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β¦s#7529) * Update .pre-commit-config.yaml * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update .pre-commit-config.yaml * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update CONTRIBUTING.md * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update README.md * Update README.md * Update README.md Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <[email protected]>
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@@ -103,8 +103,6 @@ results.print() # or .show(), .save(), .crop(), .pandas(), etc. | |
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</details> | ||
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<details> | ||
<summary>Inference with detect.py</summary> | ||
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@@ -149,20 +147,20 @@ python train.py --data coco.yaml --cfg yolov5n.yaml --weights '' --batch-size 12 | |
<details open> | ||
<summary>Tutorials</summary> | ||
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* [Train Custom Data](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data) π RECOMMENDED | ||
* [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results) βοΈ | ||
- [Train Custom Data](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data)Β π RECOMMENDED | ||
- [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results)Β βοΈ | ||
RECOMMENDED | ||
* [Weights & Biases Logging](https://github.com/ultralytics/yolov5/issues/1289) π NEW | ||
* [Roboflow for Datasets, Labeling, and Active Learning](https://github.com/ultralytics/yolov5/issues/4975) π NEW | ||
* [Multi-GPU Training](https://github.com/ultralytics/yolov5/issues/475) | ||
* [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36) β NEW | ||
* [TFLite, ONNX, CoreML, TensorRT Export](https://github.com/ultralytics/yolov5/issues/251) π | ||
* [Test-Time Augmentation (TTA)](https://github.com/ultralytics/yolov5/issues/303) | ||
* [Model Ensembling](https://github.com/ultralytics/yolov5/issues/318) | ||
* [Model Pruning/Sparsity](https://github.com/ultralytics/yolov5/issues/304) | ||
* [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607) | ||
* [Transfer Learning with Frozen Layers](https://github.com/ultralytics/yolov5/issues/1314) β NEW | ||
* [Architecture Summary](https://github.com/ultralytics/yolov5/issues/6998) β NEW | ||
- [Weights & Biases Logging](https://github.com/ultralytics/yolov5/issues/1289)Β π NEW | ||
- [Roboflow for Datasets, Labeling, and Active Learning](https://github.com/ultralytics/yolov5/issues/4975)Β π NEW | ||
- [Multi-GPU Training](https://github.com/ultralytics/yolov5/issues/475) | ||
- [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36)Β β NEW | ||
- [TFLite, ONNX, CoreML, TensorRT Export](https://github.com/ultralytics/yolov5/issues/251) π | ||
- [Test-Time Augmentation (TTA)](https://github.com/ultralytics/yolov5/issues/303) | ||
- [Model Ensembling](https://github.com/ultralytics/yolov5/issues/318) | ||
- [Model Pruning/Sparsity](https://github.com/ultralytics/yolov5/issues/304) | ||
- [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607) | ||
- [Transfer Learning with Frozen Layers](https://github.com/ultralytics/yolov5/issues/1314)Β β NEW | ||
- [Architecture Summary](https://github.com/ultralytics/yolov5/issues/6998)Β β NEW | ||
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</details> | ||
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@@ -203,7 +201,6 @@ Get started in seconds with our verified environments. Click each icon below for | |
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|Automatically track and visualize all your YOLOv5 training runs in the cloud with [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) | | ||
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<!-- ## <div align="center">Compete and Win</div> | ||
We are super excited about our first-ever Ultralytics YOLOv5 π EXPORT Competition with **$10,000** in cash prizes! | ||
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@@ -224,18 +221,15 @@ We are super excited about our first-ever Ultralytics YOLOv5 π EXPORT Competi | |
<details> | ||
<summary>Figure Notes (click to expand)</summary> | ||
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* **COCO AP val** denotes [email protected]:0.95 metric measured on the 5000-image [COCO val2017](http://cocodataset.org) dataset over various inference sizes from 256 to 1536. | ||
* **GPU Speed** measures average inference time per image on [COCO val2017](http://cocodataset.org) dataset using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) V100 instance at batch-size 32. | ||
* **EfficientDet** data from [google/automl](https://github.com/google/automl) at batch size 8. | ||
* **Reproduce** by `python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5n6.pt yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt` | ||
- **COCO AP val** denotes [email protected]:0.95 metric measured on the 5000-image [COCO val2017](http://cocodataset.org) dataset over various inference sizes from 256 to 1536. | ||
- **GPU Speed** measures average inference time per image on [COCO val2017](http://cocodataset.org) dataset using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) V100 instance at batch-size 32. | ||
- **EfficientDet** data from [google/automl](https://github.com/google/automl) at batch size 8. | ||
- **Reproduce** by `python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5n6.pt yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt` | ||
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</details> | ||
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### Pretrained Checkpoints | ||
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[assets]: https://github.com/ultralytics/yolov5/releases | ||
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[TTA]: https://github.com/ultralytics/yolov5/issues/303 | ||
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|Model |size<br><sup>(pixels) |mAP<sup>val<br>0.5:0.95 |mAP<sup>val<br>0.5 |Speed<br><sup>CPU b1<br>(ms) |Speed<br><sup>V100 b1<br>(ms) |Speed<br><sup>V100 b32<br>(ms) |params<br><sup>(M) |FLOPs<br><sup>@640 (B) | ||
|--- |--- |--- |--- |--- |--- |--- |--- |--- | ||
|[YOLOv5n][assets] |640 |28.0 |45.7 |**45** |**6.3**|**0.6**|**1.9**|**4.5** | ||
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@@ -253,10 +247,10 @@ We are super excited about our first-ever Ultralytics YOLOv5 π EXPORT Competi | |
<details> | ||
<summary>Table Notes (click to expand)</summary> | ||
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* All checkpoints are trained to 300 epochs with default settings. Nano and Small models use [hyp.scratch-low.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-low.yaml) hyps, all others use [hyp.scratch-high.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-high.yaml). | ||
* **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](http://cocodataset.org) dataset.<br>Reproduce by `python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65` | ||
* **Speed** averaged over COCO val images using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) instance. NMS times (~1 ms/img) not included.<br>Reproduce by `python val.py --data coco.yaml --img 640 --task speed --batch 1` | ||
* **TTA** [Test Time Augmentation](https://github.com/ultralytics/yolov5/issues/303) includes reflection and scale augmentations.<br>Reproduce by `python val.py --data coco.yaml --img 1536 --iou 0.7 --augment` | ||
- All checkpoints are trained to 300 epochs with default settings. Nano and Small models use [hyp.scratch-low.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-low.yaml) hyps, all others use [hyp.scratch-high.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-high.yaml). | ||
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](http://cocodataset.org) dataset.<br>Reproduce by `python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65` | ||
- **Speed** averaged over COCO val images using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) instance. NMS times (~1 ms/img) not included.<br>Reproduce by `python val.py --data coco.yaml --img 640 --task speed --batch 1` | ||
- **TTA** [Test Time Augmentation](https://github.com/ultralytics/yolov5/issues/303) includes reflection and scale augmentations.<br>Reproduce by `python val.py --data coco.yaml --img 1536 --iou 0.7 --augment` | ||
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</details> | ||
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@@ -302,3 +296,6 @@ professional support requests please visit [https://ultralytics.com/contact](htt | |
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-instagram.png" width="3%"/> | ||
</a> | ||
</div> | ||
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[assets]: https://github.com/ultralytics/yolov5/releases | ||
[tta]: https://github.com/ultralytics/yolov5/issues/303 |
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