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# 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() |