Detects faces within an image that is provided as input
Detects faces within an image that is provided as input.
detect_faces detects the 100 largest faces
in the image. For each face detected, the operation returns face
details. These details include a bounding box of the face, a confidence
value (that the bounding box contains a face), and a fixed set of
attributes such as facial landmarks (for example, coordinates of eye and
mouth), presence of beard, sunglasses, and so on.
The face-detection algorithm is most effective on frontal faces. For non-frontal or obscured faces, the algorithm might not detect the faces or might detect faces with lower confidence.
You pass the input image either as base64-encoded image bytes or as a reference to an image in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.
This is a stateless API operation. That is, the operation does not persist any data.
This operation requires permissions to perform the
rekognition:DetectFaces action.
rekognition_detect_faces(Image, Attributes)
Image |
[required] The input image as base64-encoded bytes or an S3 object. If you use the AWS CLI to call Amazon Rekognition operations, passing base64-encoded image bytes is not supported. If you are using an AWS SDK to call Amazon Rekognition, you might not
need to base64-encode image bytes passed using the |
Attributes |
An array of facial attributes you want to be returned. This can be the
default list of attributes or all attributes. If you don't specify a
value for If you provide both, |
A list with the following syntax:
list(
FaceDetails = list(
list(
BoundingBox = list(
Width = 123.0,
Height = 123.0,
Left = 123.0,
Top = 123.0
),
AgeRange = list(
Low = 123,
High = 123
),
Smile = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
Eyeglasses = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
Sunglasses = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
Gender = list(
Value = "Male"|"Female",
Confidence = 123.0
),
Beard = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
Mustache = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
EyesOpen = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
MouthOpen = list(
Value = TRUE|FALSE,
Confidence = 123.0
),
Emotions = list(
list(
Type = "HAPPY"|"SAD"|"ANGRY"|"CONFUSED"|"DISGUSTED"|"SURPRISED"|"CALM"|"UNKNOWN"|"FEAR",
Confidence = 123.0
)
),
Landmarks = list(
list(
Type = "eyeLeft"|"eyeRight"|"nose"|"mouthLeft"|"mouthRight"|"leftEyeBrowLeft"|"leftEyeBrowRight"|"leftEyeBrowUp"|"rightEyeBrowLeft"|"rightEyeBrowRight"|"rightEyeBrowUp"|"leftEyeLeft"|"leftEyeRight"|"leftEyeUp"|"leftEyeDown"|"rightEyeLeft"|"rightEyeRight"|"rightEyeUp"|"rightEyeDown"|"noseLeft"|"noseRight"|"mouthUp"|"mouthDown"|"leftPupil"|"rightPupil"|"upperJawlineLeft"|"midJawlineLeft"|"chinBottom"|"midJawlineRight"|"upperJawlineRight",
X = 123.0,
Y = 123.0
)
),
Pose = list(
Roll = 123.0,
Yaw = 123.0,
Pitch = 123.0
),
Quality = list(
Brightness = 123.0,
Sharpness = 123.0
),
Confidence = 123.0
)
),
OrientationCorrection = "ROTATE_0"|"ROTATE_90"|"ROTATE_180"|"ROTATE_270"
)svc$detect_faces(
Image = list(
Bytes = raw,
S3Object = list(
Bucket = "string",
Name = "string",
Version = "string"
)
),
Attributes = list(
"DEFAULT"|"ALL"
)
)## Not run:
# This operation detects faces in an image stored in an AWS S3 bucket.
svc$detect_faces(
Image = list(
S3Object = list(
Bucket = "mybucket",
Name = "myphoto"
)
)
)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.