added macosx-arm64 support #10

.github/workflows/build.yml

@@ -6,7 +6,7 @@ on:
       tag:
         description: 'Version Tag'
         required: false
-        default: '0.7.1'
+        default: '0.8.0'
       publishReleases:
         description: 'Publish to Releases'
         required: false

README.md

@@ -1,4 +1,4 @@
-# Deep Vision Processing [![Build Status](https://travis-ci.org/cansik/deep-vision-processing.svg?branch=master)](https://travis-ci.org/cansik/deep-vision-processing) [![Build status](https://ci.appveyor.com/api/projects/status/6026c9qq3my86jgh?svg=true)](https://ci.appveyor.com/project/cansik/deep-vision-processing)
+# Deep Vision Processing [![Build](https://github.com/cansik/deep-vision-processing/actions/workflows/build.yml/badge.svg)](https://github.com/cansik/deep-vision-processing/actions/workflows/build.yml)
 Deep computer-vision algorithms for [Processing](https://processing.org/).
 
 The idea behind this library is to provide a simple way to use (inference) machine learning algorithms for computer vision tasks inside Processing. Mainly portability and easy-to-use are the primary goals of this library. Starting with version `0.6.0` CUDA inferencing support is built into the library (Windows & Linux).
@@ -15,7 +15,7 @@ It is recommended to use the contribution manager in the Processing app to insta
 ![image](https://user-images.githubusercontent.com/5220162/118391536-05b1ea80-b635-11eb-9704-2c5b780008df.png)
 
 ### Manual
-Download the [latest](https://github.com/cansik/deep-vision-processing/releases/tag/v0.7.0-alpha) prebuilt version from the [release](https://github.com/cansik/deep-vision-processing/releases) sections and install it into your Processing library folder.
+Download the [latest](https://github.com/cansik/deep-vision-processing/releases/tag/v0.8.0-alpha) prebuilt version from the [release](https://github.com/cansik/deep-vision-processing/releases) sections and install it into your Processing library folder.
 
 ## Usage
 The base of the library is the `DeepVision` class. It is used to download the pretrained models and create new networks.
@@ -67,7 +67,7 @@ ResultList<ObjectDetectionResult> detections = network.run(myImg);
 Please have a look at the specific networks for further information or at the [examples](examples).
 
 ### CUDA Support
-With version `0.6.0` it is possible to [download the CUDA bundled libraries](https://github.com/cansik/deep-vision-processing/releases/tag/v0.6.2-alpha). This enables to run most of the DNN's on CUDA enabled graphics cards. For most networks this is necessary to run them in real-time. If you have the cuda-bundled version installed and run deep-vision on a Linux or Windows with an NVIDIA graphics card, you are able to enable the CUDA backend:
+With version `0.6.0` it is possible to [download the CUDA bundled libraries](https://github.com/cansik/deep-vision-processing/releases/tag/v0.8.0-alpha). This enables to run most of the DNN's on CUDA enabled graphics cards. For most networks this is necessary to run them in real-time. If you have the cuda-bundled version installed and run deep-vision on a Linux or Windows with an NVIDIA graphics card, you are able to enable the CUDA backend:
 
 ```java
 // Second parameter (enableCUDABackend) enables CUDA

build.gradle

@@ -1,10 +1,10 @@
 plugins {
     id 'java-library'
-    id 'org.bytedeco.gradle-javacpp-platform' version "1.5.6"
+    id 'org.bytedeco.gradle-javacpp-platform' version "1.5.7"
 }
 
 group 'ch.bildspur'
-version '0.7.0'
+version '0.8.0'
 
 sourceCompatibility = 1.8
 
@@ -32,19 +32,19 @@ dependencies {
     testCompile 'com.github.cansik:webcam-capture-processing:8f1ea8d38d'
 
     // opencv (make sure you have updated the local maven repo: mvn -U compile)
-    compile (group: 'org.bytedeco', name: 'javacv', version: "1.5.6"){
+    compile (group: 'org.bytedeco', name: 'javacv', version: "1.5.7"){
         exclude group: 'org.bytedeco', module: 'librealsense2'
         exclude group: 'org.bytedeco', module: 'librealsense2-platform'
     }
 
-    compile group: 'org.bytedeco', name: 'opencv-platform', version: "4.5.3-1.5.6"
-    compile group: 'org.bytedeco', name: 'openblas-platform', version: "0.3.17-1.5.6"
-    compile group: 'org.bytedeco', name: 'tesseract-platform', version: "4.1.1-1.5.6"
+    compile group: 'org.bytedeco', name: 'opencv-platform', version: "4.5.5-1.5.7"
+    compile group: 'org.bytedeco', name: 'openblas-platform', version: "0.3.19-1.5.7"
+    compile group: 'org.bytedeco', name: 'tesseract-platform', version: "5.0.1-1.5.7"
 
     // cuda additions
     if (project.hasProperty("cuda")) {
-        compile group: 'org.bytedeco', name: 'opencv-platform-gpu', version: "4.5.3-1.5.6"
-        compile group: 'org.bytedeco', name: 'cuda-platform-redist', version: "11.4-8.2-1.5.6"
+        compile group: 'org.bytedeco', name: 'opencv-platform-gpu', version: "4.5.5-1.5.7"
+        compile group: 'org.bytedeco', name: 'cuda-platform-redist', version: "11.6-8.3-1.5.7"
     }
 
     // processing

gradle.properties

@@ -1,4 +1,4 @@
-javacppPlatform=linux-x86_64,macosx-x86_64,windows-x86_64,linux-armhf,linux-arm64
+javacppPlatform=linux-x86_64,linux-armhf,linux-arm64,macosx-x86_64,macosx-arm64,windows-x86_64
 org.gradle.parallel=true
 
 outputName=deepvision

library.properties

@@ -4,7 +4,7 @@ authors=[Florian Bruggisser](https://broox.ch)
 url=https://github.com/cansik/deep-vision-processing
 sentence=Deep computer-vision algorithms for Processing
 paragraph=Run deep neural networks on images in Processing.
-version=007000
-prettyVersion=0.7.0
+version=008000
+prettyVersion=0.8.0
 minRevision=0
 maxRevision=0