* Upgrade presets for FFmpeg 6.1.1, DNNL 3.3.4, OpenBLAS 0.3.26, Num…

…Py 1.26.3, Leptonica 1.84.1, CUDA 12.3.2

.github/actions/deploy-ubuntu/action.yml

@@ -31,7 +31,7 @@ runs:
           export ARCH=arm64
           export ARCH_CUDA=sbsa
           export PREFIX=aarch64-linux-gnu
-          export CUDA=cuda-repo-rhel8-12-3-local-12.3.1_545.23.08-1.aarch64.rpm
+          export CUDA=cuda-repo-rhel8-12-3-local-12.3.2_545.23.08-1.aarch64.rpm
           export CUDNN=8.9.7.29-1.cuda12.2.aarch64
           export NCCL=2.19.3-1+cuda12.3.aarch64
           export NVCOMP=nvcomp_3.0.5_SBSA_12.x
@@ -40,7 +40,7 @@ runs:
           export ARCH=ppc64el
           export ARCH_CUDA=ppc64le
           export PREFIX=powerpc64le-linux-gnu
-          export CUDA=cuda-repo-rhel8-12-3-local-12.3.1_545.23.08-1.ppc64le.rpm
+          export CUDA=cuda-repo-rhel8-12-3-local-12.3.2_545.23.08-1.ppc64le.rpm
           export CUDNN=8.9.7.29-1.cuda12.2.ppc64le
           export NCCL=2.19.3-1+cuda12.3.ppc64le
         elif [[ "$CI_DEPLOY_PLATFORM" == "linux-x86" ]]; then
@@ -50,7 +50,7 @@ runs:
           export ARCH=amd64
           export ARCH_CUDA=x86_64
           export PREFIX=x86_64-linux-gnu
-          export CUDA=cuda-repo-rhel8-12-3-local-12.3.1_545.23.08-1.x86_64.rpm
+          export CUDA=cuda-repo-rhel8-12-3-local-12.3.2_545.23.08-1.x86_64.rpm
           export CUDNN=8.9.7.29-1.cuda12.2.x86_64
           export NCCL=2.19.3-1+cuda12.3.x86_64
           export NVCOMP=nvcomp_3.0.5_x86_64_12.x
@@ -140,7 +140,7 @@ runs:
 
         if [[ -n ${ARCH_CUDA:-} ]] && [[ -n ${CI_DEPLOY_NEED_CUDA:-} ]]; then
           echo Installing CUDA, cuDNN, nvCOMP, etc
-          curl -LO https://developer.download.nvidia.com/compute/cuda/12.3.1/local_installers/$CUDA
+          curl -LO https://developer.download.nvidia.com/compute/cuda/12.3.2/local_installers/$CUDA
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libcudnn8-$CUDNN.rpm
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libcudnn8-devel-$CUDNN.rpm
           curl -LO https://developer.download.nvidia.com/compute/cuda/repos/rhel8/$ARCH_CUDA/libnccl-$NCCL.rpm
@@ -200,14 +200,16 @@ runs:
 
         if [[ "$CI_DEPLOY_PLATFORM" == "linux-arm64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
           echo Installing TensorRT
-          python3 -m gdown.cli https://drive.google.com/uc?id=1LZRCv4ZAGiDQAu4pvADJIGntq4cGl5tU
+          # python3 -m gdown.cli https://drive.google.com/uc?id=1LZRCv4ZAGiDQAu4pvADJIGntq4cGl5tU
+          curl -LO https://github.com/bytedeco/binaries/releases/download/1.5.10/TensorRT-8.6.1.6.Ubuntu-20.04.aarch64-gnu.cuda-12.0.tar.gz
           $SUDO tar -hxvf TensorRT-8.6.1.6.Ubuntu-20.04.aarch64-gnu.cuda-12.0.tar.gz -C /usr/local/
           $SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
         fi
 
         if [[ "$CI_DEPLOY_PLATFORM" == "linux-x86_64" ]] && [[ "$CI_DEPLOY_MODULE" == "tensorrt" ]]; then
           echo Installing TensorRT
-          python3 -m gdown.cli https://drive.google.com/uc?id=1dVhD-DEYY42QbZe1GXl-vxe3k6KqWGsL
+          # python3 -m gdown.cli https://drive.google.com/uc?id=1dVhD-DEYY42QbZe1GXl-vxe3k6KqWGsL
+          curl -LO https://github.com/bytedeco/binaries/releases/download/1.5.10/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz
           $SUDO tar -hxvf TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz -C /usr/local/
           $SUDO ln -sf /usr/local/TensorRT* /usr/local/tensorrt
         fi

.github/actions/deploy-windows/action.yml

@@ -94,15 +94,16 @@ runs:
         if "%CI_DEPLOY_PLATFORM%"=="windows-x86_64" if not "%CI_DEPLOY_NEED_CUDA%"=="" (
           echo Installing CUDA, cuDNN, nvCOMP, etc
           curl -LO https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_522.06_windows.exe
-          curl -LO https://developer.download.nvidia.com/compute/cuda/12.3.1/local_installers/cuda_12.3.1_546.12_windows.exe
+          curl -LO https://developer.download.nvidia.com/compute/cuda/12.3.2/local_installers/cuda_12.3.2_546.12_windows.exe
           rem curl -LO https://developer.download.nvidia.com/compute/redist/cudnn/v8.8.0/local_installers/12.0/cudnn_8.8.0.121_windows.exe
-          python -m gdown.cli https://drive.google.com/uc?id=135Z7zfwguQe6vn7p013HtVkHFu9-_rru
+          rem python -m gdown.cli https://drive.google.com/uc?id=135Z7zfwguQe6vn7p013HtVkHFu9-_rru
+          curl -LO https://github.com/bytedeco/binaries/releases/download/1.5.10/cudnn-windows-x86_64-8.9.7.29_cuda12-archive.zip
           curl -LO http://www.winimage.com/zLibDll/zlib123dllx64.zip
           curl -LO https://developer.download.nvidia.com/compute/nvcomp/3.0.5/local_installers/nvcomp_3.0.5_windows_12.x.zip
           cuda_11.8.0_522.06_windows.exe -s
           bash -c "rm -Rf 'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.8'"
           bash -c "mv 'C:/Program Files/NVIDIA Corporation/NvToolsExt' 'C:/Program Files/NVIDIA Corporation/NvToolsExt_old'"
-          cuda_12.3.1_546.12_windows.exe -s
+          cuda_12.3.2_546.12_windows.exe -s
           bash -c "mv 'C:/Program Files/NVIDIA Corporation/NvToolsExt_old' 'C:/Program Files/NVIDIA Corporation/NvToolsExt'"
           bash -c "ls 'C:/Program Files/NVIDIA Corporation/NvToolsExt'"
           rem cudnn_8.8.0.121_windows.exe -s
@@ -143,7 +144,8 @@ runs:
 
         if "%CI_DEPLOY_MODULE%"=="tensorrt" (
           echo Installing TensorRT
-          python -m gdown.cli https://drive.google.com/uc?id=1GfmJ1BKbacLpUU-0i_mGu0sjrAS0Xzzi
+          rem python -m gdown.cli https://drive.google.com/uc?id=1GfmJ1BKbacLpUU-0i_mGu0sjrAS0Xzzi
+          curl -LO https://github.com/bytedeco/binaries/releases/download/1.5.10/TensorRT-8.6.1.6.Windows10.x86_64.cuda-12.0.zip
           unzip TensorRT-8.6.1.6.Windows10.x86_64.cuda-12.0.zip
           move TensorRT-8.6.1.6 "%ProgramFiles%\NVIDIA GPU Computing Toolkit\TensorRT"
         )
@@ -229,7 +231,7 @@ runs:
           set "CUDA_PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3"
           set "CUDA_PATH_V12_3=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3"
           set "PATH=%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3\bin;%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3\libnvvp;%PATH%"
-          echo CUDA Version 12.3.1>"%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3\version.txt"
+          echo CUDA Version 12.3.2>"%ProgramFiles%\NVIDIA GPU Computing Toolkit\CUDA\v12.3\version.txt"
         )
         set "CCACHE_DIR=%USERPROFILE%\ccache"
         set "PATH=C:\hostedtoolcache\windows\Python\3.9.13\x64;C:\msys64\%MSYSTEM%\bin;C:\msys64\usr\bin;%ProgramFiles%\apache-maven-3.6.3\bin;%PATH%"

CHANGELOG.md

@@ -5,7 +5,7 @@
  * Refactor and improve presets for PyTorch ([pull #1360](https://github.com/bytedeco/javacpp-presets/pull/1360))
  * Include `mkl_lapack.h` header file in presets for MKL ([issue #1388](https://github.com/bytedeco/javacpp-presets/issues/1388))
  * Map new higher-level C++ API of Triton Inference Server ([pull #1361](https://github.com/bytedeco/javacpp-presets/pull/1361))
- * Upgrade presets for OpenCV 4.9.0, FFmpeg 6.1, HDF5 1.14.3, MKL 2024.0, DNNL 3.3.3, OpenBLAS 0.3.25, ARPACK-NG 3.9.1, CPython 3.12.1, NumPy 1.26.2, SciPy 1.11.4, LLVM 17.0.6, Leptonica 1.84.0, Tesseract 5.3.3, CUDA 12.3.1, cuDNN 8.9.7, NCCL 2.19.3, OpenCL 3.0.15, PyTorch 2.1.2 ([pull #1426](https://github.com/bytedeco/javacpp-presets/pull/1426)), TensorFlow Lite 2.15.0, Triton Inference Server 2.41.0, DepthAI 2.24.0, ONNX 1.15.0, ONNX Runtime 1.16.3, TVM 0.14.0, and their dependencies
+ * Upgrade presets for OpenCV 4.9.0, FFmpeg 6.1.1, HDF5 1.14.3, MKL 2024.0, DNNL 3.3.4, OpenBLAS 0.3.26, ARPACK-NG 3.9.1, CPython 3.12.1, NumPy 1.26.3, SciPy 1.11.4, LLVM 17.0.6, Leptonica 1.84.1, Tesseract 5.3.3, CUDA 12.3.2, cuDNN 8.9.7, NCCL 2.19.3, OpenCL 3.0.15, PyTorch 2.1.2 ([pull #1426](https://github.com/bytedeco/javacpp-presets/pull/1426)), TensorFlow Lite 2.15.0, Triton Inference Server 2.41.0, DepthAI 2.24.0, ONNX 1.15.0, ONNX Runtime 1.16.3, TVM 0.14.0, and their dependencies
 
 ### June 6, 2023 version 1.5.9
  * Virtualize `nvinfer1::IGpuAllocator` from TensorRT to allow customization ([pull #1367](https://github.com/bytedeco/javacpp-presets/pull/1367))

README.md

@@ -199,7 +199,7 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * MKL 2024.x  https://software.intel.com/mkl
  * MKL-DNN 0.21.x  https://github.com/oneapi-src/oneDNN
  * DNNL 3.3.x  https://github.com/oneapi-src/oneDNN
- * OpenBLAS 0.3.25  http://www.openblas.net/
+ * OpenBLAS 0.3.26  http://www.openblas.net/
  * ARPACK-NG 3.9.x  https://github.com/opencollab/arpack-ng
  * CMINPACK 1.3.8  https://github.com/devernay/cminpack
  * FFTW 3.3.10  http://www.fftw.org/download.html

arpack-ng/platform/pom.xml

@@ -24,7 +24,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>openblas-platform</artifactId>
-      <version>0.3.25-${project.parent.version}</version>
+      <version>0.3.26-${project.parent.version}</version>
     </dependency>
     <dependency>
       <groupId>${project.groupId}</groupId>

arpack-ng/pom.xml

@@ -22,7 +22,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>openblas</artifactId>
-      <version>0.3.25-${project.parent.version}</version>
+      <version>0.3.26-${project.parent.version}</version>
     </dependency>
     <dependency>
       <groupId>org.bytedeco</groupId>
@@ -45,12 +45,12 @@
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
           </dependency>
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
             <classifier>${javacpp.platform}</classifier>
           </dependency>
         </dependencies>

cminpack/platform/pom.xml

@@ -23,7 +23,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>openblas-platform</artifactId>
-      <version>0.3.25-${project.parent.version}</version>
+      <version>0.3.26-${project.parent.version}</version>
     </dependency>
     <dependency>
       <groupId>${project.groupId}</groupId>

cminpack/pom.xml

@@ -18,7 +18,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>openblas</artifactId>
-      <version>0.3.25-${project.parent.version}</version>
+      <version>0.3.26-${project.parent.version}</version>
     </dependency>
     <dependency>
       <groupId>org.bytedeco</groupId>
@@ -41,12 +41,12 @@
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
           </dependency>
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
             <classifier>${javacpp.platform}</classifier>
           </dependency>
         </dependencies>

cpython/cppbuild.sh

@@ -7,7 +7,7 @@ if [[ -z "$PLATFORM" ]]; then
     exit
 fi
 
-OPENSSL=openssl-3.1.4
+OPENSSL=openssl-3.2.0
 CPYTHON_VERSION=3.12.1
 download https://www.openssl.org/source/$OPENSSL.tar.gz $OPENSSL.tar.gz
 download https://www.python.org/ftp/python/$CPYTHON_VERSION/Python-$CPYTHON_VERSION.tgz Python-$CPYTHON_VERSION.tgz

cuda/README.md

@@ -25,7 +25,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * CUDA 12.3.1  https://developer.nvidia.com/cuda-zone
+ * CUDA 12.3.2  https://developer.nvidia.com/cuda-zone
  * cuDNN 8.9.7  https://developer.nvidia.com/cudnn
  * NCCL 2.19.3  https://developer.nvidia.com/nccl
  * nvCOMP 3.0.5  https://developer.nvidia.com/nvcomp

depthai/pom.xml

@@ -42,7 +42,7 @@
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
           </dependency>
           <dependency>
             <groupId>org.bytedeco</groupId>
@@ -52,7 +52,7 @@
           <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>openblas</artifactId>
-            <version>0.3.25-${project.parent.version}</version>
+            <version>0.3.26-${project.parent.version}</version>
             <classifier>${javacpp.platform}</classifier>
           </dependency>
           <dependency>

dnnl/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * DNNL 3.3.3  https://01.org/dnnl
+ * DNNL 3.3.4  https://01.org/dnnl
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
 
@@ -25,7 +25,7 @@ Sample Usage
 ------------
 Here is a simple example of DNNL ported to Java from this C++ source file:
 
- * https://github.com/oneapi-src/oneDNN/blob/v3.3.3/examples/cnn_inference_int8.cpp
+ * https://github.com/oneapi-src/oneDNN/blob/v3.3.4/examples/cnn_inference_int8.cpp
 
 We can use [Maven 3](http://maven.apache.org/) to download and install automatically all the class files as well as the native binaries. To run this sample code, after creating the `pom.xml` and `CpuCnnInferenceInt8.java` source files below, simply execute on the command line:
 ```bash
@@ -46,7 +46,7 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>dnnl-platform</artifactId>
-            <version>3.3.3-1.5.10-SNAPSHOT</version>
+            <version>3.3.4-1.5.10-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

dnnl/cppbuild.sh

@@ -11,7 +11,7 @@ export DNNL_CPU_RUNTIME="OMP" # or TBB
 export DNNL_GPU_RUNTIME="OCL"
 
 TBB_VERSION=2020.3
-MKLDNN_VERSION=3.3.3
+MKLDNN_VERSION=3.3.4
 download https://github.com/oneapi-src/oneTBB/archive/v$TBB_VERSION.tar.gz oneTBB-$TBB_VERSION.tar.bz2
 download https://github.com/oneapi-src/oneDNN/archive/v$MKLDNN_VERSION.tar.gz oneDNN-$MKLDNN_VERSION.tar.bz2
 

dnnl/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>dnnl-platform</artifactId>
-  <version>3.3.3-${project.parent.version}</version>
+  <version>3.3.4-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for DNNL</name>
 
   <properties>

dnnl/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>dnnl</artifactId>
-  <version>3.3.3-${project.parent.version}</version>
+  <version>3.3.4-${project.parent.version}</version>
   <name>JavaCPP Presets for DNNL</name>
 
   <dependencies>

dnnl/samples/pom.xml

@@ -12,7 +12,7 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>dnnl-platform</artifactId>
-            <version>3.3.3-1.5.10-SNAPSHOT</version>
+            <version>3.3.4-1.5.10-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

dnnl/src/gen/java/org/bytedeco/dnnl/global/dnnl.java

@@ -3475,7 +3475,7 @@ public class dnnl extends org.bytedeco.dnnl.presets.dnnl {
 public static final int DNNL_VERSION_MINOR = 3;
 
 /** Patch version */
-public static final int DNNL_VERSION_PATCH = 3;
+public static final int DNNL_VERSION_PATCH = 4;
 
 /** Git commit hash */
 public static native @MemberGetter String DNNL_VERSION_HASH();

ffmpeg/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * FFmpeg 6.1  http://ffmpeg.org/
+ * FFmpeg 6.1.1  http://ffmpeg.org/
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
 
@@ -46,14 +46,14 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>ffmpeg-platform</artifactId>
-            <version>6.1-1.5.10-SNAPSHOT</version>
+            <version>6.1.1-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Optional GPL builds with (almost) everything enabled -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>ffmpeg-platform-gpl</artifactId>
-            <version>6.1-1.5.10-SNAPSHOT</version>
+            <version>6.1.1-1.5.10-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

ffmpeg/cppbuild.sh

@@ -32,8 +32,8 @@ SPEEX=speex-1.2.1
 OPUS=opus-1.3.1
 OPENCORE_AMR=opencore-amr-0.1.6
 VO_AMRWBENC=vo-amrwbenc-0.1.3
-OPENSSL=openssl-3.1.4
-OPENH264_VERSION=2.3.1
+OPENSSL=openssl-3.2.0
+OPENH264_VERSION=2.4.0
 X264=x264-stable
 X265=3.4
 VPX_VERSION=1.13.1
@@ -44,9 +44,9 @@ NVCODEC_VERSION=12.1.14.0
 XML2=libxml2-2.9.12
 LIBSRT_VERSION=1.5.3
 WEBP_VERSION=1.3.2
-AOMAV1_VERSION=3.7.0
-SVTAV1_VERSION=1.7.0
-FFMPEG_VERSION=6.1
+AOMAV1_VERSION=3.8.0
+SVTAV1_VERSION=1.8.0
+FFMPEG_VERSION=6.1.1
 download https://download.videolan.org/contrib/nasm/nasm-$NASM_VERSION.tar.gz nasm-$NASM_VERSION.tar.gz
 download http://zlib.net/$ZLIB.tar.gz $ZLIB.tar.gz
 download http://downloads.sourceforge.net/project/lame/lame/3.100/$LAME.tar.gz $LAME.tar.gz
@@ -396,7 +396,7 @@ EOF
         cd ../libaom-$AOMAV1_VERSION
         mkdir -p build_release
         cd build_release
-        $CMAKE -DCMAKE_TOOLCHAIN_FILE=${PLATFORM_ROOT}/build/cmake/android.toolchain.cmake -DANDROID_ABI=arm64-v8a -DANDROID_NATIVE_API_LEVEL=24 -DCMAKE_C_FLAGS="-I$INSTALL_PATH/include/" -DCMAKE_CXX_FLAGS="-I$INSTALL_PATH/include/" -DCMAKE_EXE_LINKER_FLAGS="-L$INSTALL_PATH/lib/" -DCMAKE_INSTALL_PREFIX=$INSTALL_PATH $LIBAOM_CONFIG -DCONFIG_RUNTIME_CPU_DETECT:BOOL=OFF ..
+        $CMAKE -DCMAKE_TOOLCHAIN_FILE=${PLATFORM_ROOT}/build/cmake/android.toolchain.cmake -DANDROID_ABI=arm64-v8a -DANDROID_NATIVE_API_LEVEL=24 -DCMAKE_C_FLAGS="-I$INSTALL_PATH/include/" -DCMAKE_CXX_FLAGS="-I$INSTALL_PATH/include/" -DCMAKE_EXE_LINKER_FLAGS="-L$INSTALL_PATH/lib/" -DCMAKE_INSTALL_PREFIX=$INSTALL_PATH $LIBAOM_CONFIG -DCONFIG_RUNTIME_CPU_DETECT:BOOL=OFF -DENABLE_NEON_I8MM=OFF ..
         make -j $MAKEJ
         make install
         cd ..
@@ -1647,7 +1647,7 @@ EOF
         cd ../libaom-$AOMAV1_VERSION
         mkdir -p build_release
         cd build_release
-        CFLAGS="-I$INSTALL_PATH/include/" CXXFLAGS="-I$INSTALL_PATH/include/" LDFLAGS="-L$INSTALL_PATH/lib/" $CMAKE -DCMAKE_INSTALL_PREFIX=$INSTALL_PATH -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_VERSION=1 -DCMAKE_SYSTEM_PROCESSOR=armv8 -DCMAKE_CXX_FLAGS="$CXXFLAGS -fPIC" -DCMAKE_C_FLAGS="$CFLAGS -fPIC" -DCMAKE_C_COMPILER="clang" -DCMAKE_CXX_COMPILER="clang++" $LIBAOM_CONFIG -DAOM_ARCH_AARCH64=1 ..
+        CFLAGS="-I$INSTALL_PATH/include/" CXXFLAGS="-I$INSTALL_PATH/include/" LDFLAGS="-L$INSTALL_PATH/lib/" $CMAKE -DCMAKE_INSTALL_PREFIX=$INSTALL_PATH -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_VERSION=1 -DCMAKE_SYSTEM_PROCESSOR=armv8 -DCMAKE_CXX_FLAGS="$CXXFLAGS -fPIC" -DCMAKE_C_FLAGS="$CFLAGS -fPIC" -DCMAKE_C_COMPILER="clang" -DCMAKE_CXX_COMPILER="clang++" $LIBAOM_CONFIG -DAOM_ARCH_AARCH64=1 -DCONFIG_RUNTIME_CPU_DETECT:BOOL=OFF -DENABLE_NEON_I8MM=OFF ..
         make -j $MAKEJ
         make install
         cd ..

ffmpeg/platform/gpl/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>ffmpeg-platform-gpl</artifactId>
-  <version>6.1-${project.parent.version}</version>
+  <version>6.1.1-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for FFmpeg (GPL enabled)</name>
 
   <properties>

ffmpeg/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>ffmpeg-platform</artifactId>
-  <version>6.1-${project.parent.version}</version>
+  <version>6.1.1-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for FFmpeg</name>
 
   <properties>

ffmpeg/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>ffmpeg</artifactId>
-  <version>6.1-${project.parent.version}</version>
+  <version>6.1.1-${project.parent.version}</version>
   <name>JavaCPP Presets for FFmpeg</name>
 
   <dependencies>