* Upgrade presets for FFmpeg 7.0.2, TensorFlow Lite 2.17.0, Triton I…

…nference Server 2.48.0

.github/workflows/tritonserver.yml

@@ -19,6 +19,6 @@ env:
 jobs:
   linux-x86_64:
     runs-on: ubuntu-20.04
-    container: nvcr.io/nvidia/tritonserver:24.03-py3
+    container: nvcr.io/nvidia/tritonserver:24.07-py3
     steps:
       - uses: bytedeco/javacpp-presets/.github/actions/deploy-ubuntu@actions

CHANGELOG.md

@@ -7,7 +7,7 @@
  * Build FFmpeg with zimg to enable zscale filter ([pull #1481](https://github.com/bytedeco/javacpp-presets/pull/1481))
  * Enable PulseAudio support for FFmpeg on Linux ([pull #1472](https://github.com/bytedeco/javacpp-presets/pull/1472))
  * Virtualize `btCollisionWorld`, `btOverlapFilterCallback`, `btOverlapCallback` from Bullet Physics SDK ([pull #1475](https://github.com/bytedeco/javacpp-presets/pull/1475))
- * Upgrade presets for OpenCV 4.10.0, FFmpeg 7.0, Spinnaker 4.0.0.116 ([pull #1524](https://github.com/bytedeco/javacpp-presets/pull/1524)), DNNL 3.5.3, OpenBLAS 0.3.28, CMINPACK 1.3.9, GSL 2.8, CPython 3.12.5, NumPy 2.0.1, SciPy 1.14.0, LLVM 18.1.8, LibRaw 0.21.2 ([pull #1520](https://github.com/bytedeco/javacpp-presets/pull/1520)), Tesseract 5.4.1, libffi 3.4.6, OpenCL 3.0.16, PyTorch 2.3.0 ([pull #1466](https://github.com/bytedeco/javacpp-presets/pull/1466)), SentencePiece 0.2.0, TensorFlow Lite 2.16.1, TensorRT 10.0.1.6, Triton Inference Server 2.44.0, ONNX 1.16.2, ONNX Runtime 1.18.1, TVM 0.17.0, and their dependencies
+ * Upgrade presets for OpenCV 4.10.0, FFmpeg 7.0.2, Spinnaker 4.0.0.116 ([pull #1524](https://github.com/bytedeco/javacpp-presets/pull/1524)), DNNL 3.5.3, OpenBLAS 0.3.28, CMINPACK 1.3.9, GSL 2.8, CPython 3.12.5, NumPy 2.0.1, SciPy 1.14.0, LLVM 18.1.8, LibRaw 0.21.2 ([pull #1520](https://github.com/bytedeco/javacpp-presets/pull/1520)), Tesseract 5.4.1, libffi 3.4.6, OpenCL 3.0.16, PyTorch 2.3.0 ([pull #1466](https://github.com/bytedeco/javacpp-presets/pull/1466)), SentencePiece 0.2.0, TensorFlow Lite 2.17.0, TensorRT 10.0.1.6, Triton Inference Server 2.48.0, ONNX 1.16.2, ONNX Runtime 1.18.1, TVM 0.17.0, and their dependencies
 
 ### January 29, 2024 version 1.5.10
  * Introduce `macosx-arm64` builds for PyTorch ([pull #1463](https://github.com/bytedeco/javacpp-presets/pull/1463))

README.md

@@ -226,9 +226,9 @@ Each child module in turn relies by default on the included [`cppbuild.sh` scrip
  * PyTorch 2.3.x  https://github.com/pytorch/pytorch
  * SentencePiece 0.2.0  https://github.com/google/sentencepiece
  * TensorFlow 1.15.x  https://github.com/tensorflow/tensorflow
- * TensorFlow Lite 2.16.x  https://github.com/tensorflow/tensorflow
+ * TensorFlow Lite 2.17.x  https://github.com/tensorflow/tensorflow
  * TensorRT 10.0.x  https://developer.nvidia.com/tensorrt
- * Triton Inference Server 2.44.x  https://developer.nvidia.com/nvidia-triton-inference-server
+ * Triton Inference Server 2.48.x  https://developer.nvidia.com/nvidia-triton-inference-server
  * The Arcade Learning Environment 0.8.x  https://github.com/mgbellemare/Arcade-Learning-Environment
  * DepthAI 2.24.x  https://github.com/luxonis/depthai-core
  * ONNX 1.16.x  https://github.com/onnx/onnx

ffmpeg/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * FFmpeg 7.0  http://ffmpeg.org/
+ * FFmpeg 7.0.2  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>7.0-1.5.11-SNAPSHOT</version>
+            <version>7.0.2-1.5.11-SNAPSHOT</version>
         </dependency>
 
         <!-- Optional GPL builds with (almost) everything enabled -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>ffmpeg-platform-gpl</artifactId>
-            <version>7.0-1.5.11-SNAPSHOT</version>
+            <version>7.0.2-1.5.11-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

ffmpeg/cppbuild.sh

@@ -33,22 +33,22 @@ 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-3.3.0
+OPENSSL=openssl-3.3.1
 OPENH264_VERSION=2.4.1
 X264=x264-stable
 X265=3.4
-VPX_VERSION=1.14.0
-ALSA_VERSION=1.2.11
+VPX_VERSION=1.14.1
+ALSA_VERSION=1.2.12
 FREETYPE_VERSION=2.13.2
 MFX_VERSION=1.35.1
 NVCODEC_VERSION=12.2.72.0
 XML2=libxml2-2.9.12
 LIBSRT_VERSION=1.5.3
 WEBP_VERSION=1.4.0
-AOMAV1_VERSION=3.8.2
-SVTAV1_VERSION=2.0.0
+AOMAV1_VERSION=3.9.1
+SVTAV1_VERSION=2.1.2
 ZIMG_VERSION=3.0.5
-FFMPEG_VERSION=7.0
+FFMPEG_VERSION=7.0.2
 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 $LAME.tar.gz
@@ -123,7 +123,7 @@ patch -Np1 -d ffmpeg-$FFMPEG_VERSION < ../../ffmpeg-vulkan.patch
 sedinplace 's/bool bEnableavx512/bool bEnableavx512 = false/g' x265-*/source/common/param.h
 sedinplace 's/detect512()/false/g' x265-*/source/common/quant.cpp
 sedinplace 's/CMAKE_C_COMPILER_ID MATCHES "Clang"/FALSE/g' SVT-AV1-*/CMakeLists.txt
-sedinplace 's/defined(__linux__)/defined(__linux__) \&\& !defined(__ANDROID__)/g' SVT-AV1-*/Source/Lib/Common/Codec/EbThreads.h
+# sedinplace 's/defined(__linux__)/defined(__linux__) \&\& !defined(__ANDROID__)/g' SVT-AV1-*/Source/Lib/Common/Codec/EbThreads.h
 sedinplace '/ANativeWindow_release/d' ffmpeg-*/libavutil/hwcontext_mediacodec.c
 sedinplace 's/#define MAX_SLICES 32/#define MAX_SLICES 256/g' ffmpeg-*/libavcodec/h264dec.h
 

ffmpeg/platform/gpl/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>ffmpeg-platform-gpl</artifactId>
-  <version>7.0-${project.parent.version}</version>
+  <version>7.0.2-${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>7.0-${project.parent.version}</version>
+  <version>7.0.2-${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>7.0-${project.parent.version}</version>
+  <version>7.0.2-${project.parent.version}</version>
   <name>JavaCPP Presets for FFmpeg</name>
 
   <dependencies>

ffmpeg/samples/pom.xml

@@ -12,14 +12,14 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>ffmpeg-platform</artifactId>
-            <version>7.0-1.5.11-SNAPSHOT</version>
+            <version>7.0.2-1.5.11-SNAPSHOT</version>
         </dependency>
 
         <!-- Optional GPL builds with (almost) everything enabled -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>ffmpeg-platform-gpl</artifactId>
-            <version>7.0-1.5.11-SNAPSHOT</version>
+            <version>7.0.2-1.5.11-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

ffmpeg/src/gen/java/org/bytedeco/ffmpeg/global/avutil.java

@@ -7657,7 +7657,7 @@ allocated with av_malloc() or another memory allocation function. */
 /* Automatically generated by version.sh, do not manually edit! */
 // #ifndef AVUTIL_FFVERSION_H
 // #define AVUTIL_FFVERSION_H
-public static final String FFMPEG_VERSION = "7.0";
+public static final String FFMPEG_VERSION = "7.0.2";
 // #endif /* AVUTIL_FFVERSION_H */
 
 

platform/pom.xml

@@ -92,7 +92,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>ffmpeg-platform</artifactId>
-      <version>7.0-${project.version}</version>
+      <version>7.0.2-${project.version}</version>
     </dependency>
 <!--    <dependency>-->
 <!--      <groupId>org.bytedeco</groupId>-->
@@ -307,7 +307,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>tensorflow-lite-platform</artifactId>
-      <version>2.16.1-${project.version}</version>
+      <version>2.17.0-${project.version}</version>
     </dependency>
     <dependency>
       <groupId>org.bytedeco</groupId>
@@ -317,7 +317,7 @@
     <dependency>
       <groupId>org.bytedeco</groupId>
       <artifactId>tritonserver-platform</artifactId>
-      <version>2.44-${project.version}</version>
+      <version>2.48.0-${project.version}</version>
     </dependency>
 <!--    <dependency>-->
 <!--      <groupId>org.bytedeco</groupId>-->

tensorflow-lite/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * TensorFlow Lite 2.16.1  https://www.tensorflow.org/lite
+ * TensorFlow Lite 2.17.0  https://www.tensorflow.org/lite
 
 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 TensorFlow ported to Java from this C++ source file:
 
- * https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/lite/examples/minimal/minimal.cc
+ * https://github.com/tensorflow/tensorflow/blob/v2.17.0/tensorflow/lite/examples/minimal/minimal.cc
 
 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 `Minimal.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>tensorflow-lite-platform</artifactId>
-            <version>2.16.1-1.5.11-SNAPSHOT</version>
+            <version>2.17.0-1.5.11-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

tensorflow-lite/cppbuild.sh

@@ -12,7 +12,7 @@ if [[ "$EXTENSION" == *gpu ]]; then
     export CMAKE_FLAGS="-DTFLITE_ENABLE_GPU=ON"
 fi
 
-TENSORFLOW_VERSION=2.16.1
+TENSORFLOW_VERSION=2.17.0
 download https://github.com/tensorflow/tensorflow/archive/v$TENSORFLOW_VERSION.tar.gz tensorflow-$TENSORFLOW_VERSION.tar.gz
 
 mkdir -p "$PLATFORM$EXTENSION"

tensorflow-lite/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>tensorflow-lite-platform</artifactId>
-  <version>2.16.1-${project.parent.version}</version>
+  <version>2.17.0-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for TensorFlow Lite</name>
 
   <properties>

tensorflow-lite/pom.xml

@@ -16,7 +16,7 @@
 
   <properties>
     <javacpp.packageName>tensorflowlite</javacpp.packageName>
-    <tensorflow.version>2.16.1</tensorflow.version>
+    <tensorflow.version>2.17.0</tensorflow.version>
     <tensorflow.path>${basedir}/cppbuild/${javacpp.platform}${javacpp.platform.extension}/tensorflow-${tensorflow.version}/</tensorflow.path>
   </properties>
 

tensorflow-lite/samples/pom.xml

@@ -12,7 +12,7 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>tensorflow-lite-platform</artifactId>
-            <version>2.16.1-1.5.11-SNAPSHOT</version>
+            <version>2.17.0-1.5.11-SNAPSHOT</version>
         </dependency>
     </dependencies>
     <build>

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Find_builtin_op_Pointer_int_int.java

@@ -14,8 +14,8 @@
  * 
  *  This combines the effects of TfLiteInterpreterOptionsSetOpResolverExternal
  *  and TfLiteInterpreterOptionsSetOpResolver.  The callbacks that return
- *  TfLiteRegistrationExternal will be called first, but if they return a
- *  TfLiteRegistrationExternal object that has no methods set, then
+ *  TfLiteOperator will be called first, but if they return a
+ *  TfLiteOperator object that has no methods set, then
  *  the callbacks that return a TfLiteRegistration will be called to get
  *  the methods.
  * 

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Find_builtin_op_external_Pointer_int_int.java

@@ -14,7 +14,7 @@
  *  The {@code TfLiteInterpreterOptionsSetOpResolverExternal} function provides an
  *  alternative method for registering builtin ops and/or custom ops, by
  *  providing operator resolver callbacks.  Unlike using
- *  {@code TfLiteInterpreterOptionsAddRegistrationExternal},
+ *  {@code TfLiteInterpreterOptionsAddOperator},
  *  {@code TfLiteInterpreterOptionsAddBuiltinOp} and/or
  *  {@code TfLiteInterpreterOptionsAddAddCustomOp}, these let you register all the
  *  operators in a single call.
@@ -26,7 +26,7 @@
  *  If {@code op_resolver_user_data} is non-null, its lifetime must be at least as
  *  long as the lifetime of the {@code TfLiteInterpreterOptions}.
  * 
- *  The TfLiteRegistrationExternal objects whose addresses are returned by
+ *  The TfLiteOperator objects whose addresses are returned by
  *  {@code find_builtin_op} and {@code find_custom_op} must outlive both the
  *  InterpreterOptions object and any Interpreter object created from it.
  * 
@@ -38,6 +38,6 @@ public class Find_builtin_op_external_Pointer_int_int extends FunctionPointer {
     public    Find_builtin_op_external_Pointer_int_int(Pointer p) { super(p); }
     protected Find_builtin_op_external_Pointer_int_int() { allocate(); }
     private native void allocate();
-    public native @Const TfLiteRegistrationExternal call(Pointer user_data,
-                                                         int op, int version);
+    public native @Const TfLiteOperator call(Pointer user_data, int op,
+                                             int version);
 }

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Find_custom_op_external_Pointer_String_int.java

@@ -15,7 +15,6 @@ public class Find_custom_op_external_Pointer_String_int extends FunctionPointer
     public    Find_custom_op_external_Pointer_String_int(Pointer p) { super(p); }
     protected Find_custom_op_external_Pointer_String_int() { allocate(); }
     private native void allocate();
-    public native @Const TfLiteRegistrationExternal call(Pointer user_data,
-                                                        @Cast("const char*") BytePointer custom_op,
-                                                        int version);
+    public native @Const TfLiteOperator call(Pointer user_data,
+                                            @Cast("const char*") BytePointer custom_op, int version);
 }

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/FlatBufferModel.java

@@ -78,6 +78,32 @@ public class FlatBufferModel extends Pointer {
   public static native @UniquePtr FlatBufferModel VerifyAndBuildFromFile(
         String filename);
 
+  /** Builds a model based on a file descriptor.
+   *  Caller retains ownership of {@code error_reporter} and must ensure its lifetime
+   *  is longer than the FlatBufferModel instance. Caller retains ownership of
+   *  {@code fd} and must ensure it is closed after BuildFromFile returns.
+   *  Returns a nullptr in case of failure. */
+  public static native @UniquePtr FlatBufferModel BuildFromFileDescriptor(
+        int fd,
+        ErrorReporter error_reporter/*=tflite::DefaultErrorReporter()*/);
+  public static native @UniquePtr FlatBufferModel BuildFromFileDescriptor(
+        int fd);
+
+  /** Verifies whether the content of the file descriptor is legit, then builds
+   *  a model based on the file.
+   *  The extra_verifier argument is an additional optional verifier for the
+   *  file contents. By default, we always check with tflite::VerifyModelBuffer.
+   *  If extra_verifier is supplied, the file contents is also checked against
+   *  the extra_verifier after the check against tflite::VerifyModelBuilder.
+   *  Caller retains ownership of {@code error_reporter} and must ensure its lifetime
+   *  is longer than the FlatBufferModel instance.
+   *  Returns a nullptr in case of failure. */
+  public static native @UniquePtr FlatBufferModel VerifyAndBuildFromFileDescriptor(
+        int fd, TfLiteVerifier extra_verifier/*=nullptr*/,
+        ErrorReporter error_reporter/*=tflite::DefaultErrorReporter()*/);
+  public static native @UniquePtr FlatBufferModel VerifyAndBuildFromFileDescriptor(
+        int fd);
+
   /** Builds a model based on a pre-loaded flatbuffer.
    *  Caller retains ownership of the buffer and should keep it alive until
    *  the returned object is destroyed. Caller also retains ownership of

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Free_Pointer_TfLiteOpaqueContext_Pointer.java

@@ -0,0 +1,29 @@
+// Targeted by JavaCPP version 1.5.11-SNAPSHOT: DO NOT EDIT THIS FILE
+
+package org.bytedeco.tensorflowlite;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.bytedeco.tensorflowlite.global.tensorflowlite.*;
+
+
+/** Sets the deallocation callback for the registration, similarly to
+ *  {@code TfLiteOperatorSetFree}. The function returns an error upon failure.
+ * 
+ *  This callback is called to deallocate the data returned by the init
+ *  callback. The value passed in the {@code data} parameter is the value that was
+ *  returned by the {@code init} callback. The value passed in the {@code user_data}
+ *  parameter is the value that was passed to {@code TfLiteOperatorCreateWithData}.
+ *  Please refer {@code free} of {@code TfLiteRegistration} for the detail.
+ *  */
+@Properties(inherit = org.bytedeco.tensorflowlite.presets.tensorflowlite.class)
+public class Free_Pointer_TfLiteOpaqueContext_Pointer extends FunctionPointer {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public    Free_Pointer_TfLiteOpaqueContext_Pointer(Pointer p) { super(p); }
+    protected Free_Pointer_TfLiteOpaqueContext_Pointer() { allocate(); }
+    private native void allocate();
+    public native void call(Pointer user_data, TfLiteOpaqueContext context, Pointer data);
+}

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Free_TfLiteOpaqueContext_Pointer.java

@@ -9,14 +9,14 @@
 import static org.bytedeco.tensorflowlite.global.tensorflowlite.*;
 
 
-// Sets the deallocation callback for the registration.
-//
-// This callback is called to deallocate the data returned by the init callback.
-// The value passed in the `data` parameter is the value that was returned by
-// the `init` callback.
-// Please refer `free` of `TfLiteRegistration` for the detail.
-//
-// \warning This is an experimental API and subject to change.
+/** Sets the deallocation callback for the registration.
+ * 
+ *  This callback is called to deallocate the data returned by the init
+ *  callback. The value passed in the {@code data} parameter is the value that was
+ *  returned by the {@code init} callback. Please refer {@code free} of {@code TfLiteRegistration}
+ *  for the detail.
+ * 
+ *  Deprecated: Use {@code TfLiteOperatorSetFreeWithData} */
 @Properties(inherit = org.bytedeco.tensorflowlite.presets.tensorflowlite.class)
 public class Free_TfLiteOpaqueContext_Pointer extends FunctionPointer {
     static { Loader.load(); }

tensorflow-lite/src/gen/java/org/bytedeco/tensorflowlite/Init_Pointer_TfLiteOpaqueContext_BytePointer_long.java

@@ -0,0 +1,29 @@
+// Targeted by JavaCPP version 1.5.11-SNAPSHOT: DO NOT EDIT THIS FILE
+
+package org.bytedeco.tensorflowlite;
+
+import java.nio.*;
+import org.bytedeco.javacpp.*;
+import org.bytedeco.javacpp.annotation.*;
+
+import static org.bytedeco.tensorflowlite.global.tensorflowlite.*;
+
+
+/** Sets the initialization callback for the registration. The function returns
+ *  an error upon failure.
+ * 
+ *  The callback is called to initialize the op from serialized data. The value
+ *  passed in the {@code user_data} parameter is the value that was passed to
+ *  {@code TfLiteOperatorCreateWithData}.  Please refer {@code init} of {@code TfLiteRegistration}
+ *  for the detail.
+ *  */
+@Properties(inherit = org.bytedeco.tensorflowlite.presets.tensorflowlite.class)
+public class Init_Pointer_TfLiteOpaqueContext_BytePointer_long extends FunctionPointer {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public    Init_Pointer_TfLiteOpaqueContext_BytePointer_long(Pointer p) { super(p); }
+    protected Init_Pointer_TfLiteOpaqueContext_BytePointer_long() { allocate(); }
+    private native void allocate();
+    public native Pointer call(Pointer user_data, TfLiteOpaqueContext context,
+                  @Cast("const char*") BytePointer buffer, @Cast("size_t") long length);
+}