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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,187 @@ | ||
| import { Face } from "services/face/types"; | ||
| import { createGrayscaleIntMatrixFromNormalized2List } from "utils/image"; | ||
| import { mobileFaceNetFaceSize } from "./embed"; | ||
|
|
||
| /** | ||
| * Laplacian blur detection. | ||
| */ | ||
| export const detectBlur = ( | ||
| alignedFaces: Float32Array, | ||
| faces: Face[], | ||
| ): number[] => { | ||
| const numFaces = Math.round( | ||
| alignedFaces.length / | ||
| (mobileFaceNetFaceSize * mobileFaceNetFaceSize * 3), | ||
| ); | ||
| const blurValues: number[] = []; | ||
| for (let i = 0; i < numFaces; i++) { | ||
| const face = faces[i]; | ||
| const direction = faceDirection(face); | ||
| const faceImage = createGrayscaleIntMatrixFromNormalized2List( | ||
| alignedFaces, | ||
| i, | ||
| ); | ||
| const laplacian = applyLaplacian(faceImage, direction); | ||
| blurValues.push(matrixVariance(laplacian)); | ||
| } | ||
| return blurValues; | ||
| }; | ||
|
|
||
| type FaceDirection = "left" | "right" | "straight"; | ||
|
|
||
| const faceDirection = (face: Face): FaceDirection => { | ||
| const landmarks = face.detection.landmarks; | ||
| const leftEye = landmarks[0]; | ||
| const rightEye = landmarks[1]; | ||
| const nose = landmarks[2]; | ||
| const leftMouth = landmarks[3]; | ||
| const rightMouth = landmarks[4]; | ||
|
|
||
| const eyeDistanceX = Math.abs(rightEye.x - leftEye.x); | ||
| const eyeDistanceY = Math.abs(rightEye.y - leftEye.y); | ||
| const mouthDistanceY = Math.abs(rightMouth.y - leftMouth.y); | ||
|
|
||
| const faceIsUpright = | ||
| Math.max(leftEye.y, rightEye.y) + 0.5 * eyeDistanceY < nose.y && | ||
| nose.y + 0.5 * mouthDistanceY < Math.min(leftMouth.y, rightMouth.y); | ||
|
|
||
| const noseStickingOutLeft = | ||
| nose.x < Math.min(leftEye.x, rightEye.x) && | ||
| nose.x < Math.min(leftMouth.x, rightMouth.x); | ||
|
|
||
| const noseStickingOutRight = | ||
| nose.x > Math.max(leftEye.x, rightEye.x) && | ||
| nose.x > Math.max(leftMouth.x, rightMouth.x); | ||
|
|
||
| const noseCloseToLeftEye = | ||
| Math.abs(nose.x - leftEye.x) < 0.2 * eyeDistanceX; | ||
| const noseCloseToRightEye = | ||
| Math.abs(nose.x - rightEye.x) < 0.2 * eyeDistanceX; | ||
|
|
||
| if (noseStickingOutLeft || (faceIsUpright && noseCloseToLeftEye)) { | ||
| return "left"; | ||
| } else if (noseStickingOutRight || (faceIsUpright && noseCloseToRightEye)) { | ||
| return "right"; | ||
| } | ||
|
|
||
| return "straight"; | ||
| }; | ||
|
|
||
| /** | ||
| * Return a new image by applying a Laplacian blur kernel to each pixel. | ||
| */ | ||
| const applyLaplacian = ( | ||
| image: number[][], | ||
| direction: FaceDirection, | ||
| ): number[][] => { | ||
| const paddedImage: number[][] = padImage(image, direction); | ||
| const numRows = paddedImage.length - 2; | ||
| const numCols = paddedImage[0].length - 2; | ||
|
|
||
| // Create an output image initialized to 0. | ||
| const outputImage: number[][] = Array.from({ length: numRows }, () => | ||
| new Array(numCols).fill(0), | ||
| ); | ||
|
|
||
| // Define the Laplacian kernel. | ||
| const kernel: number[][] = [ | ||
| [0, 1, 0], | ||
| [1, -4, 1], | ||
| [0, 1, 0], | ||
| ]; | ||
|
|
||
| // Apply the kernel to each pixel | ||
| for (let i = 0; i < numRows; i++) { | ||
| for (let j = 0; j < numCols; j++) { | ||
| let sum = 0; | ||
| for (let ki = 0; ki < 3; ki++) { | ||
| for (let kj = 0; kj < 3; kj++) { | ||
| sum += paddedImage[i + ki][j + kj] * kernel[ki][kj]; | ||
| } | ||
| } | ||
| // Adjust the output value if necessary (e.g., clipping). | ||
| outputImage[i][j] = sum; | ||
| } | ||
| } | ||
|
|
||
| return outputImage; | ||
| }; | ||
|
|
||
| const padImage = (image: number[][], direction: FaceDirection): number[][] => { | ||
| const removeSideColumns = 56; /* must be even */ | ||
|
|
||
| const numRows = image.length; | ||
| const numCols = image[0].length; | ||
| const paddedNumCols = numCols + 2 - removeSideColumns; | ||
| const paddedNumRows = numRows + 2; | ||
|
|
||
| // Create a new matrix with extra padding. | ||
| const paddedImage: number[][] = Array.from({ length: paddedNumRows }, () => | ||
| new Array(paddedNumCols).fill(0), | ||
| ); | ||
|
|
||
| if (direction === "straight") { | ||
| // Copy original image into the center of the padded image. | ||
| for (let i = 0; i < numRows; i++) { | ||
| for (let j = 0; j < paddedNumCols - 2; j++) { | ||
| paddedImage[i + 1][j + 1] = | ||
| image[i][j + Math.round(removeSideColumns / 2)]; | ||
| } | ||
| } | ||
| } else if (direction === "left") { | ||
| // If the face is facing left, we only take the right side of the face image. | ||
| for (let i = 0; i < numRows; i++) { | ||
| for (let j = 0; j < paddedNumCols - 2; j++) { | ||
| paddedImage[i + 1][j + 1] = image[i][j + removeSideColumns]; | ||
| } | ||
| } | ||
| } else if (direction === "right") { | ||
| // If the face is facing right, we only take the left side of the face image. | ||
| for (let i = 0; i < numRows; i++) { | ||
| for (let j = 0; j < paddedNumCols - 2; j++) { | ||
| paddedImage[i + 1][j + 1] = image[i][j]; | ||
| } | ||
| } | ||
| } | ||
|
|
||
| // Reflect padding | ||
| // Top and bottom rows | ||
| for (let j = 1; j <= paddedNumCols - 2; j++) { | ||
| paddedImage[0][j] = paddedImage[2][j]; // Top row | ||
| paddedImage[numRows + 1][j] = paddedImage[numRows - 1][j]; // Bottom row | ||
| } | ||
| // Left and right columns | ||
| for (let i = 0; i < numRows + 2; i++) { | ||
| paddedImage[i][0] = paddedImage[i][2]; // Left column | ||
| paddedImage[i][paddedNumCols - 1] = paddedImage[i][paddedNumCols - 3]; // Right column | ||
| } | ||
|
|
||
| return paddedImage; | ||
| }; | ||
|
|
||
| const matrixVariance = (matrix: number[][]): number => { | ||
| const numRows = matrix.length; | ||
| const numCols = matrix[0].length; | ||
| const totalElements = numRows * numCols; | ||
|
|
||
| // Calculate the mean. | ||
| let mean: number = 0; | ||
| matrix.forEach((row) => { | ||
| row.forEach((value) => { | ||
| mean += value; | ||
| }); | ||
| }); | ||
| mean /= totalElements; | ||
|
|
||
| // Calculate the variance. | ||
| let variance: number = 0; | ||
| matrix.forEach((row) => { | ||
| row.forEach((value) => { | ||
| const diff: number = value - mean; | ||
| variance += diff * diff; | ||
| }); | ||
| }); | ||
| variance /= totalElements; | ||
|
|
||
| return variance; | ||
| }; |
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