ultralytics 8.0.136 refactor and simplify package (#3748)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@ -88,7 +88,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
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=== "Prompt inference"
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```python
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from ultralytics.vit.sam import Predictor as SAMPredictor
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from ultralytics.models.sam import Predictor as SAMPredictor
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# Create SAMPredictor
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overrides = dict(conf=0.25, task='segment', mode='predict', imgsz=1024, model="mobile_sam.pt")
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@ -108,7 +108,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
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=== "Segment everything"
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```python
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from ultralytics.vit.sam import Predictor as SAMPredictor
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from ultralytics.models.sam import Predictor as SAMPredictor
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# Create SAMPredictor
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overrides = dict(conf=0.25, task='segment', mode='predict', imgsz=1024, model="mobile_sam.pt")
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@ -119,7 +119,7 @@ The Segment Anything Model can be employed for a multitude of downstream tasks t
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```
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- More additional args for `Segment everything` see [`Predictor/generate` Reference](../reference/vit/sam/predict.md).
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- More additional args for `Segment everything` see [`Predictor/generate` Reference](../reference/models/sam/predict.md).
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## Available Models and Supported Tasks
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@ -184,7 +184,7 @@ Auto-annotation is a key feature of SAM, allowing users to generate a [segmentat
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To auto-annotate your dataset with the Ultralytics framework, use the `auto_annotate` function as shown below:
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```python
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from ultralytics.yolo.data.annotator import auto_annotate
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from ultralytics.data.annotator import auto_annotate
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auto_annotate(data="path/to/images", det_model="yolov8x.pt", sam_model='sam_b.pt')
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```
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