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ultralytics 8.0.48 Edge TPU fix and Metrics updates (#1171)

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: majid nasiri <majnasai@gmail.com>
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Glenn Jocher
2023-02-27 21:34:22 -08:00
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commit 74e4c94806
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docs/predict.md
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@ -28,6 +28,29 @@ predictor's call method.
probs = r.probs # Class probabilities for classification outputs
```
## Sources
YOLOv8 can run inference on a variety of sources. The table below lists the various sources that can be used as input
for YOLOv8, along with the required format and notes. Sources include images, URLs, PIL images, OpenCV, numpy arrays,
torch tensors, CSV files, videos, directories, globs, YouTube videos, and streams. The table also indicates whether each
source can be used as a stream and the model argument required for that source.
| source | stream | model(arg) | type | notes |
|------------|---------|--------------------------------------------|----------------|------------------|
| image | | `'im.jpg'` | `str`, `Path` | |
| URL | | `'https://ultralytics.com/images/bus.jpg'` | `str` | |
| screenshot | | `'screen'` | `str` | |
| PIL | | `Image.open('im.jpg')` | `PIL.Image` | HWC, RGB |
| OpenCV | | `cv2.imread('im.jpg')[:,:,::-1]` | `np.ndarray` | HWC, BGR to RGB |
| numpy | | `np.zeros((640,1280,3))` | `np.ndarray` | HWC |
| torch | | `torch.zeros(16,3,320,640)` | `torch.Tensor` | BCHW, RGB |
| CSV | | `'sources.csv'` | `str`, `Path` | RTSP, RTMP, HTTP |
| video | &check; | `'vid.mp4'` | `str`, `Path` | |
| directory | &check; | `'path/'` | `str`, `Path` | |
| glob | &check; | `path/*.jpg'` | `str` | Use `*` operator |
| YouTube | &check; | `'https://youtu.be/Zgi9g1ksQHc'` | `str` | |
| stream | &check; | `'rtsp://example.com/media.mp4'` | `str` | RTSP, RTMP, HTTP |
## Working with Results
Results object consists of these component objects: