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ultralytics 8.0.70 minor fixes and improvements (#1892)

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Co-authored-by: feicccccccc <49809204+feicccccccc@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
This commit is contained in:
Glenn Jocher
2023-04-08 00:27:33 +02:00
committed by GitHub
parent c2cd3fd20e
commit c38b17a0d8
17 changed files with 71 additions and 90 deletions
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26
docs/modes/predict.md
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@ -216,19 +216,19 @@ masks, classification logits, etc.) found in the results object
res_plotted = res[0].plot()
cv2.imshow("result", res_plotted)
```
| Argument | Description |
| ----------- | ------------- |
| `conf (bool)` | Whether to plot the detection confidence score. |
| `line_width (float, optional)` | The line width of the bounding boxes. If None, it is scaled to the image size. |
| `font_size (float, optional)` | The font size of the text. If None, it is scaled to the image size. |
| `font (str)` | The font to use for the text. |
| `pil (bool)` | Whether to return the image as a PIL Image. |
| `example (str)` | An example string to display. Useful for indicating the expected format of the output. |
| `img (numpy.ndarray)` | Plot to another image. if not, plot to original image. |
| `labels (bool)` | Whether to plot the label of bounding boxes. |
| `boxes (bool)` | Whether to plot the bounding boxes. |
| `masks (bool)` | Whether to plot the masks. |
| `probs (bool)` | Whether to plot classification probability. |
| Argument | Description |
|--------------------------------|----------------------------------------------------------------------------------------|
| `conf (bool)` | Whether to plot the detection confidence score. |
| `line_width (float, optional)` | The line width of the bounding boxes. If None, it is scaled to the image size. |
| `font_size (float, optional)` | The font size of the text. If None, it is scaled to the image size. |
| `font (str)` | The font to use for the text. |
| `pil (bool)` | Whether to use PIL for image plotting. |
| `example (str)` | An example string to display. Useful for indicating the expected format of the output. |
| `img (numpy.ndarray)` | Plot to another image. if not, plot to original image. |
| `labels (bool)` | Whether to plot the label of bounding boxes. |
| `boxes (bool)` | Whether to plot the bounding boxes. |
| `masks (bool)` | Whether to plot the masks. |
| `probs (bool)` | Whether to plot classification probability. |
## Streaming Source `for`-loop

8
docs/tasks/pose.md
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@ -56,19 +56,19 @@ Train a YOLOv8-pose model on the COCO128-pose dataset.
model = YOLO('yolov8n-pose.yaml').load('yolov8n-pose.pt') # build from YAML and transfer weights
# Train the model
model.train(data='coco128-pose.yaml', epochs=100, imgsz=640)
model.train(data='coco8-pose.yaml', epochs=100, imgsz=640)
```
=== "CLI"
```bash
# Build a new model from YAML and start training from scratch
yolo pose train data=coco128-pose.yaml model=yolov8n-pose.yaml epochs=100 imgsz=640
yolo pose train data=coco8-pose.yaml model=yolov8n-pose.yaml epochs=100 imgsz=640
# Start training from a pretrained *.pt model
yolo pose train data=coco128-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640
yolo pose train data=coco8-pose.yaml model=yolov8n-pose.pt epochs=100 imgsz=640
# Build a new model from YAML, transfer pretrained weights to it and start training
yolo pose train data=coco128-pose.yaml model=yolov8n-pose.yaml pretrained=yolov8n-pose.pt epochs=100 imgsz=640
yolo pose train data=coco8-pose.yaml model=yolov8n-pose.yaml pretrained=yolov8n-pose.pt epochs=100 imgsz=640
```
## Val