2017/02/09 - Amazon Rekognition - 2 updated api methods
Changes Update rekognition client to latest version
{'FaceDetails': {'AgeRange': {'High': 'integer', 'Low': 'integer'}}}
Detects faces within an image (JPEG or PNG) that is provided as input.
For each face detected, the operation returns face details including 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, etc.
The face-detection algorithm is most effective on frontal faces. For non-frontal or obscured faces, the algorithm may not detect the faces or might detect faces with lower confidence.
For an example, see get-started-exercise-detect-faces.
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 image in which you want to detect faces. You can specify a blob or an S3 object.
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
A list of facial attributes you would like to be returned. By default, the API returns subset of facial attributes.
For example, you can specify the value as, ["ALL"] or ["DEFAULT"]. If you provide both, ["ALL", "DEFAULT"], the service uses a logical AND operator to determine which attributes to return (in this case, it is all attributes). If you specify all attributes, Amazon Rekognition performs additional detection.
(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': 'EYE_LEFT'|'EYE_RIGHT'|'NOSE'|'MOUTH_LEFT'|'MOUTH_RIGHT'|'LEFT_EYEBROW_LEFT'|'LEFT_EYEBROW_RIGHT'|'LEFT_EYEBROW_UP'|'RIGHT_EYEBROW_LEFT'|'RIGHT_EYEBROW_RIGHT'|'RIGHT_EYEBROW_UP'|'LEFT_EYE_LEFT'|'LEFT_EYE_RIGHT'|'LEFT_EYE_UP'|'LEFT_EYE_DOWN'|'RIGHT_EYE_LEFT'|'RIGHT_EYE_RIGHT'|'RIGHT_EYE_UP'|'RIGHT_EYE_DOWN'|'NOSE_LEFT'|'NOSE_RIGHT'|'MOUTH_UP'|'MOUTH_DOWN'|'LEFT_PUPIL'|'RIGHT_PUPIL',
'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.
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.
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 the landmark on the face.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of the landmark.
X (float) --
x-coordinate from the top left of the landmark expressed as the ration of the width of the image. For example, if the images is 700x200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
y-coordinate from the top left of the landmark expressed as the ration of the height of the image. For example, if the images is 700x200 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 pitch, roll, and the 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 image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 1 (inclusive).
Sharpness (float) --
Value representing sharpness of the face.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree).
OrientationCorrection (string) --
The algorithm detects the image orientation. If it detects that the image was rotated, it returns the degrees of rotation. If your application is displaying the image, you can use this value to adjust the orientation.
For example, if the service detects that the input image was rotated by 90 degrees, it corrects orientation, performs face detection, and then returns the faces. That is, the bounding box coordinates in the response are based on the corrected orientation.
{'FaceRecords': {'FaceDetail': {'AgeRange': {'High': 'integer',
'Low': 'integer'}}}}
Detects faces in the input image and adds them to the specified collection.
Amazon Rekognition does not save the actual faces detected. Instead, the underlying detection algorithm first detects the faces in the input image, and for each face extracts facial features into a feature vector, and stores it in the back-end database. Amazon Rekognition uses feature vectors when performing face match and search operations using the and operations.
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.
In response, the operation returns an array of metadata for all detected faces. This includes, the bounding box of the detected face, confidence value (indicating the bounding box contains a face), a face ID assigned by the service for each face that is detected and stored, and an image ID assigned by the service for the input image If you request all facial attributes (using the detectionAttributes parameter, Amazon Rekognition returns detailed facial attributes such as facial landmarks (for example, location of eye and mount) and other facial attributes such 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.
For an example, see example2.
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',
]
)
string
[REQUIRED]
ID of an existing collection to which you want to add the faces that are detected in the input images.
dict
[REQUIRED]
Provides the source image either as bytes or an S3 object.
The region for the S3 bucket containing the S3 object must match the region you use for Amazon Rekognition operations.
You may need to Base64-encode the image bytes depending on the language you are using and whether or not you are using the AWS SDK. For more information, see example4.
If you use the Amazon CLI to call Amazon Rekognition operations, passing image bytes using the Bytes property is not supported. You must first upload the image to an Amazon S3 bucket and then call the operation using the S3Object property.
For Amazon Rekognition to process an S3 object, the user must have permission to access the S3 object. For more information, see manage-access-resource-policies.
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
ID you want to assign to all the faces detected in the image.
list
(Optional) Returns detailed attributes of indexed faces. By default, the operation returns a subset of the facial attributes.
For example, you can specify the value as, ["ALL"] or ["DEFAULT"]. If you provide both, ["ALL", "DEFAULT"], Amazon Rekognition uses the logical AND operator to determine which attributes to return (in this case, it is all attributes). If you specify all attributes, the service performs additional detection, in addition to the default.
(string) --
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': 'EYE_LEFT'|'EYE_RIGHT'|'NOSE'|'MOUTH_LEFT'|'MOUTH_RIGHT'|'LEFT_EYEBROW_LEFT'|'LEFT_EYEBROW_RIGHT'|'LEFT_EYEBROW_UP'|'RIGHT_EYEBROW_LEFT'|'RIGHT_EYEBROW_RIGHT'|'RIGHT_EYEBROW_UP'|'LEFT_EYE_LEFT'|'LEFT_EYE_RIGHT'|'LEFT_EYE_UP'|'LEFT_EYE_DOWN'|'RIGHT_EYE_LEFT'|'RIGHT_EYE_RIGHT'|'RIGHT_EYE_UP'|'RIGHT_EYE_DOWN'|'NOSE_LEFT'|'NOSE_RIGHT'|'MOUTH_UP'|'MOUTH_DOWN'|'LEFT_PUPIL'|'RIGHT_PUPIL',
'X': ...,
'Y': ...
},
],
'Pose': {
'Roll': ...,
'Yaw': ...,
'Pitch': ...
},
'Quality': {
'Brightness': ...,
'Sharpness': ...
},
'Confidence': ...
}
},
],
'OrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270'
}
Response Structure
(dict) --
FaceRecords (list) --
An array of faces detected and added to the collection. For more information, see howitworks-index-faces.
(dict) --
Object containing both the face metadata (stored in the back-end 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 source image, and external image ID that you assigned.
FaceId (string) --
Unique identifier that Amazon Rekognition assigns to the face.
BoundingBox (dict) --
Identifies the bounding box around the object or face. The left (x-coordinate) and top (y-coordinate) are coordinates representing the top and left sides of the bounding box. Note that the upper-left corner of the image is the origin (0,0).
The top and left values returned are ratios of the overall image size. For example, if the input image is 700x200 pixels, and the top-left coordinate of the bounding box is 350x50 pixels, the API returns a left value of 0.5 (350/700) and a top value of 0.25 (50/200).
The width and height values represent the dimensions of the bounding box as a ratio of the overall image dimension. For example, if the input image is 700x200 pixels, and the bounding box width is 70 pixels, the width returned is 0.1.
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 source 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.
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 the landmark on the face.
(dict) --
Indicates the location of the landmark on the face.
Type (string) --
Type of the landmark.
X (float) --
x-coordinate from the top left of the landmark expressed as the ration of the width of the image. For example, if the images is 700x200 and the x-coordinate of the landmark is at 350 pixels, this value is 0.5.
Y (float) --
y-coordinate from the top left of the landmark expressed as the ration of the height of the image. For example, if the images is 700x200 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 pitch, roll, and the 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 image brightness and sharpness.
Brightness (float) --
Value representing brightness of the face. The service returns a value between 0 and 1 (inclusive).
Sharpness (float) --
Value representing sharpness of the face.
Confidence (float) --
Confidence level that the bounding box contains a face (and not a different object such as a tree).
OrientationCorrection (string) --
The algorithm detects the image orientation. If it detects that the image was rotated, it returns the degree of rotation. You can use this value to correct the orientation and also appropriately analyze the bounding box coordinates that are returned.