https://github.com/shriram1998/pedestrianspeedestimator
Pedestrian Speed Estimation using yolov5, deepsort and homography matrix
https://github.com/shriram1998/pedestrianspeedestimator
ai computer-vision ml
Last synced: over 1 year ago
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Pedestrian Speed Estimation using yolov5, deepsort and homography matrix
- Host: GitHub
- URL: https://github.com/shriram1998/pedestrianspeedestimator
- Owner: shriram1998
- License: gpl-3.0
- Created: 2022-03-01T08:39:35.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2022-03-01T08:39:59.000Z (over 4 years ago)
- Last Synced: 2025-01-30T15:47:18.195Z (over 1 year ago)
- Topics: ai, computer-vision, ml
- Language: Python
- Homepage:
- Size: 19.8 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Pedestrian Speed Estimation using yolov5, deepsort and homography matrix
## Demo gif
## Before you run the tracker
1. Clone the repository
2. Install dependencies
`pip install -r requirements.txt`
## Download weights
Download [weights](https://drive.google.com/file/d/1gglIwqxaH2iTvy6lZlXuAcMpd_U0GCUb/view?usp=sharing) and place it in yolov5/weights folder
## Quick run
Add a video to data/videos folder and run the following command.
```bash
python track.py --source data/videos/test.mp4 --yolo_model yolov5/weights/crowdhuman_yolov5m.pt --classes 0 --show-vid --save-vid
```
Results are saved to folder `track/expN`
## Tracking sources
Tracking can be run on most video formats
```bash
$ python track.py --source 0 # webcam
img.jpg # image
vid.mp4 # video
path/ # directory
path/*.jpg # glob
'https://youtu.be/Zgi9g1ksQHc' # YouTube
'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP stream
```
### DeepSort
Choose a ReID model based on your needs from this ReID [model zoo](https://kaiyangzhou.github.io/deep-person-reid/MODEL_ZOO)
```bash
$ python track.py --source 0 --deep_sort_model osnet_x1_0
nasnsetmobile
resnext101_32x8d
...
```
## Reference
```latex
@misc{yolov5deepsort2020,
title={Real-time multi-object tracker using YOLOv5 and deep sort},
author={Mikel Broström},
howpublished = {\url{https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch}},
year={2020}
}
```