Merge branch 'master' of https://github.com/apache/incubator-mxnet

CONTRIBUTORS.md

@@ -178,3 +178,4 @@ List of Contributors
 * [Aaron Markham](https://github.com/aaronmarkham)
 * [Sam Skalicky](https://github.com/samskalicky)
 * [Per Goncalves da Silva](https://github.com/perdasilva)
+* [Cheng-Che Lee](https://github.com/stu1130)

docs/api/python/index.md

@@ -177,4 +177,14 @@ Code examples are placed throughout the API documentation and these can be run a
    :maxdepth: 1
 
    symbol_in_pictures/symbol_in_pictures.md
-```
+```
+
+## Tools
+
+```eval_rst
+.. toctree::
+    :maxdepth: 1
+
+    tools/test_utils.md
+    tools/visualization.md
+```

docs/api/python/tools/test_utils.md

@@ -0,0 +1,27 @@
+# Test Utilities
+
+This module has a variety of tools that help using and testing MXNet.
+
+```eval_rst
+    .. currentmodule:: mxnet.test_utils
+```
+
+```eval_rst
+.. autosummary::
+    :nosignatures:
+
+    mxnet.test_utils
+```
+
+## API Reference
+
+<script type="text/javascript" src='../../../_static/js/auto_module_index.js'></script>
+
+```eval_rst
+
+.. automodule:: mxnet.test_utils
+    :members:
+
+```
+
+<script>auto_index("api-reference");</script>

docs/api/python/tools/visualization.md

@@ -0,0 +1,27 @@
+# Visualization
+
+This module contains visualization features.
+
+```eval_rst
+    .. currentmodule:: mxnet.visualization
+```
+
+```eval_rst
+.. autosummary::
+    :nosignatures:
+
+    mxnet.visualization
+```
+
+## API Reference
+
+<script type="text/javascript" src='../../../_static/js/auto_module_index.js'></script>
+
+```eval_rst
+
+.. automodule:: mxnet.visualization
+    :members:
+
+```
+
+<script>auto_index("api-reference");</script>

docs/community/mxnet_channels.md

@@ -2,9 +2,9 @@
 
 Converse with the MXNet community via the following channels:
 
-- [Forum](https://discuss.mxnet.io/): [discuss.mxnet.io](https://discuss.mxnet.io/) <i class="fas fa-external-link-alt"></i>
-- [MXNet Apache developer mailing list](https://lists.apache.org/[email protected]) ([email protected]): To subscribe, send an email to <a href="mailto:[email protected]">dev[email protected]</a> <i class="far fa-envelope"></i>
-- [MXNet Apache user mailing list](https://lists.apache.org/[email protected]) ([email protected]): To subscribe, send an email to <a href="mailto:[email protected]">user[email protected]</a> <i class="far fa-envelope"></i>
-- [MXNet Slack channel](https://apache-mxnet.slack.com): To request an invitation to the channel please subscribe to the mailing list above and then email: <a href="mailto:[email protected]">[email protected]</a> <i class="far fa-envelope"></i>
+- [Forum](https://discuss.mxnet.io/): [discuss.mxnet.io](https://discuss.mxnet.io/)
+- [MXNet Apache developer mailing list](https://lists.apache.org/[email protected]) ([email protected]): To subscribe, send an email to <a href="mailto:[email protected]">user[email protected]</a>
+- [MXNet Apache user mailing list](https://lists.apache.org/[email protected]) ([email protected]): To subscribe, send an email to <a href="mailto:[email protected]">dev[email protected]</a>
+- [MXNet Slack channel](https://the-asf.slack.com/) (Channel: #mxnet): To request an invitation to the channel please subscribe to the mailing list above and then email: <a href="mailto:[email protected]">[email protected]</a>
 
 Note: if you have an email address with apache.org, you do not need an approval to join the MXNet Slack channel.

example/image-classification/predict-cpp/README.md

@@ -1,13 +1,23 @@
-# Image Classification Example of C++
-This is a simple predictor which shows how to use c api for image classfication.
+# Image Classification Example Using the C Predict API
+This is a simple predictor which shows how to use the MXNet C Predict API for image classification with a pre-trained ImageNet model.
 
-It uses opencv for image reading
+## Prerequisites
 
-# How to Use
+* OpenCV for image processing: `USE_OPENCV` is set to true by default when [building from source](https://mxnet.incubator.apache.org/install/build_from_source.html)
 
-## Build
-1. Edit image-classification-predict.cc file, change the following lines to your model paths:
-  ```bash
+## How to Use this Example
+
+### Download the Model Artifacts
+1. You will need the model artifacts for the Inception ImageNet model. You can download these from http://data.mxnet.io/mxnet/models/imagenet/inception-bn/
+2. Place them into a `model/Inception/` subfolder, or if not, you will need to edit the source file and update the paths in the Build step.
+
+* [model/Inception/Inception-BN-symbol.json](http://data.mxnet.io/mxnet/models/imagenet/inception-bn/Inception-BN-symbol.json)
+* [model/Inception/Inception-BN-0126.params](http://data.mxnet.io/mxnet/models/imagenet/inception-bn/Inception-BN-0126.params)
+* [model/Inception/synset.txt](http://data.mxnet.io/mxnet/models/imagenet/synset.txt)
+
+### Build
+1. If using a different location for the model artifacts, edit `image-classification-predict.cc` file, and change the following lines to your artifacts' paths:
+  ```c
     // Models path for your model, you have to modify it
     std::string json_file = "model/Inception/Inception-BN-symbol.json";
     std::string param_file = "model/Inception/Inception-BN-0126.params";
@@ -16,47 +26,47 @@ It uses opencv for image reading
   ```
 
 2. You may also want to change the image size and channels:
-  ```bash
+  ```c
     // Image size and channels
     int width = 224;
     int height = 224;
     int channels = 3;
   ```
-  
+
 3. Simply just use our Makefile to build:
   ```bash
   make
   ```
 
-## Usage
-Run:
+### Run
+Run the example by passing it an image that you want to classify. If you don't have one handy, run the following to get one:
+
   ```bash
-  ./image-classification-predict apple.jpg
+  wget https://upload.wikimedia.org/wikipedia/commons/thumb/f/f4/Honeycrisp.jpg/1920px-Honeycrisp.jpg
+  ```
+
+Then run the `image-classification-predict` program, passing the image as the argument.
+
+  ```bash
+  ./image-classification-predict 1920px-Honeycrisp.jpg
   ```
-The only parameter is the path of the test image.  
 
 ## Tips
-* The model used in the sample can be downloaded here:
-http://pan.baidu.com/s/1sjXKrqX
-or here:
-http://data.mxnet.io/mxnet/models/imagenet/
 
-* If you don't run it in the mxnet root path, maybe you will need to copy lib folder here.
+* If you don't run it in the MXNet root path, you may need to copy the `lib` folder here.
 
-# Author
+## Author
 * **Xiao Liu**
 
 * E-mail: [email protected]
 
 * Homepage: [www.liuxiao.org](http://www.liuxiao.org/)
 
-# Thanks
+## Thanks
 * pertusa (for Makefile and image reading check)
 
 * caprice-j (for reading function)
 
 * sofiawu (for sample model)
 
 * piiswrong and tqchen (for useful coding suggestions)
-
-

python/mxnet/io/__init__.py

@@ -0,0 +1,29 @@
+#!/usr/bin/env python
+
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+# pylint: disable=wildcard-import
+""" Data iterators for common data formats and utility functions."""
+from __future__ import absolute_import
+
+from . import io
+from .io import *
+
+from . import utils
+from .utils import *