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YOLO Functions

Overview

yolov8Api.newYolov8 Initialize YOLOv8 Instance

  • Initialize a YOLOv8 instance
  • @return Yolov8Util object
function main() {
  // Initialize YOLO instance
  let yolov8s = yolov8Api.newYolov8();
  // Initialize config options
  let config = yolov8s.getDefaultConfig("yolov8s-640", 640, 0.25, 0.35, "ALL", 0, [
    "aixin",
    "pinglun"
  ])
  // Set CPU thread count; lower values use less CPU. Default is 4; 1 or 2 is recommended
  config["num_thread"] = 1;
  logd("config : " + JSON.stringify(config))
  // Initialize trained model
  let paramPath = "c:/model.ncnn.param";
  let binPath = "c:/model.ncnn.bin";
  let inted = yolov8s.initYoloModel(config, paramPath, binPath);
  if (inted) {
    logd("yolov8s init success");
  } else {
    logd("yolov8s init failed: " + yolov8s.getErrorMsg());
    return;
  }
  let bitmap = image.readBitmap("c:/a.png");
  let result = yolov8s.detectBitmap(bitmap, []);
  // Or use:
  let img = image.readImage("c:/a.png")
  let result2 = yolov8s.detectImage("c:/a.png", [])
  image.recycle(img);
  // With parameters, only filter pinglun class data
  //let result = yolov8s.detectBitmap(bitmap, ["pinglun"]);
  if (result == null || result == "") {
    logd("yolov8s no result: " + yolov8s.getErrorMsg());
  } else {
    logd("yolov8s result: " + result);
  }
  // Release when needed; do not release after every call
  yolov8s.release();
}


main();

yolov8Api.newYolov8Onxx Initialize YOLOv8 ONNX Instance (Multi-Instance Supported)

  • Initialize a YOLOv8 ONNX instance
  • @return Yolov8Util instance object
function main() {
  // Initialize YOLO instance
  let yolov8s = yolov8Api.newYolov8Onxx();
  // Initialize config options
  let config = yolov8s.getOnnxConfig([
    "aixin",
    "pinglun"
  ], 640, 640, 0.35, 0.55, 2)
  logd("config : " + JSON.stringify(config))
  // Initialize trained model
  let paramPath = "c:/best.onnx";
  let inted = yolov8s.initYoloModel(config, paramPath, "");
  if (inted) {
    logd("yolov8s init success");
  } else {
    logd("yolov8s init failed: " + yolov8s.getErrorMsg());
    return;
  }
  // Capture screen as img
  let img = image.captureFullScreen()
  // Read local image
  // let bitmap = image.readBitmap("/sdcard/a.png");
  let result = yolov8s.detectImage(img, []);
  // With parameters, only filter pinglun class data
  //let result = yolov8s.detectBitmap(bitmap, ["pinglun"]);
  if (result == null || result == "") {
    logd("yolov8s no result: " + yolov8s.getErrorMsg());
  } else {
    logd("yolov8s result: " + result);
  }
  if (img != null) {
    // Recycle image
    img.recycle();
  }
  // Release when needed; do not release after every call
  yolov8s.release();
}


main();

Yolov8Util.getOnnxConfig ONNX Config Options

  • ONNX configuration options
  • @param obj_names JSON array of class names; if omitted, ONNX reads them from the model, e.g. ["star","common","face"]
  • @param input_width Training image width; 0 lets ONNX extract it automatically
  • @param input_height Training image height; 0 lets ONNX extract it automatically
  • @param confThreshold Minimum confidence threshold for detections during ONNX inference
  • @param iouThreshold IoU threshold used in NMS during ONNX inference
  • @param numThread Thread count; usually half the CPU count. If unknown, omit. Use 1 or 2 to reduce CPU usage
  • @return {JSON}

Yolov8Util.getDefaultConfig Get YOLOv8 Default Config

  • Get the default YOLOv8 configuration
  • @param model_name Model name; use yolov8s-640 by default
  • @param input_size YOLOv8 training imgsz parameter; use 640 by default
  • @param box_thr Detection box coefficient; use 0.25 by default
  • @param iou_thr Output coefficient; use 0.35 by default
  • @param bind_cpu Whether to bind CPU; options are ALL, BIG, LITTLE; use ALL by default
  • @param use_vulkan_compute Enable hardware acceleration: 1 yes, 0 no; use 0 by default
  • @param obj_names JSON array of class names from training, e.g. ["star","common","face"]
  • @return JSON data
   See the `Initialize YOLOv8 instance` example

Yolov8Util.initYoloModel Initialize YOLOv8 Model

  • To generate param and bin files, see the YOLO usage chapter: convert YOLO pt to ncnn param/bin files
  • For ONNX models, set binPath to null; paramPath is the ONNX file path
  • @param map Parameter map; for ncnn use getDefaultConfig, for onnx use getOnnxConfig
  • @param paramPath Path to the param file
  • @param binPath Path to the bin file
  • @return boolean true on success, false on failure
   See the `Initialize YOLOv8 instance` example

Yolov8Util.detectBitmap Detect Image

  • Detect objects in an image
  • Example return data:
  • [{"name":"heart","confidence":0.92,"left":957,"top":986,"right":1050,"bottom":1078}]
  • name: class name; confidence: confidence score; left, top, right, bottom: bounding box coordinates
  • @param bitmap Java BufferedImage object
  • @param obj_names JSON array; omit to skip filtering, or provide class names to keep
  • @return string
   See the `Initialize YOLOv8 instance` example

Yolov8Util.detectImage Detect AutoImage

  • Detect objects in an image
  • Example return data:
  • [{"name":"heart","confidence":0.92,"left":957,"top":986,"right":1050,"bottom":1078}]
  • name: class name; confidence: confidence score; left, top, right, bottom: bounding box coordinates
  • @param image AutoImage object
  • @param obj_names JSON array; omit to skip filtering, or provide class names to keep
  • @return string
   See the `Initialize YOLOv8 instance` example

Yolov8Util.release Release Resources

  • Release YOLOv8 resources
  • @return boolean
   See the `Initialize YOLOv8 instance` example
   Call release when the script ends; no need to release after every use

Yolov8Util.getErrorMsg Get YOLOv8 Error Message

  • Get the YOLOv8 error message
  • @return string
   See the `Initialize YOLOv8 instance` example