- switch to requirements.txt now that there are
[face-privacy-filter.git] / docs / face-privacy-filter.md
index 9430a8d..aa50aa1 100644 (file)
@@ -10,6 +10,20 @@ 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.
 
+### Package dependencies
+Package dependencies for the core code and testing have been flattened into a
+single file for convenience. Instead of installing this package into your 
+your local environment, execute the command below.
+
+```
+pip install -r requirments.txt
+```
+
+**Note:** If you are using an [anaconda-based environment](https://anaconda.org), 
+you may want to try 
+installing these packages [directly](https://docs.anaconda.com/anaconda-repository/user-guide/tasks/pkgs/download-install-pkg).
+to avoid mixing of `pip` and `conda` package stores. 
+
 ### Usage
 This package contains runable scripts for command-line evaluation,
 packaging of a model (both dump and posting), and simple web-test
@@ -17,9 +31,9 @@ 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]
+usage: filter_image.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
@@ -41,28 +55,10 @@ optional arguments:
 ```
 
 
-### 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
-```
-
 
+# Example Usages
+Please consult the [tutorials](tutorials) dirctory for usage examples
+including an in-place [web page demonstration](tutorials/lesson3.md).
 
 ## Face-based Use Cases
 This project includes a number of face-based use cases including raw
@@ -72,20 +68,7 @@ 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))
-
+# Release Notes
+The [release notes](release-notes.md) catalog additions and modifications
+over various version changes.
 
-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)