- attempt symlink to most recent documentation

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-# face-privacy-filter
-A model for face detection and suppression.
-
-## Image Analysis for Face-based Privacy Filtering
-This source code creates and pushes a model into Acumos that processes
-incoming images and outputs a detected faces as well as the original image
-input (if configured that way).  The model uses a [python interface](https://pypi.python.org/pypi/opencv-python)
-to the [OpenCV library](https://opencv.org/) to detect faces and perform
-subsequent image processing.  This module does not support training
-at this time and instead uses a pre-trained face cascade, which is
-included (from OpenCV) in this module.
-
-### Usage
-This package contains runable scripts for command-line evaluation,
-packaging of a model (both dump and posting), and simple web-test
-uses.   All functionality is encapsulsted in the `filter_image.py`
-script and has the following arguments.
-
-```
-usage: run_face-privacy-filter_reference.py [-h] [-p PREDICT_PATH] [-i INPUT]
-                                            [-c] [-s] [-f {detect,pixelate}]
-                                            [-a PUSH_ADDRESS] [-d DUMP_MODEL]
-
-optional arguments:
-  -h, --help            show this help message and exit
-  -p PREDICT_PATH, --predict_path PREDICT_PATH
-                        save detections from model (model must be provided via
-                        'dump_model')
-  -i INPUT, --input INPUT
-                        absolute path to input data (image or csv, only during
-                        prediction / dump)
-  -c, --csv_input       input as CSV format not an image
-  -s, --suppress_image  do not create an extra row for a returned image
-  -f {detect,pixelate}, --function {detect,pixelate}
-                        which type of model to generate
-  -a PUSH_ADDRESS, --push_address PUSH_ADDRESS
-                        server address to push the model (e.g.
-                        http://localhost:8887/v2/models)
-  -d DUMP_MODEL, --dump_model DUMP_MODEL
-                        dump model to a pickle directory for local running
-```
-
-
-### Examples
-This single repo has a number of different models that can be
-composed together for operation.
-
-* Dump the `detect` model to disk.
-```
-./bin/run_local.sh -d model_detect -f detect
-```
-* Dump the `pixelate` model to disk.
-```
-./bin/run_local.sh -d model_pix -f pixelate
-```
-* Evaluate the `detect` model from disk and a previously produced detect object
-```
-./bin/run_local.sh -d model_detect -p output.csv -i web_demo/images/face_DiCaprio.jpg
-```
-* Example for evaluating the `pixelate` model from disk and a previously produced detect object
-```
-./bin/run_local.sh -d model_pix -i detect.csv -p output.jpg --csv_input
-```
-
-
-
-### Installation Troubleshoting
-Using some environment-based versions of python (e.g. conda),
-one problem seemed to come up with the installation of the dependent
-package `opencv-python`.  If you launch your python instance and see
-an error like the one below, keep reading.
-
-```
->>> import cv2
-Traceback (most recent call last):
-  File "<stdin>", line 1, in <module>
-ImportError: dynamic module does not define module export function (PyInit_cv2)
->>>
-```
-
-This is likely because your `PYTHONPATH` is not correctly configured to
-point to the additional installed libraries.
-
-* From the [simple example here](https://stackoverflow.com/a/42160595)
-you can check your environment with `echo $PYTHONPATH`.  If it does not
-contain the directory that you installed to, then you have a problem.
-* Please check your installation by running `python -v -v; import cv2` and checking
-that the last loaded library is in the right location.
-* In some instances, this variable needed to be blank to work properly (i.e.
-`export PYTHONPATH=`) run at some time during start up.
-
-
-## Face-based Use Cases
-This project includes a number of face-based use cases including raw
-detection, blurring, and other image-based modifications based on
-detected image regions.
-
-* **Face Detection Use-case** - This source code creates and pushes a model that processes
-incoming images and outputs detected faces.
-
-## Example Interface
-An instance should first be built and downloaded and then
-launched locally.  Afterwards, the sample application found in
-[web_demo](web_demo) uses a `localhost` service to classify
-and visualize the results of image classification.
-
-* [Commercial example](web_demo/images/commercial.jpg) ([youtube source](https://www.youtube.com/watch?v=34KfCNapnUg))
-* [Reunion face sample](web_demo/images/face_reunion.jpg) ([flickr source](https://flic.kr/p/bEgYbs))
-* [family face example](web_demo/images/face_family.jpg) ([pexel source](https://www.pexels.com/photo/adult-affection-beautiful-beauty-265764/))
-* [DiCaprio celebrity face sample](web_demo/images/face_DiCaprio.jpg) ([wikimedia source](https://en.wikipedia.org/wiki/Celebrity#/media/File:Leonardo_DiCaprio_visited_Goddard_Saturday_to_discuss_Earth_science_with_Piers_Sellers_(26105091624)_cropped.jpg))
-* [Schwarzenegger celebrity face sample](web_demo/images/face_Schwarzenegger.jpg) ([wikimedia source](https://upload.wikimedia.org/wikipedia/commons/thumb/0/0f/A._Schwarzenegger.jpg/220px-A._Schwarzenegger.jpg))
-
-
-before  | after
-------- | -------
-![raw commercial](web_demo/images/commercial.jpg)  | ![pixelated commercial](web_demo/images/commercial_pixelate.jpg)
-![raw face](web_demo/images/face_family.jpg)  | ![pixelated commercial](web_demo/images/face_family_pixelate.jpg)

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