📅 Timeline
The supervision-0.21.0 release is around the corner. Here is the timeline:
5 Jun 2024 08:00 PM CEST (UTC +2) / 5 Jun 2024 11:00 AM PDT (UTC -7)- mergedevelopintomain- closing listsupervision-0.21.0features6 Jun 2024 11:00 AM CEST (UTC +2) / 6 Jun 2024 02:00 AM PDT (UTC -7)- releasesupervision-0.21.0
🪵 Changelog
🚀 Added
sv.Detections.with_nmmto perform non-maximum merging on the current set of object detections. (#500)
sv.Detections.from_lmmallowing to parse Large Multimodal Model (LMM) text result intosv.Detectionsobject. For nowfrom_lmmsupports only PaliGemma result parsing. (#1221)
import supervision as sv
paligemma_result = "<loc0256><loc0256><loc0768><loc0768> cat"
detections = sv.Detections.from_lmm(
sv.LMM.PALIGEMMA,
paligemma_result,
resolution_wh=(1000, 1000),
classes=['cat', 'dog']
)
detections.xyxy
# array([[250., 250., 750., 750.]])
detections.class_id
# array([0])sv.VertexLabelAnnotatorallowing to annotate every vertex of a keypoint skeleton with custom text and color. (#1236)
import supervision as sv
image = ...
key_points = sv.KeyPoints(...)
LABELS = [
"nose", "left eye", "right eye", "left ear",
"right ear", "left shoulder", "right shoulder", "left elbow",
"right elbow", "left wrist", "right wrist", "left hip",
"right hip", "left knee", "right knee", "left ankle",
"right ankle"
]
COLORS = [
"#FF6347", "#FF6347", "#FF6347", "#FF6347",
"#FF6347", "#FF1493", "#00FF00", "#FF1493",
"#00FF00", "#FF1493", "#00FF00", "#FFD700",
"#00BFFF", "#FFD700", "#00BFFF", "#FFD700",
"#00BFFF"
]
COLORS = [sv.Color.from_hex(color_hex=c) for c in COLORS]
vertex_label_annotator = sv.VertexLabelAnnotator(
color=COLORS,
text_color=sv.Color.BLACK,
border_radius=5
)
annotated_frame = vertex_label_annotator.annotate(
scene=image.copy(),
key_points=key_points,
labels=labels
)
-
sv.KeyPoints.from_inferenceandsv.KeyPoints.from_yolo_nasallowing to createsv.KeyPointsfrom Inference and YOLO-NAS result. (#1147 and #1138) -
sv.mask_to_rleandsv.rle_to_maskallowing for easy conversion between mask and rle formats. (#1163)
🌱 Changed
-
sv.InferenceSlicerallowing to select overlap filtering strategy (NONE,NON_MAX_SUPPRESSIONandNON_MAX_MERGE). (#1236) -
sv.InferenceSliceradding instance segmentation model support. (#1178)
import cv2
import numpy as np
import supervision as sv
from inference import get_model
model = get_model(model_id="yolov8x-seg-640")
image = cv2.imread(<SOURCE_IMAGE_PATH>)
def callback(image_slice: np.ndarray) -> sv.Detections:
results = model.infer(image_slice)[0]
return sv.Detections.from_inference(results)
slicer = sv.InferenceSlicer(callback = callback)
detections = slicer(image)
mask_annotator = sv.MaskAnnotator()
label_annotator = sv.LabelAnnotator()
annotated_image = mask_annotator.annotate(
scene=image, detections=detections)
annotated_image = label_annotator.annotate(
scene=annotated_image, detections=detections)
sv.LineZonemaking it 10-20 times faster, depending on the use case. (#1228)
sv.DetectionDataset.from_cocoandsv.DetectionDataset.as_cocoadding support for run-length encoding (RLE) mask format. (#1163)
🏆 Contributors
@onuralpszr (Onuralp SEZER), @LinasKo (Linas Kondrackis), @rolson24 (Raif Olson), @mario-dg (Mario da Graca), @xaristeidou (Christoforos Aristeidou), @ManzarIMalik (Manzar Iqbal Malik), @tc360950 (Tomasz Cąkała), @emSko, @SkalskiP (Piotr Skalski)