predict method

Runs inference on a single image.

Takes raw image bytes as input and returns a map containing the inference results. The returned map contains:

• 'boxes': List of detected objects with bounding box coordinates
• 'detections': List of detections in YOLOResult-compatible format
• Task-specific data (keypoints for pose, mask for segmentation, etc.)

The model must be loaded with loadModel before calling this method.

Example:

// Basic detection usage
final results = await yolo.predict(imageBytes);
final boxes = results['boxes'] as List<dynamic>;
for (var box in boxes) {
  print('Class: ${box['class']}, Confidence: ${box['confidence']}');
}

// Pose estimation with YOLOResult
final results = await yolo.predict(imageBytes);
final detections = results['detections'] as List<dynamic>;
for (var detection in detections) {
  final result = YOLOResult.fromMap(detection);
  if (result.keypoints != null) {
    print('Found ${result.keypoints!.length} keypoints');
    for (int i = 0; i < result.keypoints!.length; i++) {
      final kp = result.keypoints![i];
      final conf = result.keypointConfidences![i];
      print('Keypoint $i: (${kp.x}, ${kp.y}) confidence: $conf');
    }
  }
}

imageBytes The raw image data as a Uint8List confidenceThreshold Optional confidence threshold (0.0-1.0). Defaults to 0.25 if not specified. iouThreshold Optional IoU threshold for NMS (0.0-1.0). Defaults to 0.4 if not specified. returns A map containing:

• 'boxes': List of bounding boxes
• 'detections': List of YOLOResult-compatible detection maps
• 'keypoints': (pose only) Raw keypoints data from platform throws ModelNotLoadedException if the model has not been loaded throws InferenceException if there's an error during inference