Struct IndexFacesInput 

#[non_exhaustive]
pub struct IndexFacesInput {
    pub collection_id: Option<String>,
    pub image: Option<Image>,
    pub external_image_id: Option<String>,
    pub detection_attributes: Option<Vec<Attribute>>,
    pub max_faces: Option<i32>,
    pub quality_filter: Option<QualityFilter>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

collection_id: Option<String>

The ID of an existing collection to which you want to add the faces that are detected in the input images.

image: Option<Image>

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.

If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

external_image_id: Option<String>

The ID you want to assign to all the faces detected in the image.

detection_attributes: Option<Vec<Attribute>>

An array of facial attributes you want to be returned. A DEFAULT subset of facial attributes - BoundingBox, Confidence, Pose, Quality, and Landmarks - will always be returned. You can request for specific facial attributes (in addition to the default list) - by using \["DEFAULT", "FACE_OCCLUDED"\] or just \["FACE_OCCLUDED"\]. You can request for all facial attributes by using \["ALL"\]. Requesting more attributes may increase response time.

If you provide both, \["ALL", "DEFAULT"\], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

max_faces: Option<i32>

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.

quality_filter: Option<QualityFilter>

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. 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.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

Implementations

impl IndexFacesInput

pub fn collection_id(&self) -> Option<&str>

The ID of an existing collection to which you want to add the faces that are detected in the input images.

pub fn image(&self) -> Option<&Image>

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.

If you are using an AWS SDK to call Amazon Rekognition, you might not need to base64-encode image bytes passed using the Bytes field. For more information, see Images in the Amazon Rekognition developer guide.

pub fn external_image_id(&self) -> Option<&str>

The ID you want to assign to all the faces detected in the image.

pub fn detection_attributes(&self) -> &[Attribute]

An array of facial attributes you want to be returned. A DEFAULT subset of facial attributes - BoundingBox, Confidence, Pose, Quality, and Landmarks - will always be returned. You can request for specific facial attributes (in addition to the default list) - by using \["DEFAULT", "FACE_OCCLUDED"\] or just \["FACE_OCCLUDED"\]. You can request for all facial attributes by using \["ALL"\]. Requesting more attributes may increase response time.

If you provide both, \["ALL", "DEFAULT"\], the service uses a logical AND operator to determine which attributes to return (in this case, all attributes).

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .detection_attributes.is_none().

pub fn max_faces(&self) -> Option<i32>

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.

pub fn quality_filter(&self) -> Option<&QualityFilter>

A filter that specifies a quality bar for how much filtering is done to identify faces. Filtered faces aren't indexed. If you specify AUTO, Amazon Rekognition chooses the quality bar. If you specify LOW, MEDIUM, or HIGH, filtering removes all faces that don’t meet the chosen quality bar. The default value is AUTO. 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.

To use quality filtering, the collection you are using must be associated with version 3 of the face model or higher.

impl IndexFacesInput

pub fn builder() -> IndexFacesInputBuilder

Creates a new builder-style object to manufacture IndexFacesInput.

Trait Implementations

impl Clone for IndexFacesInput

fn clone(&self) -> IndexFacesInput

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for IndexFacesInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for IndexFacesInput

fn eq(&self, other: &IndexFacesInput) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for IndexFacesInput