* Upgrade presets for OpenCV 4.8.0, NumPy 1.25.1, SciPy 1.11.1, Tens…

…orFlow Lite 2.13.0

CHANGELOG.md

@@ -1,6 +1,6 @@
 
  * Map new higher-level C++ API of Triton Inference Server ([pull #1361](https://github.com/bytedeco/javacpp-presets/pull/1361))
- * Upgrade presets for DNNL 3.1.1, CPython 3.11.4, NumPy 1.25.0, SciPy 1.11.0, LLVM 16.0.6, Triton Inference Server 2.34.0, ONNX Runtime 1.15.1, and their dependencies
+ * Upgrade presets for OpenCV 4.8.0, DNNL 3.1.1, CPython 3.11.4, NumPy 1.25.1, SciPy 1.11.1, LLVM 16.0.6, TensorFlow Lite 2.13.0, Triton Inference Server 2.34.0, ONNX Runtime 1.15.1, 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

@@ -178,7 +178,7 @@ The JavaCPP Presets depend on Maven, a powerful build system for Java, so before
 
 Each child module in turn relies by default on the included [`cppbuild.sh` scripts](#the-cppbuildsh-scripts), explained below, to install its corresponding native libraries in the `cppbuild` subdirectory. To use native libraries already installed somewhere else on the system, other installation directories than `cppbuild` can also be specified either in the `pom.xml` files or in the `.java` configuration files. The following versions are supported:
 
- * OpenCV 4.7.x  https://opencv.org/releases/
+ * OpenCV 4.8.x  https://opencv.org/releases/
  * FFmpeg 6.0.x  http://ffmpeg.org/download.html
  * FlyCapture 2.13.x  https://www.flir.com/products/flycapture-sdk
  * Spinnaker 3.0.x https://www.flir.com/products/spinnaker-sdk
@@ -204,8 +204,8 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * FFTW 3.3.10  http://www.fftw.org/download.html
  * GSL 2.7  http://www.gnu.org/software/gsl/#downloading
  * CPython 3.11.x  https://www.python.org/downloads/
- * NumPy 1.24.x  https://github.com/numpy/numpy
- * SciPy 1.10.x  https://github.com/scipy/scipy
+ * NumPy 1.25.x  https://github.com/numpy/numpy
+ * SciPy 1.11.x  https://github.com/scipy/scipy
  * Gym 0.26.x  https://github.com/openai/gym
  * LLVM 16.0.x  http://llvm.org/releases/download.html
  * libffi 3.4.x  https://github.com/libffi/libffi
@@ -223,7 +223,7 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * MXNet 1.9.x  https://github.com/apache/incubator-mxnet
  * PyTorch 2.0.x  https://github.com/pytorch/pytorch
  * TensorFlow 1.15.x  https://github.com/tensorflow/tensorflow
- * TensorFlow Lite 2.12.x  https://github.com/tensorflow/tensorflow
+ * TensorFlow Lite 2.13.x  https://github.com/tensorflow/tensorflow
  * TensorRT 8.6.x  https://developer.nvidia.com/tensorrt
  * Triton Inference Server 2.34.x  https://developer.nvidia.com/nvidia-triton-inference-server
  * The Arcade Learning Environment 0.8.x  https://github.com/mgbellemare/Arcade-Learning-Environment

numpy/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * NumPy 1.25.0  http://www.numpy.org/
+ * NumPy 1.25.1  http://www.numpy.org/
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
 
@@ -40,22 +40,22 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
     <modelVersion>4.0.0</modelVersion>
     <groupId>org.bytedeco.numpy</groupId>
     <artifactId>matmul</artifactId>
-    <version>1.5.9</version>
+    <version>1.5.10-SNAPSHOT</version>
     <properties>
         <exec.mainClass>MatMul</exec.mainClass>
     </properties>
     <dependencies>
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>numpy-platform</artifactId>
-            <version>1.25.0-1.5.9</version>
+            <version>1.25.1-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled full version of MKL -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>mkl-platform-redist</artifactId>
-            <version>2023.1-1.5.9</version>
+            <version>2023.1-1.5.10-SNAPSHOT</version>
         </dependency>
 
     </dependencies>

numpy/cppbuild.sh

@@ -7,7 +7,7 @@ if [[ -z "$PLATFORM" ]]; then
     exit
 fi
 
-NUMPY_VERSION=1.25.0
+NUMPY_VERSION=1.25.1
 download https://github.com/numpy/numpy/releases/download/v$NUMPY_VERSION/numpy-$NUMPY_VERSION.tar.gz numpy-$NUMPY_VERSION.tar.gz
 
 mkdir -p $PLATFORM

numpy/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>numpy-platform</artifactId>
-  <version>1.25.0-${project.parent.version}</version>
+  <version>1.25.1-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for NumPy</name>
 
   <properties>

numpy/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>numpy</artifactId>
-  <version>1.25.0-${project.parent.version}</version>
+  <version>1.25.1-${project.parent.version}</version>
   <name>JavaCPP Presets for NumPy</name>
 
   <dependencies>

numpy/samples/pom.xml

@@ -12,7 +12,7 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>numpy-platform</artifactId>
-            <version>1.25.0-1.5.10-SNAPSHOT</version>
+            <version>1.25.1-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled full version of MKL -->

opencv/README.md

@@ -77,7 +77,7 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>numpy-platform</artifactId>
-            <version>1.25.0-1.5.10-SNAPSHOT</version>
+            <version>1.25.1-1.5.10-SNAPSHOT</version>
         </dependency>
 
     </dependencies>

opencv/cppbuild.sh

@@ -7,7 +7,7 @@ if [[ -z "$PLATFORM" ]]; then
     exit
 fi
 
-OPENCV_VERSION=4.7.0
+OPENCV_VERSION=4.8.0
 download https://github.com/opencv/opencv/archive/$OPENCV_VERSION.tar.gz opencv-$OPENCV_VERSION.tar.gz
 download https://github.com/opencv/opencv_contrib/archive/$OPENCV_VERSION.tar.gz opencv_contrib-$OPENCV_VERSION.tar.gz