YoloV9 Code for Object Detection + Segmentation and Tracking

Yolo V9 Tracking + Object Tracing + Segmentation

First, See The Video below then see the code to do Object Detection + Segmentation and Tracking in that

YoloV9 Code for Object Detection + Segmentation and Tracking

Now, See The Python Code for Video above 

import numpy as np
import supervision as sv
from ultralytics import YOLO

model = YOLO("yolov9e-seg.pt")
tracker = sv.ByteTrack()
box_annotator = sv.MaskAnnotator()
label_annotator = sv.LabelAnnotator(text_color=sv.Color.BLACK)
trace_annotator = sv.TraceAnnotator()

def callback(frame: np.ndarray, _: int) -> np.ndarray:
    results = model(frame)[0]
    detections = sv.Detections.from_ultralytics(results)
    detections = tracker.update_with_detections(detections)

    labels = [
        f"#{tracker_id} {results.names[class_id]}"
        for class_id, tracker_id
        in zip(detections.class_id, detections.tracker_id)
    ]

    annotated_frame = box_annotator.annotate(
        frame.copy(), detections=detections)
    annotated_frame = label_annotator.annotate(
        annotated_frame, detections=detections, labels=labels)
    return trace_annotator.annotate(
        annotated_frame, detections=detections)

sv.process_video(
    source_path="1.mp4",
    target_path="1-result_2.mp4",
    callback=callback
)