Remove CentOS and Windows instructions as they are dated.

INSTALL.md

@@ -2,8 +2,7 @@
 
 ## Prerequisites
 
-This guide builds a BIQT Docker image which includes the reference BIQTIris and BIQTFace providers. The BIQT Java
-bindings are unavailable in this image.
+This guide builds a BIQT Docker image which includes the reference BIQTContactDetector, BIQTFace, and BIQTIris providers. The BIQT Java bindings are unavailable in this image.
 
 Docker 17 or higher is required.
 
@@ -63,35 +62,4 @@ to start BIQT!
 ```bash
 $> biqt --version
 BIQT v23.04
-```
-
-## Building and Installing
-
-As an administrator, execute the following commands from the VS2013 x64 Cross Tools Command Prompt. By default, a shortcut to 
-this prompt can be found by browsing to `C:\Program Files (x86)\Microsoft Visual Studio 12.0\Common7\Tools\Shortcuts`. Right-click 
-on the shortcut and select 'Run as administrator' from the popup menu.
-
-**Note:** Using the VS2012 x64 Cross Tools Command Prompt Start Menu shortcut will not work!
-
-By default, CMake will attempt to build the BIQT Java bindings. Java bindings can be disabled by adding
-`-DWITH_JAVA=OFF` to the `cmake` command.
-
-```
-git clone git@github.com:mitre/biqt biqt
-cd biqt
-mkdir build
-cmake -G "NMake Makefiles" -DBUILD_STATIC_LIBS=OFF -DBUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release ..
-nmake
-nmake install
-```
-
-
-## Verifying installation.
-
-After installation, you can invoke the BIQT CLI from any command prompt. If you encounter any errors,
-please verify that `JAVA_HOME` and the `PATH` variables are assigned correctly.
-
-```
-$> biqt --version
-BIQT v23.04
 ```

README.md

@@ -17,22 +17,22 @@ integrate the framework into larger systems.
 
 ### Quick Start
 
-Use the [`mitre/biqt`](https://hub.docker.com/r/mitre/biqt) image hosted on Docker Hub to access a preconfigured CentOS 7 environment with the BIQT
-command-line interface. This image includes the BIQTIris and BIQTFace providers.
+Use the [`ghcr.io/mitre/biqt`](https://github.com/mitre/biqt/pkgs/container/biqt) image hosted on GitHub to access a preconfigured Ubuntu 22.04 environment with the BIQT
+command-line interface. This image includes the BIQTFace, BIQTIris, and BIQTContactDetector providers.
 
 The following Linux-based example shows how to start a `mitre/biqt` container capable of accessing and using the 
 biometric images stored in the directory `/path/to/biometric/images` on the host filesystem.
 
 ```bash
-user@localhost:~/$ docker run --rm -v /path/to/images:/data -it mitre/biqt
+user@localhost:~/$ docker run --rm -v /path/to/images:/data -it ghcr.io/mitre/biqt
 [root@66d3679381d0 /]# biqt -m iris iris-image-001.png 
 ```
 
 ### Installation
 
-The framework targets Windows 10 and CentOS Linux 7.4.
+The framework targets Ubuntu 22.04.
 
-Build and install instructions for Docker, CentOS Linux 7.4, and Windows 10 can be found in [INSTALL.md](INSTALL.md).
+Build and install instructions for Docker and Ubuntu 22.04 can be found in [INSTALL.md](INSTALL.md).
 
 ### Integrating Providers
 
@@ -48,24 +48,6 @@ The `setup_provider.py` python script generates a directory structure with templ
 serve as the basis for a new provider. The following example demonstrates how to generate a
 new provider named `MyNewProvider`.
 
-**CentOS Linux 7.4**
-```
-python $BIQT_HOME/scripts/setup_provider.py MyNewProvider
-```
-
-**Windows 10**
-```
-python %BIQT_HOME%/scripts/setup_provider.py MyNewProvider
-```
-
-In the above example, the script creates a directory named `MyNewProvider` in the current directory and populates it with a 
-minimal descriptor, header file, code file, and CMakeLists.txt. TODO elements in each of these files indicate areas 
-which must be addressed.
-
-Once implemented, providers can be built and installed into the framework using the following commands. Note that the BIQT
-framework must already be installed and the BIQT_HOME environment variable must be set.
-
-
 **Ubuntu Linux 22.04**
 
 ```bash
@@ -77,7 +59,6 @@ make
 make install
 ```
 
-
 ### Related Resources
 
 Reference image quality libraries for face and iris images are available on GitHub.