Annotators¶
Annotators accept detections and apply box or mask visualizations to the detections. Annotators have many available styles.
import supervision as sv
image = ...
detections = sv.Detections(...)
box_annotator = sv.BoxAnnotator()
annotated_frame = box_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
round_box_annotator = sv.RoundBoxAnnotator()
annotated_frame = round_box_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
corner_annotator = sv.BoxCornerAnnotator()
annotated_frame = corner_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
color_annotator = sv.ColorAnnotator()
annotated_frame = color_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
circle_annotator = sv.CircleAnnotator()
annotated_frame = circle_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
dot_annotator = sv.DotAnnotator()
annotated_frame = dot_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
triangle_annotator = sv.TriangleAnnotator()
annotated_frame = triangle_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
ellipse_annotator = sv.EllipseAnnotator()
annotated_frame = ellipse_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
halo_annotator = sv.HaloAnnotator()
annotated_frame = halo_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
percentage_bar_annotator = sv.PercentageBarAnnotator()
annotated_frame = percentage_bar_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
mask_annotator = sv.MaskAnnotator()
annotated_frame = mask_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
polygon_annotator = sv.PolygonAnnotator()
annotated_frame = polygon_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
labels = [
f"{class_name} {confidence:.2f}"
for class_name, confidence
in zip(detections['class_name'], detections.confidence)
]
label_annotator = sv.LabelAnnotator(text_position=sv.Position.CENTER)
annotated_frame = label_annotator.annotate(
scene=image.copy(),
detections=detections,
labels=labels
)
import supervision as sv
image = ...
detections = sv.Detections(...)
labels = [
f"{class_name} {confidence:.2f}"
for class_name, confidence
in zip(detections['class_name'], detections.confidence)
]
rich_label_annotator = sv.RichLabelAnnotator(
font_path="<TTF_FONT_PATH>",
text_position=sv.Position.CENTER
)
annotated_frame = rich_label_annotator.annotate(
scene=image.copy(),
detections=detections,
labels=labels
)
import supervision as sv
image = ...
detections = sv.Detections(...)
icon_paths = [
"<ICON_PATH>"
for _ in detections
]
icon_annotator = sv.IconAnnotator()
annotated_frame = icon_annotator.annotate(
scene=image.copy(),
detections=detections,
icon_path=icon_paths
)
import supervision as sv
image = ...
detections = sv.Detections(...)
blur_annotator = sv.BlurAnnotator()
annotated_frame = blur_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
image = ...
detections = sv.Detections(...)
pixelate_annotator = sv.PixelateAnnotator()
annotated_frame = pixelate_annotator.annotate(
scene=image.copy(),
detections=detections
)
import supervision as sv
from ultralytics import YOLO
model = YOLO('yolov8x.pt')
trace_annotator = sv.TraceAnnotator()
video_info = sv.VideoInfo.from_video_path(video_path='...')
frames_generator = sv.get_video_frames_generator(source_path='...')
tracker = sv.ByteTrack()
with sv.VideoSink(target_path='...', video_info=video_info) as sink:
for frame in frames_generator:
result = model(frame)[0]
detections = sv.Detections.from_ultralytics(result)
detections = tracker.update_with_detections(detections)
annotated_frame = trace_annotator.annotate(
scene=frame.copy(),
detections=detections)
sink.write_frame(frame=annotated_frame)
import supervision as sv
from ultralytics import YOLO
model = YOLO('yolov8x.pt')
heat_map_annotator = sv.HeatMapAnnotator()
video_info = sv.VideoInfo.from_video_path(video_path='...')
frames_generator = sv.get_video_frames_generator(source_path='...')
with sv.VideoSink(target_path='...', video_info=video_info) as sink:
for frame in frames_generator:
result = model(frame)[0]
detections = sv.Detections.from_ultralytics(result)
annotated_frame = heat_map_annotator.annotate(
scene=frame.copy(),
detections=detections)
sink.write_frame(frame=annotated_frame)
Try Supervision Annotators on your own image
Visualize annotators on images with COCO classes such as people, vehicles, animals, household items.
Bases: BaseAnnotator
A class for drawing bounding boxes on an image using provided detections.
Source code in supervision/annotators/core.py
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the bounding box lines. |
2
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with bounding boxes based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where bounding boxes will be drawn. |
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing bounding boxes with round edges on an image using provided detections.
Source code in supervision/annotators/core.py
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112 2113 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128 2129 2130 2131 2132 2133 2134 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, color_lookup=ColorLookup.CLASS, roundness=0.6)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the bounding box lines. |
2
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
roundness |
float
|
Percent of roundness for edges of bounding box. Value must be float 0 < roundness <= 1.0 By default roundness percent is calculated based on smaller side length (width or height). |
0.6
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with bounding boxes with rounded edges based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where rounded bounding boxes will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
2037 2038 2039 2040 2041 2042 2043 2044 2045 2046 2047 2048 2049 2050 2051 2052 2053 2054 2055 2056 2057 2058 2059 2060 2061 2062 2063 2064 2065 2066 2067 2068 2069 2070 2071 2072 2073 2074 2075 2076 2077 2078 2079 2080 2081 2082 2083 2084 2085 2086 2087 2088 2089 2090 2091 2092 2093 2094 2095 2096 2097 2098 2099 2100 2101 2102 2103 2104 2105 2106 2107 2108 2109 2110 2111 2112 2113 2114 2115 2116 2117 2118 2119 2120 2121 2122 2123 2124 2125 2126 2127 2128 2129 2130 2131 2132 2133 2134 |
|
Bases: BaseAnnotator
A class for drawing box corners on an image using provided detections.
Source code in supervision/annotators/core.py
756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=4, corner_length=15, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the corner lines. |
4
|
corner_length |
int
|
Length of each corner line. |
15
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with box corners based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where box corners will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing oriented bounding boxes on an image using provided detections.
Source code in supervision/annotators/core.py
205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the bounding box lines. |
2
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with oriented bounding boxes based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where bounding boxes will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
import cv2
import supervision as sv
from ultralytics import YOLO
image = cv2.imread(<SOURCE_IMAGE_PATH>)
model = YOLO("yolov8n-obb.pt")
result = model(image)[0]
detections = sv.Detections.from_ultralytics(result)
oriented_box_annotator = sv.OrientedBoxAnnotator()
annotated_frame = oriented_box_annotator.annotate(
scene=image.copy(),
detections=detections
)
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing box masks on an image using provided detections.
Source code in supervision/annotators/core.py
471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, opacity=0.5, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
opacity |
float
|
Opacity of the overlay mask. Must be between |
0.5
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with box masks based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where bounding boxes will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing circle on an image using provided detections.
Source code in supervision/annotators/core.py
847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the circle line. |
2
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with circles based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where box corners will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing dots on an image at specific coordinates based on provided detections.
Source code in supervision/annotators/core.py
935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, radius=4, position=Position.CENTER, color_lookup=ColorLookup.CLASS, outline_thickness=0, outline_color=Color.BLACK)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
radius |
int
|
Radius of the drawn dots. |
4
|
position |
Position
|
The anchor position for placing the dot. |
CENTER
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
outline_thickness |
int
|
Thickness of the outline of the dot. |
0
|
outline_color |
Union[Color, ColorPalette]
|
The color or color palette to use for outline. It is activated by setting outline_thickness to a value greater than 0. |
BLACK
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with dots based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where dots will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 |
|
Bases: BaseAnnotator
A class for drawing triangle markers on an image at specific coordinates based on provided detections.
Source code in supervision/annotators/core.py
1887 1888 1889 1890 1891 1892 1893 1894 1895 1896 1897 1898 1899 1900 1901 1902 1903 1904 1905 1906 1907 1908 1909 1910 1911 1912 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, base=10, height=10, position=Position.TOP_CENTER, color_lookup=ColorLookup.CLASS, outline_thickness=0, outline_color=Color.BLACK)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
base |
int
|
The base width of the triangle. |
10
|
height |
int
|
The height of the triangle. |
10
|
position |
Position
|
The anchor position for placing the triangle. |
TOP_CENTER
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
outline_thickness |
int
|
Thickness of the outline of the triangle. |
0
|
outline_color |
Union[Color, ColorPalette]
|
The color or color palette to use for outline. It is activated by setting outline_thickness to a value greater than 0. |
BLACK
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with triangles based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where triangles will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 |
|
Bases: BaseAnnotator
A class for drawing ellipses on an image using provided detections.
Source code in supervision/annotators/core.py
661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, start_angle=-45, end_angle=235, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the ellipse lines. |
2
|
start_angle |
int
|
Starting angle of the ellipse. |
-45
|
end_angle |
int
|
Ending angle of the ellipse. |
235
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with ellipses based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where ellipses will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing Halos on an image using provided detections.
Warning
This annotator uses sv.Detections.mask
.
Source code in supervision/annotators/core.py
559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, opacity=0.8, kernel_size=40, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
opacity |
float
|
Opacity of the overlay mask. Must be between |
0.8
|
kernel_size |
int
|
The size of the average pooling kernel used for creating the halo. |
40
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with halos based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where masks will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing percentage bars on an image using provided detections.
Source code in supervision/annotators/core.py
2137 2138 2139 2140 2141 2142 2143 2144 2145 2146 2147 2148 2149 2150 2151 2152 2153 2154 2155 2156 2157 2158 2159 2160 2161 2162 2163 2164 2165 2166 2167 2168 2169 2170 2171 2172 2173 2174 2175 2176 2177 2178 2179 2180 2181 2182 2183 2184 2185 2186 2187 2188 2189 2190 2191 2192 2193 2194 2195 2196 2197 2198 2199 2200 2201 2202 2203 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 2219 2220 2221 2222 2223 2224 2225 2226 2227 2228 2229 2230 2231 2232 2233 2234 2235 2236 2237 2238 2239 2240 2241 2242 2243 2244 2245 2246 2247 2248 2249 2250 2251 2252 2253 2254 2255 2256 2257 2258 2259 2260 2261 2262 2263 2264 2265 2266 2267 2268 2269 2270 2271 2272 2273 2274 2275 2276 2277 2278 2279 2280 2281 2282 2283 2284 2285 2286 2287 2288 2289 2290 2291 2292 2293 2294 2295 2296 2297 2298 2299 2300 2301 2302 2303 2304 2305 2306 2307 2308 2309 2310 2311 2312 2313 2314 2315 2316 2317 2318 2319 2320 |
|
Functions¶
__init__(height=16, width=80, color=ColorPalette.DEFAULT, border_color=Color.BLACK, position=Position.TOP_CENTER, color_lookup=ColorLookup.CLASS, border_thickness=None)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
height |
int
|
The height in pixels of the percentage bar. |
16
|
width |
int
|
The width in pixels of the percentage bar. |
80
|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
border_color |
Color
|
The color of the border lines. |
BLACK
|
position |
Position
|
The anchor position of drawing the percentage bar. |
TOP_CENTER
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
border_thickness |
Optional[int]
|
The thickness of the border lines. |
None
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None, custom_values=None)
¶
Annotates the given scene with percentage bars based on the provided detections. The percentage bars visually represent the confidence or custom values associated with each detection.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where percentage bars will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
custom_values |
Optional[ndarray]
|
Custom values array to use instead of the default detection confidences. This array should have the same length as the number of detections and contain a value between 0 and 1 (inclusive) for each detection, representing the percentage to be displayed. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
2174 2175 2176 2177 2178 2179 2180 2181 2182 2183 2184 2185 2186 2187 2188 2189 2190 2191 2192 2193 2194 2195 2196 2197 2198 2199 2200 2201 2202 2203 2204 2205 2206 2207 2208 2209 2210 2211 2212 2213 2214 2215 2216 2217 2218 2219 2220 2221 2222 2223 2224 2225 2226 2227 2228 2229 2230 2231 2232 2233 2234 2235 2236 2237 2238 2239 2240 2241 2242 2243 2244 2245 2246 2247 2248 2249 2250 2251 2252 2253 2254 2255 2256 2257 2258 2259 2260 2261 2262 2263 2264 2265 |
|
Bases: BaseAnnotator
A class for drawing heatmaps on an image based on provided detections. Heat accumulates over time and is drawn as a semi-transparent overlay of blurred circles.
Source code in supervision/annotators/core.py
1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 |
|
Functions¶
__init__(position=Position.BOTTOM_CENTER, opacity=0.2, radius=40, kernel_size=25, top_hue=0, low_hue=125)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
position |
Position
|
The position of the heatmap. Defaults to
|
BOTTOM_CENTER
|
opacity |
float
|
Opacity of the overlay mask, between 0 and 1. |
0.2
|
radius |
int
|
Radius of the heat circle. |
40
|
kernel_size |
int
|
Kernel size for blurring the heatmap. |
25
|
top_hue |
int
|
Hue at the top of the heatmap. Defaults to 0 (red). |
0
|
low_hue |
int
|
Hue at the bottom of the heatmap. Defaults to 125 (blue). |
125
|
Source code in supervision/annotators/core.py
annotate(scene, detections)
¶
Annotates the scene with a heatmap based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where the heatmap will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
import supervision as sv
from ultralytics import YOLO
model = YOLO('yolov8x.pt')
heat_map_annotator = sv.HeatMapAnnotator()
video_info = sv.VideoInfo.from_video_path(video_path='...')
frames_generator = sv.get_video_frames_generator(source_path='...')
with sv.VideoSink(target_path='...', video_info=video_info) as sink:
for frame in frames_generator:
result = model(frame)[0]
detections = sv.Detections.from_ultralytics(result)
annotated_frame = heat_map_annotator.annotate(
scene=frame.copy(),
detections=detections)
sink.write_frame(frame=annotated_frame)
Source code in supervision/annotators/core.py
1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 |
|
Bases: BaseAnnotator
A class for drawing masks on an image using provided detections.
Warning
This annotator uses sv.Detections.mask
.
Source code in supervision/annotators/core.py
290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, opacity=0.5, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
opacity |
float
|
Opacity of the overlay mask. Must be between |
0.5
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with masks based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where masks will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for drawing polygons on an image using provided detections.
Warning
This annotator uses sv.Detections.mask
.
Source code in supervision/annotators/core.py
380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, thickness=2, color_lookup=ColorLookup.CLASS)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating detections. |
DEFAULT
|
thickness |
int
|
Thickness of the polygon lines. |
2
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
Source code in supervision/annotators/core.py
annotate(scene, detections, custom_color_lookup=None)
¶
Annotates the given scene with polygons based on the provided detections.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
scene |
ImageType
|
The image where polygons will be drawn.
|
required |
detections |
Detections
|
Object detections to annotate. |
required |
custom_color_lookup |
Optional[ndarray]
|
Custom color lookup array. Allows to override the default color mapping strategy. |
None
|
Returns:
Type | Description |
---|---|
ImageType
|
The annotated image, matching the type of |
Example
Source code in supervision/annotators/core.py
Bases: BaseAnnotator
A class for annotating labels on an image using provided detections.
Source code in supervision/annotators/core.py
1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 |
|
Functions¶
__init__(color=ColorPalette.DEFAULT, text_color=Color.WHITE, text_scale=0.5, text_thickness=1, text_padding=10, text_position=Position.TOP_LEFT, color_lookup=ColorLookup.CLASS, border_radius=0)
¶
Parameters:
Name | Type | Description | Default |
---|---|---|---|
color |
Union[Color, ColorPalette]
|
The color or color palette to use for annotating the text background. |
DEFAULT
|
text_color |
Union[Color, ColorPalette]
|
The color or color palette to use for the text. |
WHITE
|
text_scale |
float
|
Font scale for the text. |
0.5
|
text_thickness |
int
|
Thickness of the text characters. |
1
|
text_padding |
int
|
Padding around the text within its background box. |
10
|
text_position |
Position
|
Position of the text relative to the detection.
Possible values are defined in the |
TOP_LEFT
|
color_lookup |
ColorLookup
|
Strategy for mapping colors to annotations.
Options are |
CLASS
|
border_radius |
int
|
The radius to apply round edges. If the selected value is higher than the lower dimension, width or height, is clipped. |
0
|