JNA support for darknet

jna/.gitignore

@@ -0,0 +1,4 @@
+.idea
+.directory
+*.iml
+target

jna/pom.xml

@@ -0,0 +1,30 @@
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
+  <modelVersion>4.0.0</modelVersion>
+  <groupId>darknet</groupId>
+  <artifactId>darknet</artifactId>
+  <packaging>jar</packaging>
+  <version>1.0-SNAPSHOT</version>
+  <name>darknet</name>
+  <url>http://maven.apache.org</url>
+  <dependencies>
+    <dependency>
+      <groupId>junit</groupId>
+      <artifactId>junit</artifactId>
+      <version>4.12</version>
+      <scope>test</scope>
+    </dependency>
+    <!-- https://mvnrepository.com/artifact/net.java.dev.jna/jna -->
+    <dependency>
+      <groupId>net.java.dev.jna</groupId>
+      <artifactId>jna</artifactId>
+      <version>5.5.0</version>
+    </dependency>
+    <!-- https://mvnrepository.com/artifact/net.java.dev.jna/jna-platform -->
+    <dependency>
+      <groupId>net.java.dev.jna</groupId>
+      <artifactId>jna-platform</artifactId>
+      <version>5.5.0</version>
+    </dependency>
+  </dependencies>
+</project>

jna/src/main/java/dark/App.java

@@ -0,0 +1,104 @@
+package dark;
+
+import com.sun.jna.Native;
+import com.sun.jna.Pointer;
+import com.sun.jna.ptr.IntByReference;
+import org.bytedeco.opencv.opencv_core.Mat;
+
+
+import java.io.File;
+
+import static java.lang.System.out;
+import static org.bytedeco.opencv.global.opencv_imgcodecs.imread;
+
+
+public class App
+{
+    network net;
+    metadata meta;
+    String[] altNames;
+    //DarknetLib darknet = (DarknetLib) Native.load(new File(".").getAbsolutePath()+"/libdark.so", DarknetLib.class);
+    DarknetLib darknet = (DarknetLib) Native.load(new File(".").getAbsolutePath()+"/dark.dll", DarknetLib.class);
+
+    public static void main( String[] args ) {
+        detection[] detections = new App().PerformDetect("data/dog.jpg",0.25f,"./cfg/yolov3.cfg","./cfg/yolov3.weights", "./cfg/coco.data",false);
+    }
+
+    App(){
+    }
+
+    App(String cfgFile,String weightsFile,String classesFile){
+        PerformDetect(null,0,"./cfg/yolov3.cfg","./cfg/yolov3.weights", "./cfg/coco.data",true);
+    }
+
+    public detection[]  Detect(String filename, float thresh, float hier_thresh, float nms) {
+        image im = darknet.load_image_color(filename, 0, 0);
+        Mat mat = imread(filename);
+
+        detection[] ret = DetectImage(im, thresh, hier_thresh, nms);
+
+        Util.showImage(mat);
+        darknet.free_image(im);
+        return ret;
+    }
+
+    public detection[] DetectImage(image im, float thresh, float hier_thresh, float nms) {
+        IntByReference pnum = new IntByReference(0);
+        float pre = darknet.network_predict_image(net, im);
+        int letter_box = 0;
+        int map = 0;
+        IntByReference pmap = new IntByReference(map);
+        Pointer p =  darknet.get_network_boxes(net, im.w, im.h, thresh, hier_thresh, pmap, 0, pnum, letter_box);
+        int num = pnum.getValue();
+        detection det = new detection(p);
+        if (nms>0) {
+            darknet.do_nms_sort(det, num, meta.classes, nms);
+        }
+        detection[] detections = (detection[])det.toArray(num);
+        for(int j=0;j<num;j++) {
+            detection detect = detections[j];
+            float[] probabilites = detect.prob.getFloatArray(0,meta.classes);
+            for (int i = 0; i < meta.classes; i++) {
+                if (probabilites[i] > 0) {
+                    String nameTag = altNames[i];
+                    //out.println("name:"+nameTag+"("+probabilites[i]+")");
+                }
+            }
+        }
+        darknet.free_detections(p, num);
+        return detections;
+    }
+
+    public  detection[] PerformDetect(String imagePath,float thresh,String  configPath,String  weightPath,String  metaPath,boolean initOnly){
+        if(0 < thresh && thresh > 1) {
+            out.println("Threshold should be a float between zero and one (non-inclusive)");
+        }
+        if(! new File(configPath).exists()) {
+            out.println("Invalid config path `"+ new File(configPath).getAbsolutePath()+"`");
+        }
+        if(!new File(weightPath).exists()) {
+            out.println("Invalid weight path `"+new File(weightPath).getAbsolutePath()+"`");
+        }
+        if(!new File(metaPath).exists()) {
+            out.println("Invalid meta path `"+new File(metaPath).getAbsolutePath()+"`");
+        }
+        if(net == null) {
+            net = darknet.load_network_custom(configPath,weightPath, 0, 1);//  #batch size = 1
+        }
+        if(meta == null) {
+            meta = darknet.get_metadata(metaPath);
+        }
+        if(altNames==null) {
+            altNames = meta.names.getStringArray(0, meta.classes);
+        }
+        if(initOnly) {
+            out.println("Initialized detector");
+            return null;
+        }
+        float hier_thresh=.5f;
+        float nms=.45f;
+        detection[] detections = Detect(imagePath, thresh,hier_thresh,nms);
+        int success = darknet.dispose();
+        return detections;
+    }
+}

jna/src/main/java/dark/DarknetApp.java

@@ -0,0 +1,4 @@
+package dark;
+
+public class DarknetApp {
+}

jna/src/main/java/dark/DarknetLib.java

@@ -0,0 +1,68 @@
+package dark;
+
+import com.sun.jna.Library;
+import com.sun.jna.Pointer;
+import com.sun.jna.ptr.FloatByReference;
+import com.sun.jna.ptr.IntByReference;
+import com.sun.jna.ptr.LongByReference;
+import com.sun.jna.ptr.PointerByReference;
+
+public interface DarknetLib extends Library, YoloV2_Lib {
+    // parser.c
+    network load_network(String configurationFilename, String weightsFilename, int clear, int batch);// # batch size = 1
+    network load_network(String cfg,String weights, int clear);
+    network load_network_custom(String cfg,String weights, int clear, int batch);//works
+    // box.h
+    void do_nms_sort(detection dets, int total, int classes, float thresh);//works
+    void do_nms_obj(detection dets, int total, int classes, float thresh);
+    void diounms_sort(detection dets, int total, int classes, float thresh, int nms_kind, float beta1);
+    // network.h
+    float network_predict(network net, FloatByReference input);
+    float network_predict_ptr(network net, FloatByReference input);
+    Pointer get_network_boxes(network net, int w, int h, float thresh, float hier,IntByReference map, int relative, IntByReference num, int letter);//works
+    void free_detections(Pointer dets, int n);//works
+    void fuse_conv_batchnorm(network net);
+    void calculate_binary_weights(network net);
+    String detection_to_json(detection dets, int nboxes, int classes,String[] names,long frame_id, String filename);
+    Pointer make_network_boxes(network net, float thresh, IntByReference num);
+    void reset_rnn(network net);
+    float network_predict_image(network net, image im);//works
+    float network_predict_image_letterbox(network net, image im);
+    float validate_detector_map(String datacfg,String cfgfile,String weightfile, float thresh_calc_avg_iou, float iou_thresh,int map_points, int letter_box, network existing_net);
+    void train_detector(String datacfg,String cfgfile, String weightfile, IntByReference gpus, int ngpus, int clear, int dont_show, int calc_map, int mjpeg_port, int show_imgs);
+    void test_detector(String datacfg,String cfgfile, String weightfile, String filename, float thresh, float hier_thresh, int dont_show, int ext_output, int save_labels, String outfile, int letter_box);
+    int network_width(network net);
+    int network_height(network net);
+    void optimize_picture(network net, image orig, int max_layer, float scale, float rate, float thresh, int norm);
+    // image.h
+    image resize_image(image im, int w, int h);
+    void copy_image_from_bytes(image im, Pointer pdata);
+    image letterbox_image(image im, int w, int h);
+    void rgbgr_image(image im);
+    image make_image(int w, int h, int c);
+    image load_image_color(String filename, int w, int h);//works
+    void free_image(image m);//works
+    // layer.h
+    void free_layer(layer lay);
+    // data.c
+    void free_data(data d);
+    void load_thread(Pointer ptr);
+    // dark_cuda.h
+    void cuda_pull_array(FloatByReference x_gpu, FloatByReference x, LongByReference n);
+    void cuda_pull_array_async(FloatByReference x_gpu, FloatByReference x, LongByReference n);
+    void cuda_set_device(int n);
+    void cuda_get_context();
+    // utils.h
+    void free_ptrs(PointerByReference ptrs, int n);
+    void top_k(FloatByReference a, int n, int k, IntByReference index);
+    // tree.h
+    tree read_tree(String filename);
+    // option_list.h
+    metadata get_metadata(String file);
+    // http_stream.h
+    void delete_json_sender();
+    void send_json_custom(byte[] send_buf, int port, int timeout);
+    double get_time_point();
+    // gemm.h
+    void init_cpu();
+}