2018/11/21 - Amazon Rekognition - 8 updated api methods
Changes This release updates the DetectFaces and IndexFaces operation. When the Attributes input parameter is set to ALL, the face location landmarks includes 5 new landmarks: upperJawlineLeft, midJawlineLeft, chinBottom, midJawlineRight, upperJawlineRight.
{'FaceMatches': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}},
'UnmatchedFaces': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}
Compares a face in the source input image with each of the 100 largest faces detected in the target input image.
Note
If the source image contains multiple faces, the service detects the largest face and compares it with each face detected in the target image.
You pass the input and target images either as base64-encoded image bytes or as references to images in an Amazon S3 bucket. If you use the AWS CLI to call Amazon Rekognition operations, passing image bytes isn't supported. The image must be formatted as a PNG or JPEG file.
In response, the operation returns an array of face matches ordered by similarity score in descending order. For each face match, the response provides a bounding box of the face, facial landmarks, pose details (pitch, role, and yaw), quality (brightness and sharpness), and confidence value (indicating the level of confidence that the bounding box contains a face). The response also provides a similarity score, which indicates how closely the faces match.
Note
By default, only faces with a similarity score of greater than or equal to 80% are returned in the response. You can change this value by specifying the SimilarityThreshold parameter.
CompareFaces also returns an array of faces that don't match the source image. For each face, it returns a bounding box, confidence value, landmarks, pose details, and quality. The response also returns information about the face in the source image, including the bounding box of the face and confidence value.
If the image doesn't contain Exif metadata, CompareFaces returns orientation information for the source and target images. Use these values to display the images with the correct image orientation.
If no faces are detected in the source or target images, CompareFaces returns an InvalidParameterException error.
Note
This is a stateless API operation. That is, data returned by this operation doesn't persist.
For an example, see Comparing Faces in Images in the Amazon Rekognition Developer Guide.
This operation requires permissions to perform the rekognition:CompareFaces action.
See also: AWS API Documentation
Request Syntax
client.compare_faces(
SourceImage={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
TargetImage={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
SimilarityThreshold=...
)
dict
[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.
Bytes (bytes) --
Blob of image bytes up to 5 MBs.
S3Object (dict) --
Identifies an S3 object as the image source.
Bucket (string) --
Name of the S3 bucket.
Name (string) --
S3 object key name.
Version (string) --
If the bucket is versioning enabled, you can specify the object version.
dict
[REQUIRED]
The target 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.
Bytes (bytes) --
Blob of image bytes up to 5 MBs.
S3Object (dict) --
Identifies an S3 object as the image source.
Bucket (string) --
Name of the S3 bucket.
Name (string) --
S3 object key name.
Version (string) --
If the bucket is versioning enabled, you can specify the object version.
float
The minimum level of confidence in the face matches that a match must meet to be included in the FaceMatches array.
dict
Response Syntax
{
'SourceImageFace': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...
},
'FaceMatches': [
{
'Similarity': ...,
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...,
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
}
}
},
],
'UnmatchedFaces': [
{
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...,
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
}
},
],
'SourceImageOrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270',
'TargetImageOrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270'
}
Response Structure
(dict) --
SourceImageFace (dict) --
The face in the source image that was used for comparison.
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
Confidence level that the selected bounding box contains a face.
FaceMatches (list) --
An array of faces in the target image that match the source image face. Each CompareFacesMatch object provides the bounding box, the confidence level that the bounding box contains a face, and the similarity score for the face in the bounding box and the face in the source image.
(dict) --
Provides information about a face in a target image that matches the source image face analyzed by CompareFaces . The Face property contains the bounding box of the face in the target image. The Similarity property is the confidence that the source image face matches the face in the bounding box.
Similarity (float) --
Level of confidence that the faces match.
Face (dict) --
Provides face metadata (bounding box and confidence that the bounding box actually contains a face).
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
Level of confidence that what the bounding box contains is a face.
Landmarks (list) --
An array of facial landmarks.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies face image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
UnmatchedFaces (list) --
An array of faces in the target image that did not match the source image face.
(dict) --
Provides face metadata for target image faces that are analyzed by CompareFaces and RecognizeCelebrities .
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
Level of confidence that what the bounding box contains is a face.
Landmarks (list) --
An array of facial landmarks.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies face image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
SourceImageOrientationCorrection (string) --
The value of SourceImageOrientationCorrection is always null.
If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.
Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.
TargetImageOrientationCorrection (string) --
The value of TargetImageOrientationCorrection is always null.
If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.
Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.
{'FaceDetails': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}
Detects faces within an image that is provided as input.
DetectFaces 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), gender, 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 to call Amazon Rekognition operations, passing image bytes is not supported. The image must be either a PNG or JPEG formatted file.
Note
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.
See also: AWS API Documentation
Request Syntax
client.detect_faces(
Image={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
Attributes=[
'DEFAULT'|'ALL',
]
)
dict
[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.
Bytes (bytes) --
Blob of image bytes up to 5 MBs.
S3Object (dict) --
Identifies an S3 object as the image source.
Bucket (string) --
Name of the S3 bucket.
Name (string) --
S3 object key name.
Version (string) --
If the bucket is versioning enabled, you can specify the object version.
list
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 Attributes or if you specify ["DEFAULT"] , the API returns the following subset of facial attributes: BoundingBox , Confidence , Pose , Quality , and Landmarks . If you provide ["ALL"] , all facial attributes are returned, but the operation takes longer to complete.
If you provide both, ["ALL", "DEFAULT"] , the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).
(string) --
dict
Response Syntax
{
'FaceDetails': [
{
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
},
],
'OrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270'
}
Response Structure
(dict) --
FaceDetails (list) --
Details of each face found in the image.
(dict) --
Structure containing attributes of the face that the algorithm detected.
A FaceDetail object contains either the default facial attributes or all facial attributes. The default attributes are BoundingBox , Confidence , Landmarks , Pose , and Quality .
is the only Amazon Rekognition Video stored video operation that can return a FaceDetail object with all attributes. To specify which attributes to return, use the FaceAttributes input parameter for . The following Amazon Rekognition Video operations return only the default attributes. The corresponding Start operations don't have a FaceAttributes input parameter.
GetCelebrityRecognition
GetPersonTracking
GetFaceSearch
The Amazon Rekognition Image and operations can return all facial attributes. To specify which attributes to return, use the Attributes input parameter for DetectFaces . For IndexFaces , use the DetectAttributes input parameter.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
OrientationCorrection (string) --
The value of OrientationCorrection is always null.
If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction. The bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.
Amazon Rekognition doesn’t perform image correction for images in .png format and .jpeg images without orientation information in the image Exif metadata. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.
{'Celebrities': {'Celebrity': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}}}
Gets the celebrity recognition results for a Amazon Rekognition Video analysis started by .
Celebrity recognition in a video is an asynchronous operation. Analysis is started by a call to which returns a job identifier (JobId ). When the celebrity recognition operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartCelebrityRecognition . To get the results of the celebrity recognition analysis, first check that the status value published to the Amazon SNS topic is SUCCEEDED . If so, call GetCelebrityDetection and pass the job identifier (JobId ) from the initial call to StartCelebrityDetection .
For more information, see Working With Stored Videos in the Amazon Rekognition Developer Guide.
GetCelebrityRecognition returns detected celebrities and the time(s) they are detected in an array (Celebrities ) of objects. Each CelebrityRecognition contains information about the celebrity in a object and the time, Timestamp , the celebrity was detected.
Note
GetCelebrityRecognition only returns the default facial attributes (BoundingBox , Confidence , Landmarks , Pose , and Quality ). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.
By default, the Celebrities array is sorted by time (milliseconds from the start of the video). You can also sort the array by celebrity by specifying the value ID in the SortBy input parameter.
The CelebrityDetail object includes the celebrity identifer and additional information urls. If you don't store the additional information urls, you can get them later by calling with the celebrity identifer.
No information is returned for faces not recognized as celebrities.
Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults , the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetCelebrityDetection and populate the NextToken request parameter with the token value returned from the previous call to GetCelebrityRecognition .
See also: AWS API Documentation
Request Syntax
client.get_celebrity_recognition(
JobId='string',
MaxResults=123,
NextToken='string',
SortBy='ID'|'TIMESTAMP'
)
string
[REQUIRED]
Job identifier for the required celebrity recognition analysis. You can get the job identifer from a call to StartCelebrityRecognition .
integer
Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.
string
If the previous response was incomplete (because there is more recognized celebrities to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of celebrities.
string
Sort to use for celebrities returned in Celebrities field. Specify ID to sort by the celebrity identifier, specify TIMESTAMP to sort by the time the celebrity was recognized.
dict
Response Syntax
{
'JobStatus': 'IN_PROGRESS'|'SUCCEEDED'|'FAILED',
'StatusMessage': 'string',
'VideoMetadata': {
'Codec': 'string',
'DurationMillis': 123,
'Format': 'string',
'FrameRate': ...,
'FrameHeight': 123,
'FrameWidth': 123
},
'NextToken': 'string',
'Celebrities': [
{
'Timestamp': 123,
'Celebrity': {
'Urls': [
'string',
],
'Name': 'string',
'Id': 'string',
'Confidence': ...,
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
}
},
]
}
Response Structure
(dict) --
JobStatus (string) --
The current status of the celebrity recognition job.
StatusMessage (string) --
If the job fails, StatusMessage provides a descriptive error message.
VideoMetadata (dict) --
Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.
Codec (string) --
Type of compression used in the analyzed video.
DurationMillis (integer) --
Length of the video in milliseconds.
Format (string) --
Format of the analyzed video. Possible values are MP4, MOV and AVI.
FrameRate (float) --
Number of frames per second in the video.
FrameHeight (integer) --
Vertical pixel dimension of the video.
FrameWidth (integer) --
Horizontal pixel dimension of the video.
NextToken (string) --
If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of celebrities.
Celebrities (list) --
Array of celebrities recognized in the video.
(dict) --
Information about a detected celebrity and the time the celebrity was detected in a stored video. For more information, see GetCelebrityRecognition in the Amazon Rekognition Developer Guide.
Timestamp (integer) --
The time, in milliseconds from the start of the video, that the celebrity was recognized.
Celebrity (dict) --
Information about a recognized celebrity.
Urls (list) --
An array of URLs pointing to additional celebrity information.
(string) --
Name (string) --
The name of the celebrity.
Id (string) --
The unique identifier for the celebrity.
Confidence (float) --
The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.
BoundingBox (dict) --
Bounding box around the body of a celebrity.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Face (dict) --
Face details for the recognized celebrity.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
{'Faces': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}}
Gets face detection results for a Amazon Rekognition Video analysis started by .
Face detection with Amazon Rekognition Video is an asynchronous operation. You start face detection by calling which returns a job identifier (JobId ). When the face detection operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceDetection . To get the results of the face detection operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED . If so, call and pass the job identifier (JobId ) from the initial call to StartFaceDetection .
GetFaceDetection returns an array of detected faces (Faces ) sorted by the time the faces were detected.
Use MaxResults parameter to limit the number of labels returned. If there are more results than specified in MaxResults , the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetFaceDetection and populate the NextToken request parameter with the token value returned from the previous call to GetFaceDetection .
See also: AWS API Documentation
Request Syntax
client.get_face_detection(
JobId='string',
MaxResults=123,
NextToken='string'
)
string
[REQUIRED]
Unique identifier for the face detection job. The JobId is returned from StartFaceDetection .
integer
Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.
string
If the previous response was incomplete (because there are more faces to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of faces.
dict
Response Syntax
{
'JobStatus': 'IN_PROGRESS'|'SUCCEEDED'|'FAILED',
'StatusMessage': 'string',
'VideoMetadata': {
'Codec': 'string',
'DurationMillis': 123,
'Format': 'string',
'FrameRate': ...,
'FrameHeight': 123,
'FrameWidth': 123
},
'NextToken': 'string',
'Faces': [
{
'Timestamp': 123,
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
},
]
}
Response Structure
(dict) --
JobStatus (string) --
The current status of the face detection job.
StatusMessage (string) --
If the job fails, StatusMessage provides a descriptive error message.
VideoMetadata (dict) --
Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition video operation.
Codec (string) --
Type of compression used in the analyzed video.
DurationMillis (integer) --
Length of the video in milliseconds.
Format (string) --
Format of the analyzed video. Possible values are MP4, MOV and AVI.
FrameRate (float) --
Number of frames per second in the video.
FrameHeight (integer) --
Vertical pixel dimension of the video.
FrameWidth (integer) --
Horizontal pixel dimension of the video.
NextToken (string) --
If the response is truncated, Amazon Rekognition returns this token that you can use in the subsequent request to retrieve the next set of faces.
Faces (list) --
An array of faces detected in the video. Each element contains a detected face's details and the time, in milliseconds from the start of the video, the face was detected.
(dict) --
Information about a face detected in a video analysis request and the time the face was detected in the video.
Timestamp (integer) --
Time, in milliseconds from the start of the video, that the face was detected.
Face (dict) --
The face properties for the detected face.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
{'Persons': {'Person': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}}}
Gets the face search results for Amazon Rekognition Video face search started by . The search returns faces in a collection that match the faces of persons detected in a video. It also includes the time(s) that faces are matched in the video.
Face search in a video is an asynchronous operation. You start face search by calling to which returns a job identifier (JobId ). When the search operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartFaceSearch . To get the search results, first check that the status value published to the Amazon SNS topic is SUCCEEDED . If so, call GetFaceSearch and pass the job identifier (JobId ) from the initial call to StartFaceSearch .
For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.
The search results are retured in an array, Persons , of objects. Each``PersonMatch`` element contains details about the matching faces in the input collection, person information (facial attributes, bounding boxes, and person identifer) for the matched person, and the time the person was matched in the video.
Note
GetFaceSearch only returns the default facial attributes (BoundingBox , Confidence , Landmarks , Pose , and Quality ). The other facial attributes listed in the Face object of the following response syntax are not returned. For more information, see FaceDetail in the Amazon Rekognition Developer Guide.
By default, the Persons array is sorted by the time, in milliseconds from the start of the video, persons are matched. You can also sort by persons by specifying INDEX for the SORTBY input parameter.
See also: AWS API Documentation
Request Syntax
client.get_face_search(
JobId='string',
MaxResults=123,
NextToken='string',
SortBy='INDEX'|'TIMESTAMP'
)
string
[REQUIRED]
The job identifer for the search request. You get the job identifier from an initial call to StartFaceSearch .
integer
Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.
string
If the previous response was incomplete (because there is more search results to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of search results.
string
Sort to use for grouping faces in the response. Use TIMESTAMP to group faces by the time that they are recognized. Use INDEX to sort by recognized faces.
dict
Response Syntax
{
'JobStatus': 'IN_PROGRESS'|'SUCCEEDED'|'FAILED',
'StatusMessage': 'string',
'NextToken': 'string',
'VideoMetadata': {
'Codec': 'string',
'DurationMillis': 123,
'Format': 'string',
'FrameRate': ...,
'FrameHeight': 123,
'FrameWidth': 123
},
'Persons': [
{
'Timestamp': 123,
'Person': {
'Index': 123,
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
},
'FaceMatches': [
{
'Similarity': ...,
'Face': {
'FaceId': 'string',
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'ImageId': 'string',
'ExternalImageId': 'string',
'Confidence': ...
}
},
]
},
]
}
Response Structure
(dict) --
JobStatus (string) --
The current status of the face search job.
StatusMessage (string) --
If the job fails, StatusMessage provides a descriptive error message.
NextToken (string) --
If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of search results.
VideoMetadata (dict) --
Information about a video that Amazon Rekognition analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.
Codec (string) --
Type of compression used in the analyzed video.
DurationMillis (integer) --
Length of the video in milliseconds.
Format (string) --
Format of the analyzed video. Possible values are MP4, MOV and AVI.
FrameRate (float) --
Number of frames per second in the video.
FrameHeight (integer) --
Vertical pixel dimension of the video.
FrameWidth (integer) --
Horizontal pixel dimension of the video.
Persons (list) --
An array of persons, , in the video whose face(s) match the face(s) in an Amazon Rekognition collection. It also includes time information for when persons are matched in the video. You specify the input collection in an initial call to StartFaceSearch . Each Persons element includes a time the person was matched, face match details (FaceMatches ) for matching faces in the collection, and person information (Person ) for the matched person.
(dict) --
Information about a person whose face matches a face(s) in an Amazon Rekognition collection. Includes information about the faces in the Amazon Rekognition collection (), information about the person ( PersonDetail ), and the time stamp for when the person was detected in a video. An array of PersonMatch objects is returned by .
Timestamp (integer) --
The time, in milliseconds from the beginning of the video, that the person was matched in the video.
Person (dict) --
Information about the matched person.
Index (integer) --
Identifier for the person detected person within a video. Use to keep track of the person throughout the video. The identifier is not stored by Amazon Rekognition.
BoundingBox (dict) --
Bounding box around the detected person.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Face (dict) --
Face details for the detected person.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
FaceMatches (list) --
Information about the faces in the input collection that match the face of a person in the video.
(dict) --
Provides face metadata. In addition, it also provides the confidence in the match of this face with the input face.
Similarity (float) --
Confidence in the match of this face with the input face.
Face (dict) --
Describes the face properties such as the bounding box, face ID, image ID of the source image, and external image ID that you assigned.
FaceId (string) --
Unique identifier that Amazon Rekognition assigns to the face.
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
ImageId (string) --
Unique identifier that Amazon Rekognition assigns to the input image.
ExternalImageId (string) --
Identifier that you assign to all the faces in the input image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree).
{'Persons': {'Person': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}}}
Gets the path tracking results of a Amazon Rekognition Video analysis started by .
The person path tracking operation is started by a call to StartPersonTracking which returns a job identifier (JobId ). When the operation finishes, Amazon Rekognition Video publishes a completion status to the Amazon Simple Notification Service topic registered in the initial call to StartPersonTracking .
To get the results of the person path tracking operation, first check that the status value published to the Amazon SNS topic is SUCCEEDED . If so, call and pass the job identifier (JobId ) from the initial call to StartPersonTracking .
GetPersonTracking returns an array, Persons , of tracked persons and the time(s) their paths were tracked in the video.
Note
GetPersonTracking only returns the default facial attributes (BoundingBox , Confidence , Landmarks , Pose , and Quality ). The other facial attributes listed in the Face object of the following response syntax are not returned.
For more information, see FaceDetail in the Amazon Rekognition Developer Guide.
By default, the array is sorted by the time(s) a person's path is tracked in the video. You can sort by tracked persons by specifying INDEX for the SortBy input parameter.
Use the MaxResults parameter to limit the number of items returned. If there are more results than specified in MaxResults , the value of NextToken in the operation response contains a pagination token for getting the next set of results. To get the next page of results, call GetPersonTracking and populate the NextToken request parameter with the token value returned from the previous call to GetPersonTracking .
See also: AWS API Documentation
Request Syntax
client.get_person_tracking(
JobId='string',
MaxResults=123,
NextToken='string',
SortBy='INDEX'|'TIMESTAMP'
)
string
[REQUIRED]
The identifier for a job that tracks persons in a video. You get the JobId from a call to StartPersonTracking .
integer
Maximum number of results to return per paginated call. The largest value you can specify is 1000. If you specify a value greater than 1000, a maximum of 1000 results is returned. The default value is 1000.
string
If the previous response was incomplete (because there are more persons to retrieve), Amazon Rekognition Video returns a pagination token in the response. You can use this pagination token to retrieve the next set of persons.
string
Sort to use for elements in the Persons array. Use TIMESTAMP to sort array elements by the time persons are detected. Use INDEX to sort by the tracked persons. If you sort by INDEX , the array elements for each person are sorted by detection confidence. The default sort is by TIMESTAMP .
dict
Response Syntax
{
'JobStatus': 'IN_PROGRESS'|'SUCCEEDED'|'FAILED',
'StatusMessage': 'string',
'VideoMetadata': {
'Codec': 'string',
'DurationMillis': 123,
'Format': 'string',
'FrameRate': ...,
'FrameHeight': 123,
'FrameWidth': 123
},
'NextToken': 'string',
'Persons': [
{
'Timestamp': 123,
'Person': {
'Index': 123,
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
}
},
]
}
Response Structure
(dict) --
JobStatus (string) --
The current status of the person tracking job.
StatusMessage (string) --
If the job fails, StatusMessage provides a descriptive error message.
VideoMetadata (dict) --
Information about a video that Amazon Rekognition Video analyzed. Videometadata is returned in every page of paginated responses from a Amazon Rekognition Video operation.
Codec (string) --
Type of compression used in the analyzed video.
DurationMillis (integer) --
Length of the video in milliseconds.
Format (string) --
Format of the analyzed video. Possible values are MP4, MOV and AVI.
FrameRate (float) --
Number of frames per second in the video.
FrameHeight (integer) --
Vertical pixel dimension of the video.
FrameWidth (integer) --
Horizontal pixel dimension of the video.
NextToken (string) --
If the response is truncated, Amazon Rekognition Video returns this token that you can use in the subsequent request to retrieve the next set of persons.
Persons (list) --
An array of the persons detected in the video and the time(s) their path was tracked throughout the video. An array element will exist for each time a person's path is tracked.
(dict) --
Details and path tracking information for a single time a person's path is tracked in a video. Amazon Rekognition operations that track people's paths return an array of PersonDetection objects with elements for each time a person's path is tracked in a video.
For more information, see API_GetPersonTracking in the Amazon Rekognition Developer Guide.
Timestamp (integer) --
The time, in milliseconds from the start of the video, that the person's path was tracked.
Person (dict) --
Details about a person whose path was tracked in a video.
Index (integer) --
Identifier for the person detected person within a video. Use to keep track of the person throughout the video. The identifier is not stored by Amazon Rekognition.
BoundingBox (dict) --
Bounding box around the detected person.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Face (dict) --
Face details for the detected person.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
{'FaceRecords': {'FaceDetail': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}},
'UnindexedFaces': {'FaceDetail': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}}
Detects faces in the input image and adds them to the specified collection.
Amazon Rekognition doesn't save the actual faces that are detected. Instead, the underlying detection algorithm first detects the faces in the input image. For each face, the algorithm extracts facial features into a feature vector, and stores it in the backend database. Amazon Rekognition uses feature vectors when it performs face match and search operations using the and operations.
For more information, see Adding Faces to a Collection in the Amazon Rekognition Developer Guide.
To get the number of faces in a collection, call .
If you're using version 1.0 of the face detection model, IndexFaces indexes the 15 largest faces in the input image. Later versions of the face detection model index the 100 largest faces in the input image.
If you're using version 4 or later of the face model, image orientation information is not returned in the OrientationCorrection field.
To determine which version of the model you're using, call and supply the collection ID. You can also get the model version from the value of FaceModelVersion in the response from IndexFaces
For more information, see Model Versioning in the Amazon Rekognition Developer Guide.
If you provide the optional ExternalImageID for the input image you provided, Amazon Rekognition associates this ID with all faces that it detects. When you call the operation, the response returns the external ID. You can use this external image ID to create a client-side index to associate the faces with each image. You can then use the index to find all faces in an image.
You can specify the maximum number of faces to index with the MaxFaces input parameter. This is useful when you want to index the largest faces in an image and don't want to index smaller faces, such as those belonging to people standing in the background.
The QualityFilter input parameter allows you to filter out detected faces that don’t meet the required quality bar chosen by Amazon Rekognition. The quality bar is based on a variety of common use cases. By default, IndexFaces filters detected faces. You can also explicitly filter detected faces by specifying AUTO for the value of QualityFilter . If you do not want to filter detected faces, specify NONE .
Note
To use quality filtering, you need a collection associated with version 3 of the face model. To get the version of the face model associated with a collection, call .
Information about faces detected in an image, but not indexed, is returned in an array of objects, UnindexedFaces . Faces aren't indexed for reasons such as:
The number of faces detected exceeds the value of the MaxFaces request parameter.
The face is too small compared to the image dimensions.
The face is too blurry.
The image is too dark.
The face has an extreme pose.
In response, the IndexFaces operation returns an array of metadata for all detected faces, FaceRecords . This includes:
The bounding box, BoundingBox , of the detected face.
A confidence value, Confidence , which indicates the confidence that the bounding box contains a face.
A face ID, faceId , assigned by the service for each face that's detected and stored.
An image ID, ImageId , assigned by the service for the input image.
If you request all facial attributes (by using the detectionAttributes parameter), Amazon Rekognition returns detailed facial attributes, such as facial landmarks (for example, location of eye and mouth) and other facial attributes like gender. If you provide the same image, specify the same collection, and use the same external ID in the IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata.
The input image is passed 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 isn't supported. The image must be formatted as a PNG or JPEG file.
This operation requires permissions to perform the rekognition:IndexFaces action.
See also: AWS API Documentation
Request Syntax
client.index_faces(
CollectionId='string',
Image={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
ExternalImageId='string',
DetectionAttributes=[
'DEFAULT'|'ALL',
],
MaxFaces=123,
QualityFilter='NONE'|'AUTO'
)
string
[REQUIRED]
The ID of an existing collection to which you want to add the faces that are detected in the input images.
dict
[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 isn't supported.
Bytes (bytes) --
Blob of image bytes up to 5 MBs.
S3Object (dict) --
Identifies an S3 object as the image source.
Bucket (string) --
Name of the S3 bucket.
Name (string) --
S3 object key name.
Version (string) --
If the bucket is versioning enabled, you can specify the object version.
string
The ID you want to assign to all the faces detected in the image.
list
An array of facial attributes that you want to be returned. This can be the default list of attributes or all attributes. If you don't specify a value for Attributes or if you specify ["DEFAULT"] , the API returns the following subset of facial attributes: BoundingBox , Confidence , Pose , Quality , and Landmarks . If you provide ["ALL"] , all facial attributes are returned, but the operation takes longer to complete.
If you provide both, ["ALL", "DEFAULT"] , the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).
(string) --
integer
The maximum number of faces to index. The value of MaxFaces must be greater than or equal to 1. IndexFaces returns no more than 100 detected faces in an image, even if you specify a larger value for MaxFaces .
If IndexFaces detects more faces than the value of MaxFaces , the faces with the lowest quality are filtered out first. If there are still more faces than the value of MaxFaces , the faces with the smallest bounding boxes are filtered out (up to the number that's needed to satisfy the value of MaxFaces ). Information about the unindexed faces is available in the UnindexedFaces array.
The faces that are returned by IndexFaces are sorted by the largest face bounding box size to the smallest size, in descending order.
MaxFaces can be used with a collection associated with any version of the face model.
string
A filter that specifies how much filtering is done to identify faces that are detected with low quality. Filtered faces aren't indexed. If you specify AUTO , filtering prioritizes the identification of faces that don’t meet the required quality bar chosen by Amazon Rekognition. The quality bar is based on a variety of common use cases. Low-quality detections can occur for a number of reasons. Some examples are an object that's misidentified as a face, a face that's too blurry, or a face with a pose that's too extreme to use. If you specify NONE , no filtering is performed. The default value is AUTO.
To use quality filtering, the collection you are using must be associated with version 3 of the face model.
dict
Response Syntax
{
'FaceRecords': [
{
'Face': {
'FaceId': 'string',
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'ImageId': 'string',
'ExternalImageId': 'string',
'Confidence': ...
},
'FaceDetail': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
},
],
'OrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270',
'FaceModelVersion': 'string',
'UnindexedFaces': [
{
'Reasons': [
'EXCEEDS_MAX_FACES'|'EXTREME_POSE'|'LOW_BRIGHTNESS'|'LOW_SHARPNESS'|'LOW_CONFIDENCE'|'SMALL_BOUNDING_BOX',
],
'FaceDetail': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'AgeRange': {
'Low': 123,
'High': 123
},
'Smile': {
'Value': True|False,
'Confidence': ...
},
'Eyeglasses': {
'Value': True|False,
'Confidence': ...
},
'Sunglasses': {
'Value': True|False,
'Confidence': ...
},
'Gender': {
'Value': 'Male'|'Female',
'Confidence': ...
},
'Beard': {
'Value': True|False,
'Confidence': ...
},
'Mustache': {
'Value': True|False,
'Confidence': ...
},
'EyesOpen': {
'Value': True|False,
'Confidence': ...
},
'MouthOpen': {
'Value': True|False,
'Confidence': ...
},
'Emotions': [
{
'Type': 'HAPPY'|'SAD'|'ANGRY'|'CONFUSED'|'DISGUSTED'|'SURPRISED'|'CALM'|'UNKNOWN',
'Confidence': ...
},
],
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
},
]
}
Response Structure
(dict) --
FaceRecords (list) --
An array of faces detected and added to the collection. For more information, see Searching Faces in a Collection in the Amazon Rekognition Developer Guide.
(dict) --
Object containing both the face metadata (stored in the backend database), and facial attributes that are detected but aren't stored in the database.
Face (dict) --
Describes the face properties such as the bounding box, face ID, image ID of the input image, and external image ID that you assigned.
FaceId (string) --
Unique identifier that Amazon Rekognition assigns to the face.
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
ImageId (string) --
Unique identifier that Amazon Rekognition assigns to the input image.
ExternalImageId (string) --
Identifier that you assign to all the faces in the input image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree).
FaceDetail (dict) --
Structure containing attributes of the face that the algorithm detected.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
OrientationCorrection (string) --
If your collection is associated with a face detection model that's later than version 3.0, the value of OrientationCorrection is always null and no orientation information is returned.
If your collection is associated with a face detection model that's version 3.0 or earlier, the following applies:
If the input image is in .jpeg format, it might contain exchangeable image file format (Exif) metadata that includes the image's orientation. Amazon Rekognition uses this orientation information to perform image correction - the bounding box coordinates are translated to represent object locations after the orientation information in the Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata. The value of OrientationCorrection is null.
If the image doesn't contain orientation information in its Exif metadata, Amazon Rekognition returns an estimated orientation (ROTATE_0, ROTATE_90, ROTATE_180, ROTATE_270). Amazon Rekognition doesn’t perform image correction for images. The bounding box coordinates aren't translated and represent the object locations before the image is rotated.
Bounding box information is returned in the FaceRecords array. You can get the version of the face detection model by calling .
FaceModelVersion (string) --
The version number of the face detection model that's associated with the input collection (CollectionId ).
UnindexedFaces (list) --
An array of faces that were detected in the image but weren't indexed. They weren't indexed because the quality filter identified them as low quality, or the MaxFaces request parameter filtered them out. To use the quality filter, you specify the QualityFilter request parameter.
(dict) --
A face that detected, but didn't index. Use the Reasons response attribute to determine why a face wasn't indexed.
Reasons (list) --
An array of reasons that specify why a face wasn't indexed.
EXTREME_POSE - The face is at a pose that can't be detected. For example, the head is turned too far away from the camera.
EXCEEDS_MAX_FACES - The number of faces detected is already higher than that specified by the MaxFaces input parameter for IndexFaces .
LOW_BRIGHTNESS - The image is too dark.
LOW_SHARPNESS - The image is too blurry.
LOW_CONFIDENCE - The face was detected with a low confidence.
SMALL_BOUNDING_BOX - The bounding box around the face is too small.
(string) --
FaceDetail (dict) --
The structure that contains attributes of a face that IndexFaces detected, but didn't index.
BoundingBox (dict) --
Bounding box of the face. Default attribute.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
AgeRange (dict) --
The estimated age range, in years, for the face. Low represents the lowest estimated age and High represents the highest estimated age.
Low (integer) --
The lowest estimated age.
High (integer) --
The highest estimated age.
Smile (dict) --
Indicates whether or not the face is smiling, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is smiling or not.
Confidence (float) --
Level of confidence in the determination.
Eyeglasses (dict) --
Indicates whether or not the face is wearing eye glasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing eye glasses or not.
Confidence (float) --
Level of confidence in the determination.
Sunglasses (dict) --
Indicates whether or not the face is wearing sunglasses, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face is wearing sunglasses or not.
Confidence (float) --
Level of confidence in the determination.
Gender (dict) --
Gender of the face and the confidence level in the determination.
Value (string) --
Gender of the face.
Confidence (float) --
Level of confidence in the determination.
Beard (dict) --
Indicates whether or not the face has a beard, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has beard or not.
Confidence (float) --
Level of confidence in the determination.
Mustache (dict) --
Indicates whether or not the face has a mustache, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the face has mustache or not.
Confidence (float) --
Level of confidence in the determination.
EyesOpen (dict) --
Indicates whether or not the eyes on the face are open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the eyes on the face are open.
Confidence (float) --
Level of confidence in the determination.
MouthOpen (dict) --
Indicates whether or not the mouth on the face is open, and the confidence level in the determination.
Value (boolean) --
Boolean value that indicates whether the mouth on the face is open or not.
Confidence (float) --
Level of confidence in the determination.
Emotions (list) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
(dict) --
The emotions detected on the face, and the confidence level in the determination. For example, HAPPY, SAD, and ANGRY.
Type (string) --
Type of emotion detected.
Confidence (float) --
Level of confidence in the determination.
Landmarks (list) --
Indicates the location of landmarks on the face. Default attribute.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw. Default attribute.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies image brightness and sharpness. Default attribute.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree). Default attribute.
{'CelebrityFaces': {'Face': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}},
'UnrecognizedFaces': {'Landmarks': {'Type': ['chinBottom',
'midJawlineLeft',
'upperJawlineLeft',
'midJawlineRight',
'upperJawlineRight']}}}
Returns an array of celebrities recognized in the input image. For more information, see Recognizing Celebrities in the Amazon Rekognition Developer Guide.
RecognizeCelebrities returns the 100 largest faces in the image. It lists recognized celebrities in the CelebrityFaces array and unrecognized faces in the UnrecognizedFaces array. RecognizeCelebrities doesn't return celebrities whose faces aren't among the largest 100 faces in the image.
For each celebrity recognized, RecognizeCelebrities returns a Celebrity object. The Celebrity object contains the celebrity name, ID, URL links to additional information, match confidence, and a ComparedFace object that you can use to locate the celebrity's face on the image.
Amazon Rekognition doesn't retain information about which images a celebrity has been recognized in. Your application must store this information and use the Celebrity ID property as a unique identifier for the celebrity. If you don't store the celebrity name or additional information URLs returned by RecognizeCelebrities , you will need the ID to identify the celebrity in a call to the operation.
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.
For an example, see Recognizing Celebrities in an Image in the Amazon Rekognition Developer Guide.
This operation requires permissions to perform the rekognition:RecognizeCelebrities operation.
See also: AWS API Documentation
Request Syntax
client.recognize_celebrities(
Image={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
}
)
dict
[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.
Bytes (bytes) --
Blob of image bytes up to 5 MBs.
S3Object (dict) --
Identifies an S3 object as the image source.
Bucket (string) --
Name of the S3 bucket.
Name (string) --
S3 object key name.
Version (string) --
If the bucket is versioning enabled, you can specify the object version.
dict
Response Syntax
{
'CelebrityFaces': [
{
'Urls': [
'string',
],
'Name': 'string',
'Id': 'string',
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...,
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
}
},
'MatchConfidence': ...
},
],
'UnrecognizedFaces': [
{
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...,
'Landmarks': [
{
'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': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
}
},
],
'OrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270'
}
Response Structure
(dict) --
CelebrityFaces (list) --
Details about each celebrity found in the image. Amazon Rekognition can detect a maximum of 15 celebrities in an image.
(dict) --
Provides information about a celebrity recognized by the operation.
Urls (list) --
An array of URLs pointing to additional information about the celebrity. If there is no additional information about the celebrity, this list is empty.
(string) --
Name (string) --
The name of the celebrity.
Id (string) --
A unique identifier for the celebrity.
Face (dict) --
Provides information about the celebrity's face, such as its location on the image.
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
Level of confidence that what the bounding box contains is a face.
Landmarks (list) --
An array of facial landmarks.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies face image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
MatchConfidence (float) --
The confidence, in percentage, that Amazon Rekognition has that the recognized face is the celebrity.
UnrecognizedFaces (list) --
Details about each unrecognized face in the image.
(dict) --
Provides face metadata for target image faces that are analyzed by CompareFaces and RecognizeCelebrities .
BoundingBox (dict) --
Bounding box of the face.
Width (float) --
Width of the bounding box as a ratio of the overall image width.
Height (float) --
Height of the bounding box as a ratio of the overall image height.
Left (float) --
Left coordinate of the bounding box as a ratio of overall image width.
Top (float) --
Top coordinate of the bounding box as a ratio of overall image height.
Confidence (float) --
Level of confidence that what the bounding box contains is a face.
Landmarks (list) --
An array of facial landmarks.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of landmark.
X (float) --
The x-coordinate from the top left of the landmark expressed as the ratio of the width of the image. For example, if the image is 700 x 200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
The y-coordinate from the top left of the landmark expressed as the ratio of the height of the image. For example, if the image is 700 x 200 and the y-coordinate of the landmark is at 100 pixels, this value is 0.5.
Pose (dict) --
Indicates the pose of the face as determined by its pitch, roll, and yaw.
Roll (float) --
Value representing the face rotation on the roll axis.
Yaw (float) --
Value representing the face rotation on the yaw axis.
Pitch (float) --
Value representing the face rotation on the pitch axis.
Quality (dict) --
Identifies face image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a brighter face image.
Sharpness (float) --
Value representing sharpness of the face. The service returns a value between 0 and 100 (inclusive). A higher value indicates a sharper face image.
OrientationCorrection (string) --
The orientation of the input image (counterclockwise direction). If your application displays the image, you can use this value to correct the orientation. The bounding box coordinates returned in CelebrityFaces and UnrecognizedFaces represent face locations before the image orientation is corrected.
Note
If the input image is in .jpeg format, it might contain exchangeable image (Exif) metadata that includes the image's orientation. If so, and the Exif metadata for the input image populates the orientation field, the value of OrientationCorrection is null. The CelebrityFaces and UnrecognizedFaces bounding box coordinates represent face locations after Exif metadata is used to correct the image orientation. Images in .png format don't contain Exif metadata.