C# (CSharp) Amazon.Rekognition.Model Namespace

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.

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.

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.

For an example, see get-started-exercise-compare-faces

This operation requires permissions to perform the rekognition:CompareFaces action.

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.

This operation requires permissions to perform the rekognition:DeleteCollection action.

This operation requires permissions to perform the rekognition:DeleteFaces action.

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.

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.

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.

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.

For an example, see example1.

This operation requires permissions to perform the rekognition:ListCollections action.

This operation requires permissions to perform the rekognition:ListFaces action.

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.