2016/11/30 - Amazon Rekognition - 11 new api methods
Changes Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications.
Creates a collection in an AWS region. You can add faces to the collection using the operation.
For example, you might create collections, one for each of your application users. A user can then index faces using the IndexFaces operation and persist results in a specific collection. Then, a user can search the collection for faces in the user-specific container.
For an example, see example1.
This operation requires permissions to perform the rekognition:CreateCollection action.
See also: AWS API Documentation
Request Syntax
client.create_collection(
CollectionId='string'
)
string
[REQUIRED]
ID for the collection that you are creating.
dict
Response Syntax
{
'StatusCode': 123,
'CollectionArn': 'string'
}
Response Structure
(dict) --
StatusCode (integer) --
HTTP status code indicating the result of the operation.
CollectionArn (string) --
Amazon Resource Name (ARN) of the collection. You can use this to manage permissions on your resources.
Detects instances of real-world labels within an image (JPEG or PNG) provided as input. This includes objects like flower, tree, and table; events like wedding, graduation, and birthday party; and concepts like landscape, evening, and nature. For an example, see get-started-exercise-detect-labels.
For each object, scene, and concept the API returns one or more labels. Each label provides the object name, and the level of confidence that the image contains the object. For example, suppose the input image has a lighthouse, the sea, and a rock. The response will include all three labels, one for each object.
{Name: lighthouse, Confidence: 98.4629}
{Name: rock,Confidence: 79.2097}
{Name: sea,Confidence: 75.061}
In the preceding example, the operation returns one label for each of the three objects. The operation can also return multiple labels for the same object in the image. For example, if the input image shows a flower (for example, a tulip), the operation might return the following three labels.
{Name: flower,Confidence: 99.0562}
{Name: plant,Confidence: 99.0562}
{Name: tulip,Confidence: 99.0562}
In this example, the detection algorithm more precisely identifies the flower as a tulip.
You can provide the input image as an S3 object or as base64-encoded bytes. In response, the API returns an array of labels. In addition, the response also includes the orientation correction. Optionally, you can specify MinConfidence to control the confidence threshold for the labels returned. The default is 50%. You can also add the MaxLabels parameter to limit the number of labels returned.
Note
If the object detected is a person, the operation doesn't provide the same facial details that the DetectFaces operation provides.
This is a stateless API operation. That is, the operation does not persist any data.
This operation requires permissions to perform the rekognition:DetectLabels action.
See also: AWS API Documentation
Request Syntax
client.detect_labels(
Image={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
MaxLabels=123,
MinConfidence=...
)
dict
[REQUIRED]
The input image. You can provide a blob of image bytes 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.
integer
Maximum number of labels you want the service to return in the response. The service returns the specified number of highest confidence labels.
float
Specifies the minimum confidence level for the labels to return. Amazon Rekognition doesn't return any labels with confidence lower than this specified value.
If minConfidence is not specified, the operation returns labels with a confidence values greater than or equal to 50 percent.
dict
Response Syntax
{
'Labels': [
{
'Name': 'string',
'Confidence': ...
},
],
'OrientationCorrection': 'ROTATE_0'|'ROTATE_90'|'ROTATE_180'|'ROTATE_270'
}
Response Structure
(dict) --
Labels (list) --
An array of labels for the real-world objects detected.
(dict) --
Structure containing details about the detected label, including bounding box, name, and level of confidence.
Name (string) --
The name (label) of the object.
Confidence (float) --
Level of confidence.
OrientationCorrection (string) --
Amazon Rekognition returns the orientation of the input image that was detected (clockwise direction). If your application displays the image, you can use this value to correct the orientation. If Rekognition detects that the input image was rotated (for example, by 90 degrees), it first corrects the orientation before detecting the labels.
Deletes faces from a collection. You specify a collection ID and an array of face IDs to remove from the collection.
This operation requires permissions to perform the rekognition:DeleteFaces action.
See also: AWS API Documentation
Request Syntax
client.delete_faces(
CollectionId='string',
FaceIds=[
'string',
]
)
string
[REQUIRED]
Collection from which to remove the specific faces.
list
[REQUIRED]
An array of face IDs to delete.
(string) --
dict
Response Syntax
{
'DeletedFaces': [
'string',
]
}
Response Structure
(dict) --
DeletedFaces (list) --
An array of strings (face IDs) of the faces that were deleted.
(string) --
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, 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, 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.
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"], 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': ...
},
'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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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.
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, then 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, then 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.
For a given input image, first detects the largest face in the image, and then searches the specified collection for matching faces. The operation compares the features of the input face with faces in the specified collection.
Note
To search for all faces in an input image, you might first call the API, and then use the face IDs returned in subsequent calls to the API.
You can also call the DetectFaces API and use the bounding boxes in the response to make face crops, which then you can pass in to the SearchFacesByImage API.
The response returns an array of faces that match, ordered by similarity score with the highest similarity first. More specifically, it is an array of metadata for each face match found. Along with the metadata, the response also includes a similarity indicating how similar the face is to the input face. In the response, the API also returns the bounding box (and a confidence level that the bounding box contains a face) of the face that Rekognition used for the input image.
For an example, see example3.
This operation requires permissions to perform the rekognition:SearchFacesByImage action.
See also: AWS API Documentation
Request Syntax
client.search_faces_by_image(
CollectionId='string',
Image={
'Bytes': b'bytes',
'S3Object': {
'Bucket': 'string',
'Name': 'string',
'Version': 'string'
}
},
MaxFaces=123,
FaceMatchThreshold=...
)
string
[REQUIRED]
ID of the collection to search.
dict
[REQUIRED]
Provides the source image either as bytes 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.
integer
Maximum number of faces to return. The operation returns the maximum number of faces with the highest confidence in the match.
float
(Optional) Specifies the minimum confidence in the face match to return. For example, don't return any matches where confidence in matches is less than 70%.
dict
Response Syntax
{
'SearchedFaceBoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'SearchedFaceConfidence': ...,
'FaceMatches': [
{
'Similarity': ...,
'Face': {
'FaceId': 'string',
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'ImageId': 'string',
'ExternalImageId': 'string',
'Confidence': ...
}
},
]
}
Response Structure
(dict) --
SearchedFaceBoundingBox (dict) --
The bounding box around the face in the input image that Rekognition used for the search.
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.
SearchedFaceConfidence (float) --
The level of confidence that the searchedFaceBoundingBox , contains a face.
FaceMatches (list) --
An array of faces that match the input face, along with the confidence in the match.
(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) --
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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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).
For a given input face ID, searches the specified collection for matching faces. You get a face ID when you add a face to the collection using the IndexFaces operation. The operation compares the features of the input face with faces in the specified collection.
Note
You can also search faces without indexing faces by using the SearchFacesByImage operation.
The operation response returns an array of faces that match, ordered by similarity score with the highest similarity first. More specifically, it is an array of metadata for each face match that is found. Along with the metadata, the response also includes a confidence value for each face match, indicating the confidence that the specific face matches the input face.
For an example, see example3.
This operation requires permissions to perform the rekognition:SearchFaces action.
See also: AWS API Documentation
Request Syntax
client.search_faces(
CollectionId='string',
FaceId='string',
MaxFaces=123,
FaceMatchThreshold=...
)
string
[REQUIRED]
ID of the collection to search.
string
[REQUIRED]
ID of a face to find matches for in the collection.
integer
Maximum number of faces to return. The API will return the maximum number of faces with the highest confidence in the match.
float
Optional value specifying the minimum confidence in the face match to return. For example, don't return any matches where confidence in matches is less than 70%.
dict
Response Syntax
{
'SearchedFaceId': 'string',
'FaceMatches': [
{
'Similarity': ...,
'Face': {
'FaceId': 'string',
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'ImageId': 'string',
'ExternalImageId': 'string',
'Confidence': ...
}
},
]
}
Response Structure
(dict) --
SearchedFaceId (string) --
ID of the face that was searched for matches in a collection.
FaceMatches (list) --
An array of faces that matched the input face, along with the confidence in the match.
(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) --
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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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).
Returns list of collection IDs in your account. If the result is truncated, the response also provides a NextToken that you can use in the subsequent request to fetch the next set of collection IDs.
For an example, see example1.
This operation requires permissions to perform the rekognition:ListCollections action.
See also: AWS API Documentation
Request Syntax
client.list_collections(
NextToken='string',
MaxResults=123
)
string
Pagination token from the previous response.
integer
Maximum number of collection IDs to return.
dict
Response Syntax
{
'CollectionIds': [
'string',
],
'NextToken': 'string'
}
Response Structure
(dict) --
CollectionIds (list) --
An array of collection IDs.
(string) --
NextToken (string) --
If the result is truncated, the response provides a NextToken that you can use in the subsequent request to fetch the next set of collection IDs.
Compares a face in the source input image with each face detected in the target input image.
Note
If the source image contains multiple faces, the service detects the largest face and uses it to compare with each face detected in the target image.
In response, the operation returns an array of face matches ordered by similarity score with the highest similarity scores first. For each face match, the response provides a bounding box of the face 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 the similarity score of greater than or equal to 80% are returned in the response. You can change this value.
In addition to the face matches, the response returns information about the face in the source image, including the bounding box of the face and confidence value.
Note
This is a stateless API operation. That is, the operation does not persist any data.
For an example, see get-started-exercise-compare-faces
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]
Source image either as bytes or an Amazon 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.
dict
[REQUIRED]
Target image either as bytes or an Amazon 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.
float
The minimum level of confidence in the match you want included in the result.
dict
Response Syntax
{
'SourceImageFace': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...
},
'FaceMatches': [
{
'Similarity': ...,
'Face': {
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'Confidence': ...
}
},
]
}
Response Structure
(dict) --
SourceImageFace (dict) --
The face from the source image that was used for comparison.
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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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 that the selected bounding box contains a face.
FaceMatches (list) --
Provides an array of CompareFacesMatch objects. Each object provides the bounding box, confidence that the bounding box contains a face, and the similarity between the face in the bounding box and the face in the source image.
(dict) --
Provide the bounding box, confidence that the bounding box actually contains a face, and the similarity between the face in the bounding box and the face in the source image.
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) --
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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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.
Deletes the specified collection. Note that this operation removes all faces in the collection. For an example, see example1.
This operation requires permissions to perform the rekognition:DeleteCollection action.
See also: AWS API Documentation
Request Syntax
client.delete_collection(
CollectionId='string'
)
string
[REQUIRED]
ID of the collection to delete.
dict
Response Syntax
{
'StatusCode': 123
}
Response Structure
(dict) --
StatusCode (integer) --
HTTP status code that indicates the result of the operation.
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.
Note
This is a stateless API operation. That is, the operation does not persist any data.
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, Rekognition performs additional detection.
(string) --
dict
Response Syntax
{
'FaceDetails': [
{
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'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.
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, then 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, then 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.
Returns metadata for faces in the specified collection. This metadata includes information such as the bounding box coordinates, the confidence (that the bounding box contains a face), and face ID. For an example, see example3.
This operation requires permissions to perform the rekognition:ListFaces action.
See also: AWS API Documentation
Request Syntax
client.list_faces(
CollectionId='string',
NextToken='string',
MaxResults=123
)
string
[REQUIRED]
ID of the collection from which to list the faces.
string
If the previous response was incomplete (because there is more data to retrieve), Amazon Rekognition returns a pagination token in the response. You can use this pagination token to retrieve the next set of faces.
integer
Maximum number of faces to return.
dict
Response Syntax
{
'Faces': [
{
'FaceId': 'string',
'BoundingBox': {
'Width': ...,
'Height': ...,
'Left': ...,
'Top': ...
},
'ImageId': 'string',
'ExternalImageId': 'string',
'Confidence': ...
},
],
'NextToken': 'string'
}
Response Structure
(dict) --
Faces (list) --
An array of Face objects.
(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.
Note
The bounding box coordinates can have negative values. For example, if Amazon Rekognition is able to detect a face that is at the image edge and is only partially visible, the service can return coordinates that are outside the image bounds and, depending on the image edge, you might get negative values or values greater than 1 for the left or top values.
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).
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.