OC-SORT

Overview

OC-SORT remains Simple, Online, and Real-Time like (SORT) but improves robustness during occlusion and non-linear motion. It recognizes limitations from SORT and the linear motion assumption of the Kalman filter, and adds three mechanisms to enhance tracking. These mechanisms help having better Kalman Filter parameters after an occlusion, add a term to the association process to incorporate how consistent is the direction with the new association with respect to the tracks' previous direction and add a second-stage association step between the last observation of unmatched tracks and the unmatched observations after the usual association to attempt to recover tracks that were lost due to object stopping or short-term occlusion.

Comparison

For comparisons with other trackers, plus dataset context and evaluation details, see the tracker comparison page.

Dataset	HOTA	IDF1	MOTA
MOT17	61.9	76.1	76.7
SportsMOT	71.5	71.2	95.2
SoccerNet	78.6	72.7	94.5

Run on video, webcam, or RTSP stream

These examples use OpenCV for decoding and display. Replace <SOURCE_VIDEO_PATH>, <WEBCAM_INDEX>, and <RTSP_STREAM_URL> with your inputs. <WEBCAM_INDEX> is usually 0 for the default camera.

VideoWebcamRTSP

import cv2
import supervision as sv
from rfdetr import RFDETRMedium
from trackers import OCSORTTracker

tracker = OCSORTTracker()
model = RFDETRMedium()

box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()

video_capture = cv2.VideoCapture("<SOURCE_VIDEO_PATH>")
if not video_capture.isOpened():
    raise RuntimeError("Failed to open video source")

while True:
    success, frame_bgr = video_capture.read()
    if not success:
        break

    frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
    detections = model.predict(frame_rgb)
    detections = tracker.update(detections)

    annotated_frame = box_annotator.annotate(frame_bgr, detections)
    annotated_frame = label_annotator.annotate(
        annotated_frame, detections, labels=detections.tracker_id
    )

    cv2.imshow("RF-DETR + OC-SORT", annotated_frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

video_capture.release()
cv2.destroyAllWindows()

import cv2
import supervision as sv
from rfdetr import RFDETRMedium
from trackers import OCSORTTracker

tracker = OCSORTTracker()
model = RFDETRMedium()

box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()

video_capture = cv2.VideoCapture("<WEBCAM_INDEX>")
if not video_capture.isOpened():
    raise RuntimeError("Failed to open webcam")

while True:
    success, frame_bgr = video_capture.read()
    if not success:
        break

    frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
    detections = model.predict(frame_rgb)
    detections = tracker.update(detections)

    annotated_frame = box_annotator.annotate(frame_bgr, detections)
    annotated_frame = label_annotator.annotate(
        annotated_frame, detections, labels=detections.tracker_id
    )

    cv2.imshow("RF-DETR + OC-SORT", annotated_frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

video_capture.release()
cv2.destroyAllWindows()

import cv2
import supervision as sv
from rfdetr import RFDETRMedium
from trackers import OCSORTTracker

tracker = OCSORTTracker()
model = RFDETRMedium()

box_annotator = sv.BoxAnnotator()
label_annotator = sv.LabelAnnotator()

video_capture = cv2.VideoCapture("<RTSP_STREAM_URL>")
if not video_capture.isOpened():
    raise RuntimeError("Failed to open RTSP stream")

while True:
    success, frame_bgr = video_capture.read()
    if not success:
        break

    frame_rgb = cv2.cvtColor(frame_bgr, cv2.COLOR_BGR2RGB)
    detections = model.predict(frame_rgb)
    detections = tracker.update(detections)

    annotated_frame = box_annotator.annotate(frame_bgr, detections)
    annotated_frame = label_annotator.annotate(
        annotated_frame, detections, labels=detections.tracker_id
    )

    cv2.imshow("RF-DETR + OC-SORT", annotated_frame)
    if cv2.waitKey(1) & 0xFF == ord("q"):
        break

video_capture.release()
cv2.destroyAllWindows()

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