Minor fix in docs for python admonition and code blocks (#16646)
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4 changed files with 23 additions and 23 deletions
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@ -141,7 +141,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
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=== "Black Background Pixels"
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=== "Black Background Pixels"
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```py
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```python
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# Create 3-channel mask
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# Create 3-channel mask
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mask3ch = cv2.cvtColor(b_mask, cv2.COLOR_GRAY2BGR)
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mask3ch = cv2.cvtColor(b_mask, cv2.COLOR_GRAY2BGR)
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@ -192,7 +192,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
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=== "Transparent Background Pixels"
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=== "Transparent Background Pixels"
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```py
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```python
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# Isolate object with transparent background (when saved as PNG)
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# Isolate object with transparent background (when saved as PNG)
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isolated = np.dstack([img, b_mask])
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isolated = np.dstack([img, b_mask])
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```
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```
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@ -248,7 +248,7 @@ After performing the [Segment Task](../tasks/segment.md), it's sometimes desirab
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??? example "Example Final Step"
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??? example "Example Final Step"
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```py
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```python
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# Save isolated object to file
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# Save isolated object to file
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_ = cv2.imwrite(f"{img_name}_{label}-{ci}.png", iso_crop)
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_ = cv2.imwrite(f"{img_name}_{label}-{ci}.png", iso_crop)
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```
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```
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@ -48,7 +48,7 @@ The dataset YAML is the same standard YOLOv5 and YOLOv8 YAML format.
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After zipping your dataset, you should [validate it](https://docs.ultralytics.com/reference/hub/__init__/#ultralytics.hub.check_dataset) before uploading it to [Ultralytics HUB](https://www.ultralytics.com/hub). [Ultralytics HUB](https://www.ultralytics.com/hub) conducts the dataset validation check post-upload, so by ensuring your dataset is correctly formatted and error-free ahead of time, you can forestall any setbacks due to dataset rejection.
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After zipping your dataset, you should [validate it](https://docs.ultralytics.com/reference/hub/__init__/#ultralytics.hub.check_dataset) before uploading it to [Ultralytics HUB](https://www.ultralytics.com/hub). [Ultralytics HUB](https://www.ultralytics.com/hub) conducts the dataset validation check post-upload, so by ensuring your dataset is correctly formatted and error-free ahead of time, you can forestall any setbacks due to dataset rejection.
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```py
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```python
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from ultralytics.hub import check_dataset
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from ultralytics.hub import check_dataset
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check_dataset("path/to/dataset.zip", task="detect")
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check_dataset("path/to/dataset.zip", task="detect")
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@ -380,7 +380,7 @@ Expand sections below for information on how these models were exported and test
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See [export mode](../modes/export.md) for details regarding export configuration arguments.
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See [export mode](../modes/export.md) for details regarding export configuration arguments.
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```py
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```python
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from ultralytics import YOLO
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from ultralytics import YOLO
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model = YOLO("yolov8n.pt")
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model = YOLO("yolov8n.pt")
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@ -401,7 +401,7 @@ Expand sections below for information on how these models were exported and test
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See [predict mode](../modes/predict.md) for additional information.
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See [predict mode](../modes/predict.md) for additional information.
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```py
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```python
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import cv2
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import cv2
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from ultralytics import YOLO
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from ultralytics import YOLO
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@ -421,7 +421,7 @@ Expand sections below for information on how these models were exported and test
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See [`val` mode](../modes/val.md) to learn more about validation configuration arguments.
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See [`val` mode](../modes/val.md) to learn more about validation configuration arguments.
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```py
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```python
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from ultralytics import YOLO
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from ultralytics import YOLO
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model = YOLO("yolov8n.engine")
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model = YOLO("yolov8n.engine")
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