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Zhongdao / UniTrack

[NeurIPS'21] Unified tracking framework with a single appearance model. It supports Single Object Tracking (SOT), Video Object Segmentation (VOS), Multi-Object Tracking (MOT), Multi-Object Tracking and Segmentation (MOTS), Pose Tracking, Video Instance Segmentation (VIS), and class-agnostic MOT (e.g. TAO dataset).
MIT License
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mot_demo issue #34

Closed CarlHuangNuc closed 2 years ago

CarlHuangNuc commented 2 years ago

python demo/mot_demo.py --classes 1 2demo/mot_demo.py:186: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. common_args = yaml.load(f) 2022-04-23 12:44:56.034 | INFO | main:main:135 - Args: Namespace(asso_with_motion=True, ckpt='./detector/YOLOX/weights/yolox_x.pth', classes=[1, 2], conf=0.65, conf_thres=0.65, config='./config/imagenet_resnet18_s3.yaml', confirm_iou_thres=0.7, demo='video', device='cuda', down_factor=8, dup_iou_thres=0.15, exp_file='./detector/YOLOX/exps/default/yolox_x.py', exp_name='imagenet_resnet18_s3', feat_size=[4, 10], gpu_id=0, im_mean=[0.485, 0.456, 0.406], im_std=[0.229, 0.224, 0.225], img_size=[640, 480], infer2D=True, iou_thres=0.5, min_box_area=200, model_type='imagenet18', mot_root='/home/wangzd/datasets/MOT/MOT16', motion_gated=True, motion_lambda=0.98, nms=None, nms_thres=0.4, nopadding=False, obid='FairMOT', output_root='./results/mot_demo', path='../mmtracking-master/demo/demo.mp4', prop_flag=False, remove_layers=['layer4'], resume='None', save_images=False, save_result=False, save_videos=True, test_mot16=False, track_buffer=30, tsize=[640, 480], use_kalman=True, workers=4) Lenth of the video: 8 frames 1111111111111111111111111 /dfs/data/miniconda3/envs/openmmlab/lib/python3.7/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1639180594101/work/aten/src/ATen/native/TensorShape.cpp:2157.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] 2022-04-23 12:44:57.335 | INFO | main:main:149 - Model Summary: Params: 99.07M, Gflops: 211.45 2022-04-23 12:45:05.732 | INFO | main:main:152 - loading checkpoint <class 'dict'> Traceback (most recent call last): File "demo/mot_demo.py", line 201, in main(exp, args) File "demo/mot_demo.py", line 158, in main det_model.load_state_dict(ckpt["model"]) KeyError: 'model'

i using YOLOX default pretrain train coco weight.(https://github.com/open-mmlab/mmdetection/tree/master/configs/yolox)

Zhongdao commented 2 years ago

It seems the model weights you are using have different keys to the official yolox models. Could you please try using models from the official repo? Here it is: https://github.com/Megvii-BaseDetection/YOLOX

CarlHuangNuc commented 2 years ago

Thanks, fix it.