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- <a href="https://apps.apple.com/app/id1452689527" target="_blank">
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- <img src="https://user-images.githubusercontent.com/26833433/98699617-a1595a00-2377-11eb-8145-fc674eb9b1a7.jpg" width="1000"></a>
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  &nbsp
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  <a href="https://github.com/ultralytics/yolov5/actions"><img src="https://github.com/ultralytics/yolov5/workflows/CI%20CPU%20testing/badge.svg" alt="CI CPU testing"></a>
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  This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and evolution on anonymized client datasets. **All code and models are under active development, and are subject to modification or deletion without notice.** Use at your own risk.
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- <p align="center"><img width="800" src="https://user-images.githubusercontent.com/26833433/114313216-f0a5e100-9af5-11eb-8445-c682b60da2e3.png"></p>
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  <details>
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  <summary>YOLOv5-P5 640 Figure (click to expand)</summary>
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- <p align="center"><img width="800" src="https://user-images.githubusercontent.com/26833433/114313219-f1d70e00-9af5-11eb-9973-52b1f98d321a.png"></p>
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  </details>
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  <details>
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  <summary>Figure Notes (click to expand)</summary>
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  Results saved to runs/detect/exp2
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  Done. (0.103s)
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  ```
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- <img src="https://user-images.githubusercontent.com/26833433/97107365-685a8d80-16c7-11eb-8c2e-83aac701d8b9.jpeg" width="500">
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  ### PyTorch Hub
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  yolov5l 24
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  yolov5x 16
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  ```
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- <img src="https://user-images.githubusercontent.com/26833433/90222759-949d8800-ddc1-11ea-9fa1-1c97eed2b963.png" width="900">
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  ## Citation
 
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+ <a align="left" href="https://apps.apple.com/app/id1452689527" target="_blank">
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+ <img width="800" src="https://user-images.githubusercontent.com/26833433/98699617-a1595a00-2377-11eb-8145-fc674eb9b1a7.jpg"></a>
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  &nbsp
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  <a href="https://github.com/ultralytics/yolov5/actions"><img src="https://github.com/ultralytics/yolov5/workflows/CI%20CPU%20testing/badge.svg" alt="CI CPU testing"></a>
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  This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices evolved over thousands of hours of training and evolution on anonymized client datasets. **All code and models are under active development, and are subject to modification or deletion without notice.** Use at your own risk.
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+ <p align="left"><img width="800" src="https://user-images.githubusercontent.com/26833433/114313216-f0a5e100-9af5-11eb-8445-c682b60da2e3.png"></p>
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  <details>
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  <summary>YOLOv5-P5 640 Figure (click to expand)</summary>
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+ <p align="left"><img width="800" src="https://user-images.githubusercontent.com/26833433/114313219-f1d70e00-9af5-11eb-9973-52b1f98d321a.png"></p>
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  </details>
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  <details>
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  <summary>Figure Notes (click to expand)</summary>
 
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  Results saved to runs/detect/exp2
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  Done. (0.103s)
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  ```
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+ <img width="500" src="https://user-images.githubusercontent.com/26833433/97107365-685a8d80-16c7-11eb-8c2e-83aac701d8b9.jpeg">
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  ### PyTorch Hub
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  yolov5l 24
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  yolov5x 16
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  ```
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+ <img width="800" src="https://user-images.githubusercontent.com/26833433/90222759-949d8800-ddc1-11ea-9fa1-1c97eed2b963.png">
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  ## Citation