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Add Hindi हिन्दी and Arabic العربية Docs translations (#6428)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Glenn Jocher 2023-11-18 21:51:47 +01:00 • committed by GitHub
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12
docs/en/models/sam.md
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@ -32,7 +32,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
### SAM prediction example
!!! example "Segment with prompts"
!!! Example "Segment with prompts"
Segment image with given prompts.
@ -54,7 +54,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
model('ultralytics/assets/zidane.jpg', points=[900, 370], labels=[1])
```
!!! example "Segment everything"
!!! Example "Segment everything"
Segment the whole image.
@ -82,7 +82,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
- The logic here is to segment the whole image if you don't pass any prompts(bboxes/points/masks).
!!! example "SAMPredictor example"
!!! Example "SAMPredictor example"
This way you can set image once and run prompts inference multiple times without running image encoder multiple times.
@ -152,7 +152,7 @@ This comparison shows the order-of-magnitude differences in the model sizes and
Tests run on a 2023 Apple M2 Macbook with 16GB of RAM. To reproduce this test:
!!! example ""
!!! Example ""
=== "Python"
```python
@ -187,7 +187,7 @@ Auto-annotation is a key feature of SAM, allowing users to generate a [segmentat
To auto-annotate your dataset with the Ultralytics framework, use the `auto_annotate` function as shown below:
!!! example ""
!!! Example ""
=== "Python"
```python
@ -212,7 +212,7 @@ Auto-annotation with pre-trained models can dramatically cut down the time and e
If you find SAM useful in your research or development work, please consider citing our paper:
!!! note ""
!!! Note ""
=== "BibTeX"