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deep_sort_pytorch.zip
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更新日期:2025-09-22

deep-sort-pytorch

资源文件列表(大概)

文件名
大小
deep_sort_pytorch/utils/__init__.py
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deep_sort_pytorch/deep_sort/sort - Copy/__init__.py
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deep_sort_pytorch/utils/draw.py
1.13KB
deep_sort_pytorch/utils/io.py
4.25KB
deep_sort_pytorch/utils/json_logger.py
11.49KB
deep_sort_pytorch/configs/deep_sort.yaml
208B
deep_sort_pytorch/deep_sort/__init__.py
500B
deep_sort_pytorch/utils/log.py
480B
deep_sort_pytorch/utils/parser.py
1.05KB
deep_sort_pytorch/README.md
4.83KB
deep_sort_pytorch/utils/__pycache__/parser.cpython-310.pyc
1.64KB
deep_sort_pytorch/utils/__pycache__/__init__.cpython-310.pyc
252B
deep_sort_pytorch/deep_sort/README.md
65B
deep_sort_pytorch/utils/__pycache__/__init__.cpython-38.pyc
160B
deep_sort_pytorch/deep_sort/deep/checkpoint/.gitkeep
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deep_sort_pytorch/LICENSE
1.04KB
deep_sort_pytorch/deep_sort/deep/__init__.py
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deep_sort_pytorch/deep_sort/__pycache__/deep_sort.cpython-310.pyc
4.11KB
deep_sort_pytorch/deep_sort/sort/tracker.py
5.31KB
deep_sort_pytorch/deep_sort/deep/test.py
2.48KB
deep_sort_pytorch/utils/evaluation.py
3.45KB
deep_sort_pytorch/deep_sort/sort/__init__.py
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deep_sort_pytorch/deep_sort/__pycache__/__init__.cpython-310.pyc
712B
deep_sort_pytorch/utils/asserts.py
316B
deep_sort_pytorch/utils/__pycache__/parser.cpython-37.pyc
1.52KB
deep_sort_pytorch/deep_sort/sort/detection.py
1.43KB
deep_sort_pytorch/.gitignore
89B
deep_sort_pytorch/deep_sort/deep/train.jpg
58.93KB
deep_sort_pytorch/utils/__pycache__/parser.cpython-38.pyc
1.51KB
deep_sort_pytorch/deep_sort/deep/__pycache__/model.cpython-310.pyc
2.86KB
deep_sort_pytorch/deep_sort/__pycache__/deep_sort.cpython-38.pyc
4.06KB
deep_sort_pytorch/deep_sort/sort - Copy/nn_matching.py
5.51KB
deep_sort_pytorch/deep_sort/deep_sort.py
3.77KB
deep_sort_pytorch/utils/tools.py
734B
deep_sort_pytorch/deep_sort/deep/train.py
6.17KB
deep_sort_pytorch/deep_sort/deep/__pycache__/__init__.cpython-310.pyc
261B
deep_sort_pytorch/deep_sort/__pycache__/__init__.cpython-37.pyc
639B
deep_sort_pytorch/deep_sort/deep/feature_extractor.py
1.73KB
deep_sort_pytorch/deep_sort/sort - Copy/linear_assignment.py
7.9KB
deep_sort_pytorch/deep_sort/sort - Copy/iou_matching.py
2.86KB
deep_sort_pytorch/deep_sort/sort/track.py
4.94KB
deep_sort_pytorch/deep_sort/__pycache__/deep_sort.cpython-37.pyc
4KB
deep_sort_pytorch/deep_sort/deep/evaluate.py
307B
deep_sort_pytorch/deep_sort/sort/nn_matching.py
5.51KB
deep_sort_pytorch/deep_sort/deep/__pycache__/__init__.cpython-37.pyc
194B
deep_sort_pytorch/deep_sort/__pycache__/__init__.cpython-38.pyc
630B
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/__init__.cpython-38.pyc
169B
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/kalman_filter.cpython-38.pyc
6.61KB
deep_sort_pytorch/deep_sort/deep/__pycache__/feature_extractor.cpython-310.pyc
2.5KB
deep_sort_pytorch/deep_sort/deep/__pycache__/feature_extractor.cpython-37.pyc
2.37KB
deep_sort_pytorch/utils/__pycache__/__init__.cpython-37.pyc
173B
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/linear_assignment.cpython-37.pyc
6.81KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/detection.cpython-38.pyc
1.83KB
deep_sort_pytorch/deep_sort/deep/__pycache__/__init__.cpython-38.pyc
169B
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/iou_matching.cpython-37.pyc
2.83KB
deep_sort_pytorch/deep_sort/deep/original_model.py
3.26KB
deep_sort_pytorch/deep_sort/deep/__pycache__/feature_extractor.cpython-38.pyc
2.38KB
deep_sort_pytorch/deep_sort/deep/model.py
3.34KB
deep_sort_pytorch/deep_sort/deep/__pycache__/model.cpython-38.pyc
2.77KB
deep_sort_pytorch/deep_sort/sort/linear_assignment.py
7.9KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/iou_matching.cpython-38.pyc
2.82KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/nn_matching.cpython-38.pyc
5.92KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/track.cpython-38.pyc
5.48KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/detection.cpython-37.pyc
1.86KB
deep_sort_pytorch/deep_sort/sort/iou_matching.py
2.86KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/nn_matching.cpython-37.pyc
5.93KB
deep_sort_pytorch/deep_sort/deep/__pycache__/model.cpython-37.pyc
2.77KB
deep_sort_pytorch/deep_sort/sort/__pycache__/iou_matching.cpython-38.pyc
2.82KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/__init__.cpython-37.pyc
194B
deep_sort_pytorch/deep_sort/sort/__pycache__/__init__.cpython-38.pyc
169B
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/kalman_filter.cpython-37.pyc
6.57KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/track.cpython-37.pyc
5.47KB
deep_sort_pytorch/deep_sort/sort/__pycache__/track.cpython-310.pyc
5.58KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/tracker.cpython-37.pyc
5.47KB
deep_sort_pytorch/deep_sort/sort/__pycache__/nn_matching.cpython-38.pyc
5.92KB
deep_sort_pytorch/deep_sort/sort/__pycache__/iou_matching.cpython-310.pyc
2.91KB
deep_sort_pytorch/deep_sort/sort/__pycache__/linear_assignment.cpython-310.pyc
6.91KB
deep_sort_pytorch/deep_sort/sort/__pycache__/linear_assignment.cpython-37.pyc
6.81KB
deep_sort_pytorch/deep_sort/sort/__pycache__/kalman_filter.cpython-38.pyc
6.61KB
deep_sort_pytorch/deep_sort/sort/__pycache__/detection.cpython-310.pyc
1.94KB
deep_sort_pytorch/deep_sort/sort/__pycache__/__init__.cpython-310.pyc
261B
deep_sort_pytorch/deep_sort/sort/__pycache__/tracker.cpython-37.pyc
5.47KB
deep_sort_pytorch/deep_sort/sort/__pycache__/__init__.cpython-37.pyc
194B
deep_sort_pytorch/deep_sort/sort/__pycache__/iou_matching.cpython-37.pyc
2.83KB
deep_sort_pytorch/deep_sort/sort/__pycache__/track.cpython-37.pyc
5.47KB
deep_sort_pytorch/deep_sort/sort/__pycache__/nn_matching.cpython-310.pyc
6.01KB
deep_sort_pytorch/deep_sort/sort/__pycache__/nn_matching.cpython-37.pyc
5.93KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/linear_assignment.cpython-38.pyc
6.83KB
deep_sort_pytorch/deep_sort/sort/__pycache__/kalman_filter.cpython-37.pyc
6.57KB
deep_sort_pytorch/deep_sort/sort/__pycache__/linear_assignment.cpython-38.pyc
6.83KB
deep_sort_pytorch/deep_sort/sort - Copy/kalman_filter.py
7.83KB
deep_sort_pytorch/deep_sort/sort - Copy/__pycache__/tracker.cpython-38.pyc
5.52KB
deep_sort_pytorch/deep_sort/sort/__pycache__/detection.cpython-38.pyc
1.86KB
deep_sort_pytorch/deep_sort/sort/__pycache__/tracker.cpython-38.pyc
5.55KB
deep_sort_pytorch/deep_sort/sort/__pycache__/track.cpython-38.pyc
5.51KB
deep_sort_pytorch/deep_sort/sort/__pycache__/tracker.cpython-310.pyc
5.55KB
deep_sort_pytorch/deep_sort/sort/__pycache__/detection.cpython-37.pyc
1.86KB
deep_sort_pytorch/deep_sort/sort/__pycache__/kalman_filter.cpython-310.pyc
6.69KB
deep_sort_pytorch/deep_sort/sort - Copy/preprocessing.py
1.94KB
deep_sort_pytorch/deep_sort/sort/kalman_filter.py
7.83KB
deep_sort_pytorch/deep_sort/sort/preprocessing.py
1.94KB
deep_sort_pytorch/deep_sort/deep/checkpoint/ckpt.t7
43.9MB

资源内容介绍

多目标跟踪算法
# Deep Sort with PyTorch![](demo/demo.gif)## Update(1-1-2020)Changes- fix bugs- refactor code- accerate detection by adding nms on gpu## Latest Update(07-22)Changes- bug fix (Thanks @JieChen91 and @yingsen1 for bug reporting). - using batch for feature extracting for each frame, which lead to a small speed up. - code improvement.Futher improvement direction - Train detector on specific dataset rather than the official one.- Retrain REID model on pedestrain dataset for better performance.- Replace YOLOv3 detector with advanced ones.**Any contributions to this repository is welcome!**## IntroductionThis is an implement of MOT tracking algorithm deep sort. Deep sort is basicly the same with sort but added a CNN model to extract features in image of human part bounded by a detector. This CNN model is indeed a RE-ID model and the detector used in [PAPER](https://arxiv.org/abs/1703.07402) is FasterRCNN , and the original source code is [HERE](https://github.com/nwojke/deep_sort). However in original code, the CNN model is implemented with tensorflow, which I'm not familier with. SO I re-implemented the CNN feature extraction model with PyTorch, and changed the CNN model a little bit. Also, I use **YOLOv3** to generate bboxes instead of FasterRCNN.## Dependencies- python 3 (python2 not sure)- numpy- scipy- opencv-python- sklearn- torch >= 0.4- torchvision >= 0.1- pillow- vizer- edict## Quick Start0. Check all dependencies installed```bashpip install -r requirements.txt```for user in china, you can specify pypi source to accelerate install like:```bashpip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple```1. Clone this repository```git clone git@github.com:ZQPei/deep_sort_pytorch.git```2. Download YOLOv3 parameters```cd detector/YOLOv3/weight/wget https://pjreddie.com/media/files/yolov3.weightswget https://pjreddie.com/media/files/yolov3-tiny.weightscd ../../../```3. Download deepsort parameters ckpt.t7```cd deep_sort/deep/checkpoint# download ckpt.t7 fromhttps://drive.google.com/drive/folders/1xhG0kRH1EX5B9_Iz8gQJb7UNnn_riXi6 to this foldercd ../../../``` 4. Compile nms module```bashcd detector/YOLOv3/nmssh build.shcd ../../..```Notice:If compiling failed, the simplist way is to **Upgrade your pytorch >= 1.1 and torchvision >= 0.3" and you can avoid the troublesome compiling problems which are most likely caused by either `gcc version too low` or `libraries missing`.5. Run demo```usage: python yolov3_deepsort.py VIDEO_PATH [--help] [--frame_interval FRAME_INTERVAL] [--config_detection CONFIG_DETECTION] [--config_deepsort CONFIG_DEEPSORT] [--display] [--display_width DISPLAY_WIDTH] [--display_height DISPLAY_HEIGHT] [--save_path SAVE_PATH] [--cpu] # yolov3 + deepsortpython yolov3_deepsort.py [VIDEO_PATH]# yolov3_tiny + deepsortpython yolov3_deepsort.py [VIDEO_PATH] --config_detection ./configs/yolov3_tiny.yaml# yolov3 + deepsort on webcampython3 yolov3_deepsort.py /dev/video0 --camera 0# yolov3_tiny + deepsort on webcampython3 yolov3_deepsort.py /dev/video0 --config_detection ./configs/yolov3_tiny.yaml --camera 0```Use `--display` to enable display. Results will be saved to `./output/results.avi` and `./output/results.txt`.All files above can also be accessed from BaiduDisk! linker：[BaiduDisk](https://pan.baidu.com/s/1YJ1iPpdFTlUyLFoonYvozg)passwd：fbuw## Training the RE-ID modelThe original model used in paper is in original_model.py, and its parameter here [original_ckpt.t7](https://drive.google.com/drive/folders/1xhG0kRH1EX5B9_Iz8gQJb7UNnn_riXi6). To train the model, first you need download [Market1501](http://www.liangzheng.com.cn/Project/project_reid.html) dataset or [Mars](http://www.liangzheng.com.cn/Project/project_mars.html) dataset. Then you can try [train.py](deep_sort/deep/train.py) to train your own parameter and evaluate it using [test.py](deep_sort/deep/test.py) and [evaluate.py](deep_sort/deep/evalute.py).![train.jpg](deep_sort/deep/train.jpg)## Demo videos and images[demo.avi](https://drive.google.com/drive/folders/1xhG0kRH1EX5B9_Iz8gQJb7UNnn_riXi6)[demo2.avi](https://drive.google.com/drive/folders/1xhG0kRH1EX5B9_Iz8gQJb7UNnn_riXi6)![1.jpg](demo/1.jpg)![2.jpg](demo/2.jpg)## References- paper: [Simple Online and Realtime Tracking with a Deep Association Metric](https://arxiv.org/abs/1703.07402)- code: [nwojke/deep_sort](https://github.com/nwojke/deep_sort)- paper: [YOLOv3](https://pjreddie.com/media/files/papers/YOLOv3.pdf)- code: [Joseph Redmon/yolov3](https://pjreddie.com/darknet/yolo/)

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