fix(pre_commit): 🎨 auto format pre-commit hooks
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@ -213,8 +213,8 @@ Finally, we can annotate the image with the predictions. Since we are working wi
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## Display Custom Labels
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By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator)
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will label each detection with its `class_name` (if possible) or `class_id`. You can
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By default, [`sv.LabelAnnotator`](annotators/#supervision.annotators.core.LabelAnnotator)
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will label each detection with its `class_name` (if possible) or `class_id`. You can
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override this behavior by passing a list of custom `labels` to the `annotate` method.
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=== "Inference"
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@ -284,16 +284,16 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
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image = Image.open(<PATH TO IMAGE>)
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inputs = processor(images=image, return_tensors="pt")
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with torch.no_grad():
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outputs = model(**inputs)
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width, height = image.size
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target_size = torch.tensor([[height, width]])
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results = processor.post_process_object_detection(
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outputs=outputs, target_sizes=target_size)[0]
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detections = sv.Detections.from_transformers(results)
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bounding_box_annotator = sv.BoundingBoxAnnotator()
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label_annotator = sv.LabelAnnotator()
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@ -313,10 +313,10 @@ override this behavior by passing a list of custom `labels` to the `annotate` me
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## Annotate Image with Segmentations
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If you are running the segmentation model
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[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator)
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is a drop-in replacement for
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[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator)
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If you are running the segmentation model
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[`sv.MaskAnnotator`](annotators/#supervision.annotators.core.MaskAnnotator)
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is a drop-in replacement for
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[`sv.BoundingBoxAnnotator`](annotators/#supervision.annotators.core.BoundingBoxAnnotator)
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that will allow you to draw masks instead of boxes.
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=== "Inference"
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@ -361,4 +361,4 @@ that will allow you to draw masks instead of boxes.
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scene=annotated_image, detections=detections)
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```
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