Docs - Update links in documentation (#91)

Update links to repositories to reflect new organization.

Signed-off-by: David Galiffi <David.Galiffi@amd.com>

README.md

@@ -77,15 +77,15 @@ rocAL can be currently used to perform the following operations either with rand
   + RedHat - `8` / `9`
   + SLES - `15-SP4`
 *  [ROCm](https://rocmdocs.amd.com/en/latest/deploy/linux/installer/install.html) with --usecase=graphics,rocm
-*  [AMD RPP](https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp) - MIVisionX Component
-*  [AMD OpenVX™](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/amd_openvx) and AMD OpenVX™ Extensions: `VX_RPP` and `AMD Media` - MIVisionX Components
+*  [AMD RPP](https://github.com/ROCm/rpp) - MIVisionX Component
+*  [AMD OpenVX™](https://github.com/ROCm/MIVisionX/tree/master/amd_openvx) and AMD OpenVX™ Extensions: `VX_RPP` and `AMD Media` - MIVisionX Components
 *  [Turbo JPEG](https://libjpeg-turbo.org/) - Version 2.0.6.2 from `https://github.com/rrawther/libjpeg-turbo.git`
 *  [Half-precision floating-point](https://half.sourceforge.net) library - Version `1.12.0` or higher
 *  [Google Protobuf](https://developers.google.com/protocol-buffers) - Version `3.12.4` or higher
 *  [LMBD Library](http://www.lmdb.tech/doc/)
 *  [RapidJSON](https://github.com/Tencent/rapidjson)
 *  [PyBind11](https://github.com/pybind/pybind11)
-*  [HIP](https://github.com/ROCm-Developer-Tools/HIP)
+*  [HIP](https://github.com/ROCm/HIP)
 *  OpenMP
 *  C++17
 ## Build instructions
@@ -138,7 +138,7 @@ For the convenience of the developer, we here provide the setup script which wil
 
     + run the setup script to install all the dependencies required
     + run the below commands to build rocAL & test
-    + run tests - [test option instructions](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/wiki/CTest)
+    + run tests - [test option instructions](https://github.com/ROCm/MIVisionX/wiki/CTest)
 
 ```
     python rocAL-setup.py

docker/README.md

@@ -1,9 +1,9 @@
 # rocAL Docker
 
-Docker is a set of platform as a service (PaaS) products that use OS-level virtualization to deliver software in packages called containers. [Read More](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/wiki/Docker)
+Docker is a set of platform as a service (PaaS) products that use OS-level virtualization to deliver software in packages called containers. [Read More](https://github.com/ROCm/MIVisionX/wiki/Docker)
 
 ## Build - dockerfiles
 
 ```
 sudo docker build --build-arg {ARG_NAME}={ARG_VALUE} -f {DOCKER_FILE_NAME}.dockerfile -t {DOCKER_IMAGE_NAME} .
-```
+```

docker/rocal-on-rhel-09.dockerfile

@@ -26,12 +26,12 @@ RUN apt-get update -y && apt-get -y install autoconf automake libbz2-dev libssl-
 RUN apt-get -y install sqlite3 libsqlite3-dev libtool build-essential
 RUN git clone -b v3.21.9 https://github.com/protocolbuffers/protobuf.git && cd protobuf && git submodule update --init --recursive && \
         ./autogen.sh && ./configure && make -j8 && make check -j8 && sudo make install && sudo ldconfig && cd
-RUN git clone -b 0.99  https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.git && cd rpp && mkdir build && cd build && \
+RUN git clone -b 0.99  https://github.com/ROCm/rpp.git && cd rpp && mkdir build && cd build && \
         cmake -DBACKEND=HIP ../ && make -j4 && sudo make install && cd
 
 ENV ROCAL_WORKSPACE=/workspace
 WORKDIR $ROCAL_WORKSPACE
 
 # Install MIVisionX
-RUN git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git && \
+RUN git clone https://github.com/ROCm/MIVisionX.git && \
         mkdir build && cd build && cmake -DBACKEND=HIP -DROCAL=OFF ../MIVisionX && make -j8 && make install

docker/rocal-on-ubuntu-20-with-pytorch-with-mesa.dockerfile

@@ -47,7 +47,7 @@ RUN DEBIAN_FRONTEND=noninteractive apt-get -y install wget libbz2-dev libssl-dev
         git clone -b 2.0.6.2 https://github.com/rrawther/libjpeg-turbo.git && cd libjpeg-turbo && mkdir build && cd build && \
         cmake -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_BUILD_TYPE=RELEASE -DENABLE_STATIC=FALSE -DCMAKE_INSTALL_DOCDIR=/usr/share/doc/libjpeg-turbo-2.0.3 \
         -DCMAKE_INSTALL_DEFAULT_LIBDIR=lib ../ && make -j4 && sudo make install && cd ../../ && \
-        git clone -b 1.1.0  https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.git && cd rpp && mkdir build && cd build && \
+        git clone -b 1.1.0  https://github.com/ROCm/rpp.git && cd rpp && mkdir build && cd build && \
         cmake -DBACKEND=HIP ../ && make -j4 && sudo make install && cd ../../ && \
         git clone -b v3.12.4 https://github.com/protocolbuffers/protobuf.git && cd protobuf && git submodule update --init --recursive && \
         ./autogen.sh && ./configure && make -j8 && make check -j8 && sudo make install && sudo ldconfig && cd
@@ -65,5 +65,5 @@ ENV ROCAL_WORKSPACE=/workspace
 WORKDIR $ROCAL_WORKSPACE
 
 # install MIVisionX 
-RUN git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git && \
+RUN git clone https://github.com/ROCm/MIVisionX.git && \
         mkdir build && cd build && cmake -DBACKEND=HIP -DROCAL=OFF ../MIVisionX && make -j8 && make install

docker/rocal-on-ubuntu-20.dockerfile

@@ -44,7 +44,7 @@ RUN DEBIAN_FRONTEND=noninteractive apt-get -y install wget libbz2-dev libssl-dev
         git clone -b 2.0.6.2 https://github.com/rrawther/libjpeg-turbo.git && cd libjpeg-turbo && mkdir build && cd build && \
         cmake -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_BUILD_TYPE=RELEASE -DENABLE_STATIC=FALSE -DCMAKE_INSTALL_DOCDIR=/usr/share/doc/libjpeg-turbo-2.0.3 \
         -DCMAKE_INSTALL_DEFAULT_LIBDIR=lib ../ && make -j4 && sudo make install && cd ../../ && \
-        git clone -b 1.1.0  https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.git && cd rpp && mkdir build && cd build && \
+        git clone -b 1.1.0  https://github.com/ROCm/rpp.git && cd rpp && mkdir build && cd build && \
         cmake -DBACKEND=HIP ../ && make -j4 && sudo make install && cd ../../ && \
         git clone -b v3.12.4 https://github.com/protocolbuffers/protobuf.git && cd protobuf && git submodule update --init --recursive && \
         ./autogen.sh && ./configure && make -j8 && make check -j8 && sudo make install && sudo ldconfig && cd
@@ -62,5 +62,5 @@ ENV ROCAL_WORKSPACE=/workspace
 WORKDIR $ROCAL_WORKSPACE
 
 # install MIVisionX 
-RUN git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git && \
+RUN git clone https://github.com/ROCm/MIVisionX.git && \
         mkdir build && cd build && cmake -DBACKEND=HIP -DROCAL=OFF ../MIVisionX && make -j8 && make install

docker/rocal-on-ubuntu-22.dockerfile

@@ -48,7 +48,7 @@ RUN apt-get update -y && apt-get -y install autoconf automake libbz2-dev libssl-
 RUN apt-get -y install sqlite3 libsqlite3-dev libtool build-essential
 RUN git clone -b v3.21.9 https://github.com/protocolbuffers/protobuf.git && cd protobuf && git submodule update --init --recursive && \
         ./autogen.sh && ./configure && make -j8 && make check -j8 && sudo make install && sudo ldconfig && cd
-RUN git clone -b 1.1.0  https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.git && cd rpp && mkdir build && cd build && \
+RUN git clone -b 1.1.0  https://github.com/ROCm/rpp.git && cd rpp && mkdir build && cd build && \
         cmake -DBACKEND=HIP ../ && make -j4 && sudo make install && cd
 ENV CUPY_INSTALL_USE_HIP=1
 ENV ROCM_HOME=/opt/rocm
@@ -64,5 +64,5 @@ ENV ROCAL_WORKSPACE=/workspace
 WORKDIR $ROCAL_WORKSPACE
 
 # Install MIVisionX
-RUN git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git && \
+RUN git clone https://github.com/ROCm/MIVisionX.git && \
         mkdir build && cd build && cmake -DBACKEND=HIP -DROCAL=OFF ../MIVisionX && make -j8 && make install

docker/rocal-with-pytorch.dockerfile

@@ -34,7 +34,7 @@ RUN DEBIAN_FRONTEND=noninteractive apt-get -y install wget libbz2-dev libssl-dev
         git clone -b 2.0.6.2 https://github.com/rrawther/libjpeg-turbo.git && cd libjpeg-turbo && mkdir build && cd build && \
         cmake -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_BUILD_TYPE=RELEASE -DENABLE_STATIC=FALSE -DCMAKE_INSTALL_DOCDIR=/usr/share/doc/libjpeg-turbo-2.0.3 \
         -DCMAKE_INSTALL_DEFAULT_LIBDIR=lib ../ && make -j4 && sudo make install && cd ../../ && \
-        git clone -b 1.1.0  https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.git && cd rpp && mkdir build && cd build && \
+        git clone -b 1.1.0  https://github.com/ROCm/rpp.git && cd rpp && mkdir build && cd build && \
         cmake -DBACKEND=HIP ../ && make -j4 && sudo make install && cd ../../ && \
         git clone -b v3.12.4 https://github.com/protocolbuffers/protobuf.git && cd protobuf && git submodule update --init --recursive && \
         ./autogen.sh && ./configure && make -j8 && make check -j8 && sudo make install && sudo ldconfig && cd
@@ -52,5 +52,5 @@ ENV ROCAL_WORKSPACE=/workspace
 WORKDIR $ROCAL_WORKSPACE
 
 # install MIVisionX 
-RUN git clone https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX.git && \
+RUN git clone https://github.com/ROCm/MIVisionX.git && \
         mkdir build && cd build && cmake -DBACKEND=HIP -DROCAL=OFF ../MIVisionX && make -j8 && make install

docs/README.md

@@ -110,7 +110,7 @@ git clone -b mlperf-v1.1-rocal https://github.com/rrawther/MLPerf-mGPU
 
 ### MIVisionX Pytorch Docker
 
-* Refer to the [docker](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX#docker) page for prerequisites and information on building the docker
+* Refer to the [docker](https://github.com/ROCm/MIVisionX#docker) page for prerequisites and information on building the docker
 * Step 1: Run the docker image*
 ````
 sudo docker run -it -v <Path-To-Data-HostSystem>:/data -v /<Path-to-GitRepo>:/dockerx -w /dockerx --privileged --device=/dev/kfd --device=/dev/dri --group-add video --shm-size=4g --ipc="host" --network=host <docker-name>

docs/user_guide/ch1.md

@@ -80,4 +80,4 @@ rocAL operators offer the flexibility to run on CPU or GPU for building hybrid p
 | Image_random_crop | Decodes and randomly crops JPEG images |
 | Image_slice       | Decodes and slices JPEG images         |
 
-To see examples demonstrating the usage of decoders and readers, [click here](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/rocAL/rocAL_pybind/examples)
+To see examples demonstrating the usage of decoders and readers, [click here](https://github.com/ROCm/MIVisionX/tree/master/rocAL/rocAL_pybind/examples)

docs/user_guide/ch2.md

@@ -18,4 +18,4 @@ Figure 2.	rocAL Master-Graph Architecture
 
 RPP is a comprehensive high-performance computer vision library optimized for the AMD CPU and GPU with HIP and OpenCL backends. It is available under the AMD ROCm software platform. It provides low-level functionality for all rocAL operators for single, image, and tensor datatypes. RPP provides an extensive library for vision augmentations that includes vision functions, color augmentations, filter augmentations, geometric distortions, and a few more features. 
 
-For more information on RPP along with the list of supported kernels, see https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp.
+For more information on RPP along with the list of supported kernels, see https://github.com/ROCm/rpp.

docs/user_guide/ch3.md

@@ -5,8 +5,8 @@ This chapter provides information about the installation of rocAL and related pa
 ## 3.1 Prerequisites 
 
 * Linux distribution
-*  [AMD RPP](https://github.com/GPUOpen-ProfessionalCompute-Libraries/rpp)
-*  [AMD OpenVX™](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/amd_openvx) and AMD OpenVX™ Extensions: `VX_RPP` and `AMD Media`
+*  [AMD RPP](https://github.com/ROCm/rpp)
+*  [AMD OpenVX™](https://github.com/ROCm/MIVisionX/tree/master/amd_openvx) and AMD OpenVX™ Extensions: `VX_RPP` and `AMD Media`
 *  [Turbo JPEG](https://libjpeg-turbo.org/) - Version `2.0` or higher
 *  [Half-precision floating-point](https://half.sourceforge.net) library - Version `1.12.0` or higher
 *  [Google Protobuf](https://developers.google.com/protocol-buffers) - Version `3.12.4` or higher
@@ -20,23 +20,23 @@ To see the list of supported platforms for rocAL, see the ROCm Installation Guid
 
 ## 3.3 Installing rocAL 
 
-rocAL is shipped along with MIVisionX. To build and install the rocAL C++ library, follow the instructions given [here](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX#build--install-mivisionx)
+rocAL is shipped along with MIVisionX. To build and install the rocAL C++ library, follow the instructions given [here](https://github.com/ROCm/MIVisionX#build--install-mivisionx)
 
 ## 3.4 Installing rocAL Python Package 
 
 The rocAL Python package (rocal_pybind) is a separate redistributable wheel. rocal_pybind, which is created using Pybind11, enables data transfer between rocAL C++ API and Python API. With the help of rocal_pybind.so wrapper library, the rocAL functionality, which is primarily in C/C++, can be effectively used in Python. 
 The Python package supports PyTorch, TensorFlow, Caffe2, and data readers available for various formats such as FileReader, COCO Reader, TFRecord Reader, and CaffeReader.
 
-To build and install the Python package, see [rocAL python](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/rocAL/rocAL_pybind).
+To build and install the Python package, see [rocAL python](https://github.com/ROCm/MIVisionX/tree/master/rocAL/rocAL_pybind).
 
 ## 3.5 Installing rocAL Using Framework Dockers
 
 To test the rocAL Python APIs using PyTorch or TensorFlow, we recommend building a docker with rocAL and ROCm using any of the links below:
 
-- [rocAL PyTorch docker](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker/pytorch)
-- [rocAL TensorFlow docker](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker/tensorflow)
+- [rocAL PyTorch docker](https://github.com/ROCm/MIVisionX/tree/master/docker/pytorch)
+- [rocAL TensorFlow docker](https://github.com/ROCm/MIVisionX/tree/master/docker/tensorflow)
 
 To use rocAL on Ubuntu, use the following dockers:
 
-- [rocAL on ubuntu20](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/blob/master/docker/mivisionx-on-ubuntu20.dockerfile)
-- [rocAL on Ubuntu22](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/blob/master/docker/mivisionx-on-ubuntu22.dockerfile)
+- [rocAL on ubuntu20](https://github.com/ROCm/MIVisionX/blob/master/docker/mivisionx-on-ubuntu20.dockerfile)
+- [rocAL on Ubuntu22](https://github.com/ROCm/MIVisionX/blob/master/docker/mivisionx-on-ubuntu22.dockerfile)

docs/user_guide/ch4.md

@@ -182,7 +182,7 @@ show_images(images)
 
 ## 4.3 rocAL Data Types
 
-All the rocAL data types are defined under [amd.rocal.types](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/blob/master/rocAL/rocAL_pybind/amd/rocal/types.py). Import this library in the application to access the various data types such as rocAL status, processing mode, tensor output type, image size evaluation policy, image color, tensor layout, decode device, resize scaling mode, and resize interpolation type. 
+All the rocAL data types are defined under [amd.rocal.types](https://github.com/ROCm/MIVisionX/blob/master/rocAL/rocAL_pybind/amd/rocal/types.py). Import this library in the application to access the various data types such as rocAL status, processing mode, tensor output type, image size evaluation policy, image color, tensor layout, decode device, resize scaling mode, and resize interpolation type. 
 
 Here are some of the commonly used rocAL data types:
 

docs/user_guide/ch5.md

@@ -159,6 +159,6 @@ Run the training Session
                 train_label_one_hot_list = get_label_one_hot(train_label_ndArray)
 ```
 
-4. Run the training as shown [here](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/rocAL/rocAL_pybind/examples/tf_petsTrainingExample).
+4. Run the training as shown [here](https://github.com/ROCm/MIVisionX/tree/master/rocAL/rocAL_pybind/examples/tf_petsTrainingExample).
 
-To see a sample training script, click [here](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/rocAL/rocAL_pybind/examples/tf_petsTrainingExample).
+To see a sample training script, click [here](https://github.com/ROCm/MIVisionX/tree/master/rocAL/rocAL_pybind/examples/tf_petsTrainingExample).

docs/user_guide/ch6.md

@@ -72,7 +72,7 @@ extern "C"  RocalStatus  ROCAL_API_CALL rocalRelease(RocalContext rocal_context)
 
 ## 6.1.5 Image Augmentation Using C++ API
 
-The example below shows how to create a pipeline, read JPEG images, perform certain augmentations on them, and show the output using OpenCV by utilizing C++ [APIs](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/blob/develop/apps/image_augmentation/image_augmentation.cpp#L103).
+The example below shows how to create a pipeline, read JPEG images, perform certain augmentations on them, and show the output using OpenCV by utilizing C++ [APIs](https://github.com/ROCm/MIVisionX/blob/develop/apps/image_augmentation/image_augmentation.cpp#L103).
 
 ```
 Auto handle = rocalCreate(inputBatchSize, processing_device?RocalProcessMode::ROCAL_PROCESS_GPU:RocalProcessMode::ROCAL_PROCESS_CPU, 0,1);
@@ -109,4 +109,4 @@ while (!rocalIsEmpty(handle))
 }
 ```
 
-To see a sample image augmentation application in C++, click [here](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/develop/apps/image_augmentation). 
+To see a sample image augmentation application in C++, click [here](https://github.com/ROCm/MIVisionX/tree/develop/apps/image_augmentation). 

rocAL_pybind/examples/README.md

@@ -9,7 +9,7 @@ rocAL_api_python_unittest=1
 rocAL_api_coco_pipeline=0
 
 ## INSTALL PYBIND TO RUN ANY TESTS
-* [rocAL Pybind Installation](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/README.md)
+* [rocAL Pybind Installation](https://github.com/ROCm/MIVisionX/tree/master/README.md)
 
 ## EXPORT ROCAL_DATA_PATH
 export ROCAL_DATA_PATH=/Absolute/Path/Of/rocal_data/

rocAL_pybind/examples/tf_petsTrainingExample/README.md

@@ -1,11 +1,11 @@
 ## Running tf_petsTrainingExample
 
 ### Building the required TF Rocm docker
-* Use the instructions in the [docker section](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker) to build the required [Tensorflow docker](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker/tensorflow)
+* Use the instructions in the [docker section](https://github.com/ROCm/MIVisionX/tree/master/docker) to build the required [Tensorflow docker](https://github.com/ROCm/MIVisionX/tree/master/docker/tensorflow)
 * Upgrade pip to the latest version.
 
 ### Building the required Pytorch Rocm docker
-* Use the instructions in the [docker section](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker) to build the required [Pytorch docker](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/tree/master/docker/pytorch)
+* Use the instructions in the [docker section](https://github.com/ROCm/MIVisionX/tree/master/docker) to build the required [Pytorch docker](https://github.com/ROCm/MIVisionX/tree/master/docker/pytorch)
 * Upgrade pip to the latest version.
 * Run requirements.sh to install the required packages.
 

rocAL_pybind/setup.py

@@ -40,7 +40,7 @@ def has_ext_modules(self):
 setup(
       name='amd-rocal',
       description='AMD ROCm Augmentation Library',
-      url='https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX/rocAL',
+      url='https://github.com/ROCm/MIVisionX/rocAL',
       version='1.0.0',
       author='AMD',
       license='Apache License 2.0',

tests/cpp_api_tests/rocAL_unittests/README.md

@@ -32,7 +32,7 @@ Usage: ./rocAL_unittests reader-type pipeline-type=1(classification)2(detection)
 
 The bash script `testAllScript.sh` can be used to run and dump the outputs for all test cases in rocAL and run the python script to verify the correctness of the generated outputs with the golden outputs.
 
-Input data is available in the following link : [MIVisionX-data](https://github.com/GPUOpen-ProfessionalCompute-Libraries/MIVisionX-data)
+Input data is available in the following link : [MIVisionX-data](https://github.com/ROCm/MIVisionX-data)
 
 `export ROCAL_DATA_PATH=<absolute_path_to_MIVIsionX-data>`