Lambda architecture

clone

metadata

stats

composite (Though this is permitted through the use of overlayWith)

certain output options (Including toFile, toBuffer, tile and raw)

smartCrop(optional, boolean || object) - Activates the smart cropping feature for an original image. If the value is true, then the feature returns the first face detected from the original image with no additional options. For example:

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        smartCrop: true
    }
})

The following smartCrop variables are shown in the following code sample:

smartCrop.faceIndex(optional, number) - Specifies which face to focus on if multiple are present within an original image. The solution indexes detected faces in a zero-based array from the largest detected face to the smallest. If this value isn’t specified, Amazon Rekognition returns the largest face detected from the original image. smartCrop.padding(optional, number) - Specifies an amount of padding in pixels to add around the cropped image. The solution applies the padding value to all sides of the cropped image.

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        smartCrop: {
            faceIndex: 1,  // zero-based index of detected faces
            padding: 40,   // padding expressed in pixels, applied to all sides
        }
    }
})

roundCrop(optional, boolean || object) - Activates the round cropping feature for an original image. If the value is true, then the feature returns a circular cropped image that’s centered from the original image and has a diameter of the smallest edge of the original image. For example:

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        roundCrop: true
    }
})

The following roundCrop variables are shown in the following code sample:

roundCrop.rx (optional, number) - Specifies the radius along the x-axis of the ellipse. If a value isn’t provided, the image handler defaults to a value that’s half the length of the smallest edge. roundCrop.ry (optional, number) - Specifies the radius along the y-axis of the ellipse. If a value isn’t provided, the image handler defaults to a value that’s half the length of the smallest edge. roundCrop.top(optional, number) - Specifies the offset from the top of the original image to place the center of the ellipse. If a value isn’t provided, the image handler defaults to a value that’s half of the height. roundCrop.left (optional, number) - Specifies the offset from the left-most edge of the original image to place the center of the ellipse. If a value isn’t provided, the image handler defaults to a value that’s half of the width.

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        roundCrop: {
            rx: 30,   // x-axis radius
            ry: 20,   // y-axis radius
            top: 300, // offset from top edge of original image
            left: 500 // offset from left edge of original image
        }
    }
})

overlayWith.bucket (required, string) - Specifies the bucket that the overlay image should be retrieved from. This bucket must be present in the SOURCE_BUCKETS parameter.

overlayWith.key (required, string) - Specifies the object key that is used for the overlay image.

overlayWith.alpha (optional, number) - Specifies the opacity that should be used for the overlay image. This can be set from 0 (fully opaque) and 100 (fully transparent).

overlayWith.wRatio (required, number) - Specifies the percentage of the width of underlying image that the overlay image should be sized to. This can be set from 0 and 100, where 100 indicates that the overlay image has the same width as the underlying image.

overlayWith.hRatio (required, number) - Specifies the percentage of the height of underlying image that the overlay image should be sized to. This can be set from 0 and 100, where 100 indicates that the overlay image has the same height as the underlying image.

overlayWith.options.top (optional, number | string) - Specifies the distance in pixels from the top edge of the underlying photo that the overlay should be placed. A number formatted as a string with a p at the end is treated as a percentage.

overlayWith.options.left (optional, number | string) - Specifies the distance in pixels from the left edge of the underlying photo that the overlay should be placed. A number formatted as a string with a p at the end is treated as a percentage.

animated (optional, boolean) - Overwrites the initial animated status of the image. If the value is true , the solution will attempt to process the image as animated. For example:

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.webp>",
    edits: {
        animated: true
    }
})

If it is false, the solution will process the image as a still image. For example:

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.gif>",
    edits: {
        animated: false
    }
})

contentModeration (optional, boolean || object) - Activates the content moderation feature for an original image. If the value is true, then the feature detects inappropriate content using Amazon Rekognition with a minimum confidence that’s set higher than 75%. If Amazon Rekognition finds inappropriate content, the solution blurs the image. For example:

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        contentModeration: true
    }
})

The following contentModeration variables are shown in the following code sample:

contentModeration.minConfidence (optional, number) - Specifies the minimum confidence level for Amazon Rekognition to use. Amazon Rekognition only returns detected content that’s higher than the minimum confidence. If a value isn’t provided, the default value is set to 75%.

contentModeration.blur (optional, number) - Specifies the intensity level that an image is blurred if inappropriate content is found. The number represents the sigma of the Gaussian mask, where sigma = 1 + radius /2. For more information, refer to the sharp documentation. If a value isn’t provided, the default value is set to 50.

contentModeration.moderationLabels (optional, array) - Identifies the specific content to search for. The image is blurred only if Amazon Rekognition locates the content specified in the smartCrop.moderationLabels provided. You can use either a top-level category or a second-level category. Top-level categories include its associated second-level categories. For more information about moderation label options, refer to Content moderation in the Amazon Rekognition Developer Guide.

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    edits: {
        contentModeration: {
            minConfidence: 90,  // minimum confidence level for inappropriate content
            blur: 80,           // amount to blur image
            moderationLabels: [ // labels to search for
               "Hate Symbols",
               "Smoking"
             ]
        }
    }
})

headers (optional, object) - Includes the provided headers in the response. Header should be written in Pascal-Case and cannot overwrite headers that would otherwise be present in the response (Except for Cache-Control).

const imageRequest = JSON.stringify({
    bucket: "<myImageBucket>",
    key: "<myImage.jpeg>",
    headers: {
        "Cache-Control":"max-age=86400,public"
        "Custom-Header":"some-custom-value"
    }
})