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README.md
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README.md
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# Tutorials
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# Tutorials
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* [Train Custom Data](https://github.com/ultralytics/yolov3/wiki/Train-Custom-Data) ** << recommended**
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* [Train Custom Data](https://github.com/ultralytics/yolov3/wiki/Train-Custom-Data) < highly recommended!!
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* [Train Single Class](https://github.com/ultralytics/yolov3/wiki/Example:-Train-Single-Class)
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* [Train Single Class](https://github.com/ultralytics/yolov3/wiki/Example:-Train-Single-Class)
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* [Google Colab Notebook](https://colab.research.google.com/drive/1G8T-VFxQkjDe4idzN8F-hbIBqkkkQnxw) with quick training, inference and testing examples
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* [Google Colab Notebook](https://colab.research.google.com/drive/1G8T-VFxQkjDe4idzN8F-hbIBqkkkQnxw) with quick training, inference and testing examples
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* [GCP Quickstart](https://github.com/ultralytics/yolov3/wiki/GCP-Quickstart)
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* [GCP Quickstart](https://github.com/ultralytics/yolov3/wiki/GCP-Quickstart)
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## Image Augmentation
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## Image Augmentation
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`datasets.py` applies random OpenCV-powered (https://opencv.org/) augmentation to the input images in accordance with the following specifications. Augmentation is applied **only** during training, not during inference. Bounding boxes are automatically tracked and updated with the images. 416 x 416 examples pictured below.
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`datasets.py` applies OpenCV-powered (https://opencv.org/) augmentation to the input image. We use a **mosaic dataloader** (pictured below) to increase image variability during training.
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Augmentation | Description
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--- | ---
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Translation | +/- 10% (vertical and horizontal)
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Rotation | +/- 5 degrees
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Shear | +/- 2 degrees (vertical and horizontal)
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Scale | +/- 10%
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Reflection | 50% probability (horizontal-only)
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H**S**V Saturation | +/- 50%
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HS**V** Intensity | +/- 50%
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<img src="https://user-images.githubusercontent.com/26833433/66699231-27beea80-ece5-11e9-9cad-bdf9d82c500a.jpg" width="900">
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<img src="https://user-images.githubusercontent.com/26833433/66699231-27beea80-ece5-11e9-9cad-bdf9d82c500a.jpg" width="900">
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@ -89,8 +79,6 @@ V100 |1<br>2| 32 x 2<br>64 x 1 | 122<br>**178** | 16 min<br>**11 min** | **$0.
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# Inference
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# Inference
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`detect.py` runs inference on any sources:
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```bash
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```bash
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python3 detect.py --source ...
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python3 detect.py --source ...
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```
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```
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@ -102,15 +90,13 @@ python3 detect.py --source ...
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- RTSP stream: `--source rtsp://170.93.143.139/rtplive/470011e600ef003a004ee33696235daa`
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- RTSP stream: `--source rtsp://170.93.143.139/rtplive/470011e600ef003a004ee33696235daa`
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- HTTP stream: `--source http://wmccpinetop.axiscam.net/mjpg/video.mjpg`
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- HTTP stream: `--source http://wmccpinetop.axiscam.net/mjpg/video.mjpg`
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To run a specific models:
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**YOLOv3:** `python3 detect.py --cfg cfg/yolov3.cfg --weights yolov3.pt`
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**YOLOv3:** `python3 detect.py --cfg cfg/yolov3.cfg --weights yolov3.weights`
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<img src="https://user-images.githubusercontent.com/26833433/64067835-51d5b500-cc2f-11e9-982e-843f7f9a6ea2.jpg" width="500">
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<img src="https://user-images.githubusercontent.com/26833433/64067835-51d5b500-cc2f-11e9-982e-843f7f9a6ea2.jpg" width="500">
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**YOLOv3-tiny:** `python3 detect.py --cfg cfg/yolov3-tiny.cfg --weights yolov3-tiny.weights`
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**YOLOv3-tiny:** `python3 detect.py --cfg cfg/yolov3-tiny.cfg --weights yolov3-tiny.pt`
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<img src="https://user-images.githubusercontent.com/26833433/64067834-51d5b500-cc2f-11e9-9357-c485b159a20b.jpg" width="500">
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<img src="https://user-images.githubusercontent.com/26833433/64067834-51d5b500-cc2f-11e9-9357-c485b159a20b.jpg" width="500">
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**YOLOv3-SPP:** `python3 detect.py --cfg cfg/yolov3-spp.cfg --weights yolov3-spp.weights`
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**YOLOv3-SPP:** `python3 detect.py --cfg cfg/yolov3-spp.cfg --weights yolov3-spp.pt`
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<img src="https://user-images.githubusercontent.com/26833433/64067833-51d5b500-cc2f-11e9-8208-6fe197809131.jpg" width="500">
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<img src="https://user-images.githubusercontent.com/26833433/64067833-51d5b500-cc2f-11e9-8208-6fe197809131.jpg" width="500">
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