🚀 Added
- Ability to select
sv.Detectionsby index, list of indexes or slice. Here is an example illustrating the new selection methods. (#118)
>>> import supervision as sv
>>> detections = sv.Detections(...)
>>> len(detections[0])
1
>>> len(detections[[0, 1]])
2
>>> len(detections[0:2])
2
- Ability to extract masks from YOLOv8 results using
sv.Detections.from_yolov8. Here is an example illustrating how to extract boolean masks from the result of the YOLOv8 model inference. (#101)
>>> import cv2
>>> from ultralytics import YOLO
>>> import supervision as sv
>>> image = cv2.imread(...)
>>> image.shape
(640, 640, 3)
>>> model = YOLO('yolov8s-seg.pt')
>>> result = model(image)[0]
>>> detections = sv.Detections.from_yolov8(result)
>>> detections.mask.shape
(2, 640, 640)- Ability to crop the image using
sv.crop. Here is an example showing how to get a separate crop for each detection insv.Detections. (#122)
>>> import cv2
>>> import supervision as sv
>>> image = cv2.imread(...)
>>> detections = sv.Detections(...)
>>> len(detections)
2
>>> crops = [
... sv.crop(image=image, xyxy=xyxy)
... for xyxy
... in detections.xyxy
... ]
>>> len(crops)
2- Ability to conveniently save multiple images into directory using
sv.ImageSink. An example shows how to save every tenth video frame as a separate image. (#120)
>>> import supervision as sv
>>> with sv.ImageSink(target_dir_path='target/directory/path') as sink:
... for image in sv.get_video_frames_generator(source_path='source_video.mp4', stride=10):
... sink.save_image(image=image)🛠️ Fixed
- Inconvenient handling of
sv.PolygonZonecoordinates. Nowsv.PolygonZoneaccepts coordinates in the form of[[x1, y1], [x2, y2], ...]that can be both integers and floats. (#106)