[docs] open release of BVLC models for unrestricted use

See BVLC model license details on the model zoo page.

docs/model_zoo.md

@@ -14,7 +14,9 @@ To help share these models, we introduce the model zoo framework:
 
 ## Where to get trained models
 
-First of all, we provide some trained models out of the box.
+First of all, we bundle BVLC-trained models for unrestricted, out of the box use.
+<br>
+See the [BVLC model license](#bvlc-model-license) for details.
 Each one of these can be downloaded by running `scripts/download_model_binary.py <dirname>` where `<dirname>` is specified below:
 
 - **BVLC Reference CaffeNet** in `models/bvlc_reference_caffenet`: AlexNet trained on ILSVRC 2012, with a minor variation from the version as described in [ImageNet classification with deep convolutional neural networks](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) by Krizhevsky et al. in NIPS 2012. (Trained by Jeff Donahue @jeffdonahue)
@@ -22,7 +24,9 @@ Each one of these can be downloaded by running `scripts/download_model_binary.py
 - **BVLC Reference R-CNN ILSVRC-2013** in `models/bvlc_reference_rcnn_ilsvrc13`: pure Caffe implementation of [R-CNN](https://github.com/rbgirshick/rcnn) as described by Girshick et al. in CVPR 2014. (Trained by Ross Girshick @rbgirshick)
 - **BVLC GoogLeNet** in `models/bvlc_googlenet`: GoogLeNet trained on ILSVRC 2012, almost exactly as described in [Going Deeper with Convolutions](http://arxiv.org/abs/1409.4842) by Szegedy et al. in ILSVRC 2014. (Trained by Sergio Guadarrama @sguada)
 
-User-provided models are posted to a public-editable [wiki page](https://github.com/BVLC/caffe/wiki/Model-Zoo).
+**Community models** made by Caffe users are posted to a publicly editable [wiki page](https://github.com/BVLC/caffe/wiki/Model-Zoo).
+These models are subject to conditions of their respective authors such as citation and license.
+Thank you for sharing your models!
 
 ## Model info format
 
@@ -55,3 +59,12 @@ We host our BVLC-provided models on our own server.
 Dropbox also works fine (tip: make sure that `?dl=1` is appended to the end of the URL).
 
 `scripts/download_model_binary.py <dirname>` downloads the `.caffemodel` from the URL specified in the `<dirname>/readme.md` frontmatter and confirms SHA1.
+
+## BVLC model license
+
+The Caffe models bundled by the BVLC are released for unrestricted use.
+
+These models are trained on data from the [ImageNet project](http://www.image-net.org/) and training data includes internet photos that may be subject to copyright.
+
+Our present understanding as researchers is that there is no restriction placed on the open release of these learned model weights, since none of the original images are distributed in whole or in part.
+To the extent that the interpretation arises that weights are derivative works of the original copyright holder and they assert such a copyright, UC Berkeley makes no representations as to what use is allowed other than to consider our present release in the spirit of fair use in the academic mission of the university to disseminate knowledge and tools as broadly as possible without restriction.

examples/classification.ipynb

@@ -19,7 +19,7 @@
       "\n",
       "Caffe provides a general Python interface for models with `caffe.Net` in `python/caffe/pycaffe.py`, but to make off-the-shelf classification easy we provide a `caffe.Classifier` class and `classify.py` script. Both Python and MATLAB wrappers are provided. However, the Python wrapper has more features so we will describe it here. For MATLAB, refer to `matlab/caffe/matcaffe_demo.m`.\n",
       "\n",
-      "Before we begin, you must compile Caffe and install the python wrapper by setting your `PYTHONPATH`. If you haven't yet done so, please refer to the [installation instructions](installation.html). This example uses our pre-trained CaffeNet model, an ILSVRC12 image classifier. You can download it by running `./scripts/download_model_binary.py models/bvlc_reference_caffenet`. Note that this pre-trained model is licensed for academic research / non-commercial use only.\n",
+      "Before we begin, you must compile Caffe and install the python wrapper by setting your `PYTHONPATH`. If you haven't yet done so, please refer to the [installation instructions](installation.html). This example uses our pre-trained CaffeNet model, an ILSVRC12 image classifier. You can download it by running `./scripts/download_model_binary.py models/bvlc_reference_caffenet`.\n",
       "\n",
       "Ready? Let's start."
      ]

models/bvlc_alexnet/readme.md

@@ -22,6 +22,4 @@ This model was trained by Evan Shelhamer @shelhamer
 
 ## License
 
-The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
-"Researcher shall use the Database only for non-commercial research and educational purposes."
-Accordingly, this model is distributed under a non-commercial license.
+This model is released for unrestricted use.

models/bvlc_googlenet/readme.md

@@ -30,6 +30,4 @@ This model was trained by Sergio Guadarrama @sguada
 
 ## License
 
-The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
-"Researcher shall use the Database only for non-commercial research and educational purposes."
-Accordingly, this model is distributed under a non-commercial license.
+This model is released for unrestricted use.

models/bvlc_reference_caffenet/readme.md

@@ -22,6 +22,4 @@ This model was trained by Jeff Donahue @jeffdonahue
 
 ## License
 
-The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
-"Researcher shall use the Database only for non-commercial research and educational purposes."
-Accordingly, this model is distributed under a non-commercial license.
+This model is released for unrestricted use.

models/bvlc_reference_rcnn_ilsvrc13/readme.md

@@ -17,6 +17,4 @@ This model was trained by Ross Girshick @rbgirshick
 
 ## License
 
-The data used to train this model comes from the ImageNet project, which distributes its database to researchers who agree to a following term of access:
-"Researcher shall use the Database only for non-commercial research and educational purposes."
-Accordingly, this model is distributed under a non-commercial license.
+This model is released for unrestricted use.