# Modified deepsort.py — Target ID recovery with IOU threshold and smooth tracking import os import cv2 import time import argparse import torch import warnings import json import sys import numpy as np sys.path.append(os.path.join(os.path.dirname(__file__), 'thirdparty/fast-reid')) from detector import build_detector from deep_sort import build_tracker from utils.draw import draw_boxes from utils.parser import get_config from utils.log import get_logger from utils.io import write_results def compute_iou(box1, box2): if box1 is None or box2 is None: return 0.0 xi1, yi1 = max(box1[0], box2[0]), max(box1[1], box2[1]) xi2, yi2 = min(box1[2], box2[2]), min(box1[3], box2[3]) inter_area = max(0, xi2 - xi1) * max(0, yi2 - yi1) box1_area = (box1[2] - box1[0]) * (box1[3] - box1[1]) box2_area = (box2[2] - box2[0]) * (box2[3] - box2[1]) union = box1_area + box2_area - inter_area return inter_area / union if union > 0 else 0.0 def get_best_iou_track(outputs, target_bbox, return_iou=False): if target_bbox is None: return (None, 0.0) if return_iou else None best_iou = 0 best_id = None for det in outputs: x1, y1, x2, y2 = det[:4] track_id = int(det[-1]) iou = compute_iou([x1, y1, x2, y2], target_bbox) if iou > best_iou: best_iou = iou best_id = track_id if return_iou: return best_id, best_iou return best_id class VideoTracker: def __init__(self, cfg, args, video_path): self.cfg = cfg self.args = args self.video_path = video_path self.logger = get_logger("root") self.first_frame_flag = True self.target_id = None self.last_known_bbox = None use_cuda = args.use_cuda and torch.cuda.is_available() if not use_cuda: warnings.warn("Running in cpu mode which maybe very slow!", UserWarning) if args.display: cv2.namedWindow("test", cv2.WINDOW_NORMAL) cv2.resizeWindow("test", args.display_width, args.display_height) if args.cam != -1: self.vdo = cv2.VideoCapture(args.cam) else: self.vdo = cv2.VideoCapture(video_path) self.detector = build_detector(cfg, use_cuda=use_cuda, segment=args.segment) self.deepsort = build_tracker(cfg, use_cuda=use_cuda) def run(self): results = [] idx_frame = 0 with open('coco_classes.json', 'r') as f: idx_to_class = json.load(f) if not self.vdo.isOpened(): raise IOError("Failed to open video") im_width = int(self.vdo.get(cv2.CAP_PROP_FRAME_WIDTH)) im_height = int(self.vdo.get(cv2.CAP_PROP_FRAME_HEIGHT)) if self.args.save_path: os.makedirs(self.args.save_path, exist_ok=True) self.writer = cv2.VideoWriter( os.path.join(self.args.save_path, "results.avi"), cv2.VideoWriter_fourcc(*'MJPG'), 20, (im_width, im_height)) while self.vdo.grab(): idx_frame += 1 if idx_frame % self.args.frame_interval: continue _, ori_im = self.vdo.retrieve() im = cv2.cvtColor(ori_im, cv2.COLOR_BGR2RGB) if self.args.segment: bbox_xywh, cls_conf, cls_ids, seg_masks = self.detector(im) else: bbox_xywh, cls_conf, cls_ids = self.detector(im) mask = cls_ids == 0 # person class bbox_xywh = bbox_xywh[mask] cls_conf = cls_conf[mask] cls_ids = cls_ids[mask] if bbox_xywh.shape[0] == 0: continue bbox_xywh[:, 2:] *= 1.2 if self.args.segment: seg_masks = seg_masks[mask] outputs, mask_outputs = self.deepsort.update(bbox_xywh, cls_conf, cls_ids, im, seg_masks) else: outputs, _ = self.deepsort.update(bbox_xywh, cls_conf, cls_ids, im) if self.first_frame_flag and len(outputs) > 0: cv2.imshow("Select target", ori_im) cv2.waitKey(1) target_roi = cv2.selectROI("Select target", ori_im, False, False) cv2.destroyWindow("Select target") target_bbox = [target_roi[0], target_roi[1], target_roi[0] + target_roi[2], target_roi[1] + target_roi[3]] self.target_id = get_best_iou_track(outputs, target_bbox) self.last_known_bbox = target_bbox print(f"[INFO] Selected target ID: {self.target_id}") self.first_frame_flag = False continue bbox_tlwh = [] filtered_outputs = [] for det in outputs: if int(det[-1]) == self.target_id: filtered_outputs.append(det) self.last_known_bbox = det[:4] if len(filtered_outputs) == 0 and self.last_known_bbox is not None: new_id, best_iou = get_best_iou_track(outputs, self.last_known_bbox, return_iou=True) if best_iou > 0.4: self.target_id = new_id print(f"[INFO] Target temporarily lost. Reassigned to ID {self.target_id} (IOU={best_iou:.2f})") for det in outputs: if int(det[-1]) == self.target_id: filtered_outputs.append(det) self.last_known_bbox = det[:4] else: print("[INFO] IOU too low to reassign. Skipping reassignment.") if len(filtered_outputs) > 0: def box_center(box): return np.array([(box[0] + box[2]) / 2, (box[1] + box[3]) / 2]) smoothed_outputs = [] for det in filtered_outputs: if self.last_known_bbox is None: smoothed_outputs.append(det) continue dist = np.linalg.norm(box_center(det[:4]) - box_center(self.last_known_bbox)) if dist < 300: smoothed_outputs.append(det) else: print(f"[INFO] Skipped jumpy box with dist={dist:.2f}") if len(smoothed_outputs) > 0: bbox_xyxy = np.array([det[:4] for det in smoothed_outputs]) identities = [int(det[-1]) for det in smoothed_outputs] cls = [int(det[-2]) for det in smoothed_outputs] names = [idx_to_class[str(label)] for label in cls] ori_im = draw_boxes(ori_im, bbox_xyxy, names, identities) for box in bbox_xyxy: bbox_tlwh.append(self.deepsort._xyxy_to_tlwh(box)) results.append((idx_frame - 1, bbox_tlwh, identities, cls)) if self.args.display: cv2.imshow("test", ori_im) if cv2.waitKey(1) & 0xFF == ord('q'): break if self.args.save_path: self.writer.write(ori_im) if self.args.save_path: write_results(os.path.join(self.args.save_path, "results.txt"), results, 'mot') self.vdo.release() if self.args.display: cv2.destroyAllWindows() def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("--VIDEO_PATH", type=str, default="demo.avi") parser.add_argument("--config_mmdetection", type=str, default="./configs/mmdet.yaml") parser.add_argument("--config_detection", type=str, default="./configs/mask_rcnn.yaml") parser.add_argument("--config_deepsort", type=str, default="./configs/deep_sort.yaml") parser.add_argument("--config_fastreid", type=str, default="./configs/fastreid.yaml") parser.add_argument("--fastreid", action="store_true") parser.add_argument("--mmdet", action="store_true") parser.add_argument("--segment", action="store_true") parser.add_argument("--display", action="store_true") parser.add_argument("--frame_interval", type=int, default=1) parser.add_argument("--display_width", type=int, default=800) parser.add_argument("--display_height", type=int, default=600) parser.add_argument("--save_path", type=str, default="./output/") parser.add_argument("--cpu", dest="use_cuda", action="store_false", default=True) parser.add_argument("--camera", action="store", dest="cam", type=int, default="-1") return parser.parse_args() if __name__ == "__main__": args = parse_args() cfg = get_config() cfg.USE_SEGMENT = args.segment cfg.USE_MMDET = args.mmdet cfg.USE_FASTREID = args.fastreid cfg.merge_from_file(args.config_mmdetection if args.mmdet else args.config_detection) cfg.merge_from_file(args.config_deepsort) if args.fastreid: cfg.merge_from_file(args.config_fastreid) tracker = VideoTracker(cfg, args, video_path=args.VIDEO_PATH) tracker.run()