim.py>`_.
  - Wide ResNet (CIFAR) by `ritchieng <https://github.com/ritchieng/wideresnet-tensorlayer>`_.
- - More CNN implementations of `TF-Slim <https://github.com/tensorflow/models/tree/master/slim#pre-trained-models>`_ can be connected to TensorLayer via SlimNetsLayer.
+ - More CNN implementations of `TF-Slim <https://github.com/tensorflow/models/tree/master/research/slim>`_ can be connected to TensorLayer via SlimNetsLayer.
  - `Spatial Transformer Networks <https://arxiv.org/abs/1506.02025>`_ by `zsdonghao <https://github.com/zsdonghao/Spatial-Transformer-Nets>`_.
  - `U-Net for brain tumor segmentation <https://github.com/zsdonghao/u-net-brain-tumor>`_ by `zsdonghao <https://github.com/zsdonghao/u-net-brain-tumor>`_.
  - Variational Autoencoder (VAE) for (CelebA) by `yzwxx <https://github.com/yzwxx/vae-celebA>`_.
- - Image Captioning - Reimplementation of Google's `im2txt <https://github.com/tensorflow/models/tree/master/im2txt>`_ by `zsdonghao <https://github.com/zsdonghao/Image-Captioning>`_.
+ - Image Captioning - Reimplementation of Google's `im2txt <https://github.com/tensorflow/models/tree/master/research/im2txt>`_ by `zsdonghao <https://github.com/zsdonghao/Image-Captioning>`_.
 
 Natural Language Processing
 ==============================

example/data/greenbackground/0.jpg

@@ -24,7 +24,7 @@
 1. How to combine TensorLayer and TF-Slim ?
 
 Introduction of Slim    : https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/slim
-Slim Pre-trained Models : https://github.com/tensorflow/models/tree/master/slim
+Slim Pre-trained Models : https://github.com/tensorflow/models/tree/master/research/slim
 
 With the help of SlimNetsLayer, all Slim Model can be combined into TensorLayer.
 All models in the following link, end with `return net, end_points`` are available.
@@ -114,7 +114,7 @@ def print_prob(prob):
 
 saver = tf.train.Saver()
 if not os.path.isfile("inception_v3.ckpt"):
-    print("Please download inception_v3 ckpt from : https://github.com/tensorflow/models/tree/master/slim#Pretrained")
+    print("Please download inception_v3 ckpt from : https://github.com/tensorflow/models/tree/master/research/slim")
     exit()
 try:    # TF12+
     saver.restore(sess, "./inception_v3.ckpt")