I’m using Axelera’s Voyager SDK to run a YOLOv8s object-detection pipeline on video files, and I need to capture every detection into a JSON array for downstream processing. For each detected object, I want to record:
-
frame_index
: the zero-based frame number -
timestamp
: the frame’s PTS in seconds -
bbox
:[x1, y1, x2, y2]
coordinates -
class_id
: numeric COCO class index -
class_name
: readable label (e.g. “person”) -
score
: detection confidence
What’s the cleanest way to hook into the Voyager inference loop, pull out the ObjectDetectionMeta
(task name “detections”), convert its boxes
, scores
, class_ids
, and labels
into native Python types, attach the FrameResult.src_timestamp
, and dump the results into a single JSON file? Example snippets or pointers to the relevant SDK APIs would be greatly appreciated.