https://github.com/deshwalmahesh/yolov7-deepsort-tracking
Modular and ready to deploy code to detect and track videos using YOLO-v7 and DeepSORT
https://github.com/deshwalmahesh/yolov7-deepsort-tracking
Last synced: 6 months ago
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Modular and ready to deploy code to detect and track videos using YOLO-v7 and DeepSORT
- Host: GitHub
- URL: https://github.com/deshwalmahesh/yolov7-deepsort-tracking
- Owner: deshwalmahesh
- Created: 2022-07-13T10:30:51.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2022-12-30T05:10:06.000Z (almost 3 years ago)
- Last Synced: 2025-04-01T03:36:56.293Z (7 months ago)
- Language: Jupyter Notebook
- Size: 66.5 MB
- Stars: 162
- Watchers: 2
- Forks: 66
- Open Issues: 13
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Metadata Files:
- Readme: readme.md
Awesome Lists containing this project
- awesome-yolo-object-detection - deshwalmahesh/yolov7-deepsort-tracking - deepsort-tracking?style=social"/> : Modular and ready to deploy code to detect and track videos using YOLO-v7 and DeepSORT. (Object Detection Applications)
- awesome-yolo-object-detection - deshwalmahesh/yolov7-deepsort-tracking - deepsort-tracking?style=social"/> : Modular and ready to deploy code to detect and track videos using YOLO-v7 and DeepSORT. (Applications)
README
# Welcome!
This repo uses official implementations (with modifications) of [YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors](https://github.com/WongKinYiu/yolov7) and [Simple Online and Realtime Tracking with a Deep Association Metric (Deep SORT)](https://github.com/nwojke/deep_sort) to detect objects from images, videos and then track objects in Videos (tracking in images does not make sense)
I have refactored the code, removed dependencies, removed extra code so that you can use **ANY** detector model with `DeepSORT`. Please look at the `Demo.ipynb` notebook on how to use the code.
# Steps:
To use in `Colab`: Open `Colab Demo.ipynb`
For use in local system, please follow the below steps
1. Clone the repo as `git clone https://github.com/deshwalmahesh/yolov7-deepsort-tracking/`
2. Download the weights of any of the pre trained `YOLOv7` models from the links: [`yolov7.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7.pt) [`yolov7x.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7x.pt) [`yolov7-w6.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-w6.pt) [`yolov7-e6.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-e6.pt) [`yolov7-d6.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-d6.pt) [`yolov7-e6e.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-e6e.pt)
3. **NOTE**: Every model has it's own parameters like `image_size` and all so you have to use the appropriate parameters. This repo was tested successfully with [`yolov7x.pt`](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7x.pt)
4. Go to `Demo.ipynb` and run the code.
# Troubleshooting
This code works **perfectly** with `python== 3.7, tensorflow==2.8.0, torch== 1.8.0, sklearn==0.24.2` on local **Ubuntu: CPU** as well as **Colab: CPU + GPU** as of `13/07/2022`.
One of the most frequent problem is with the `PATH` such as model weights, input, output etc so pass in the path of the weights carefully. Do not just `run all` all the cells given in the notebook. this code works perfectly as long as you pass the correct path.
If you find yourself in trouble, please raise an issue.
# References
1. [YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors](https://github.com/WongKinYiu/yolov7)
2. [Simple Online and Realtime Tracking with a Deep Association Metric (Deep SORT)](https://github.com/nwojke/deep_sort)
3. [Tensorflow-v1 error code help](https://github.com/theAIGuysCode/yolov4-deepsort)
# Help, Issues and Future work
Any issues, help, bug, feature requestd andd suggestions are very much welcomed. Please feel free to open up the issues.
I'll be putting the quantized `Onnx` deployable version here along with `Docker` image in some time. If you have the time and expertise, please free to open up a merge request.