29 lines
942 B
Python
Executable File
29 lines
942 B
Python
Executable File
from inference import get_model
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import supervision as sv
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import cv2
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# define the image url to use for inference
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image_file = "taylor-swift-album-1989.jpeg"
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image = cv2.imread(image_file)
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# load a pre-trained yolov8n model
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model = get_model(model_id="taylor-swift-records/3")
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# run inference on our chosen image, image can be a url, a numpy array, a PIL image, etc.
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results = model.infer(image)[0]
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# load the results into the supervision Detections api
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detections = sv.Detections.from_inference(results)
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# create supervision annotators
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bounding_box_annotator = sv.BoundingBoxAnnotator()
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label_annotator = sv.LabelAnnotator()
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# annotate the image with our inference results
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annotated_image = bounding_box_annotator.annotate(
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scene=image, detections=detections)
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annotated_image = label_annotator.annotate(
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scene=annotated_image, detections=detections)
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# display the image
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sv.plot_image(annotated_image) |