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101 lines
3.5 KiB
101 lines
3.5 KiB
---
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comments: true
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description: Explore YOLOv8n-based object tracking with Ultralytics' BoT-SORT and ByteTrack. Learn configuration, usage, and customization tips.
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keywords: object tracking, YOLO, trackers, BoT-SORT, ByteTrack
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---
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<img width="1024" src="https://user-images.githubusercontent.com/26833433/243418637-1d6250fd-1515-4c10-a844-a32818ae6d46.png">
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Object tracking is a task that involves identifying the location and class of objects, then assigning a unique ID to
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that detection in video streams.
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The output of tracker is the same as detection with an added object ID.
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## Available Trackers
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The following tracking algorithms have been implemented and can be enabled by passing `tracker=tracker_type.yaml`
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* [BoT-SORT](https://github.com/NirAharon/BoT-SORT) - `botsort.yaml`
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* [ByteTrack](https://github.com/ifzhang/ByteTrack) - `bytetrack.yaml`
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The default tracker is BoT-SORT.
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## Tracking
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Use a trained YOLOv8n/YOLOv8n-seg model to run tracker on video streams.
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!!! example ""
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=== "Python"
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```python
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from ultralytics import YOLO
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# Load a model
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model = YOLO('yolov8n.pt') # load an official detection model
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model = YOLO('yolov8n-seg.pt') # load an official segmentation model
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model = YOLO('path/to/best.pt') # load a custom model
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# Track with the model
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results = model.track(source="https://youtu.be/Zgi9g1ksQHc", show=True)
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results = model.track(source="https://youtu.be/Zgi9g1ksQHc", show=True, tracker="bytetrack.yaml")
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```
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=== "CLI"
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```bash
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yolo track model=yolov8n.pt source="https://youtu.be/Zgi9g1ksQHc" # official detection model
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yolo track model=yolov8n-seg.pt source=... # official segmentation model
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yolo track model=path/to/best.pt source=... # custom model
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yolo track model=path/to/best.pt tracker="bytetrack.yaml" # bytetrack tracker
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```
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As in the above usage, we support both the detection and segmentation models for tracking and the only thing you need to
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do is loading the corresponding (detection or segmentation) model.
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## Configuration
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### Tracking
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Tracking shares the configuration with predict, i.e `conf`, `iou`, `show`. More configurations please refer
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to [predict page](https://docs.ultralytics.com/modes/predict/).
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!!! example ""
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=== "Python"
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```python
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from ultralytics import YOLO
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model = YOLO('yolov8n.pt')
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results = model.track(source="https://youtu.be/Zgi9g1ksQHc", conf=0.3, iou=0.5, show=True)
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```
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=== "CLI"
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```bash
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yolo track model=yolov8n.pt source="https://youtu.be/Zgi9g1ksQHc" conf=0.3, iou=0.5 show
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```
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### Tracker
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We also support using a modified tracker config file, just copy a config file i.e `custom_tracker.yaml`
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from [ultralytics/cfg/trackers](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/trackers) and modify
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any configurations(expect the `tracker_type`) you need to.
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!!! example ""
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=== "Python"
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```python
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from ultralytics import YOLO
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model = YOLO('yolov8n.pt')
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results = model.track(source="https://youtu.be/Zgi9g1ksQHc", tracker='custom_tracker.yaml')
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```
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=== "CLI"
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```bash
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yolo track model=yolov8n.pt source="https://youtu.be/Zgi9g1ksQHc" tracker='custom_tracker.yaml'
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```
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Please refer to [ultralytics/cfg/trackers](https://github.com/ultralytics/ultralytics/tree/main/ultralytics/cfg/trackers)
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page |