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This commit is contained in:
Manav Rathi 2024-05-18 10:23:50 +05:30
parent 42d767cac3
commit 9fa828e384
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1 changed files with 19 additions and 26 deletions
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45
web/apps/photos/src/services/face/f-index.ts
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@ -157,26 +157,24 @@ const detectFaces = async (
): Promise<Array<FaceDetection>> => {
const maxFaceDistancePercent = Math.sqrt(2) / 100;
const maxFaceDistance = imageBitmap.width * maxFaceDistancePercent;
const preprocessResult = preprocessImageBitmapToFloat32ChannelsFirst(
imageBitmap,
640,
640,
);
const data = preprocessResult.data;
const resized = preprocessResult.newSize;
const outputData = await workerBridge.detectFaces(data);
const faces = getFacesFromYOLOOutput(outputData as Float32Array, 0.7);
const inBox = newBox(0, 0, resized.width, resized.height);
const { yoloInput, yoloSize } =
convertToYOLOInputFloat32ChannelsFirst(imageBitmap);
const yoloOutput = await workerBridge.detectFaces(yoloInput);
const faces = getFacesFromYOLOOutput(yoloOutput, 0.7);
const inBox = newBox(0, 0, yoloSize.width, yoloSize.height);
const toBox = newBox(0, 0, imageBitmap.width, imageBitmap.height);
const faceDetections = transformFaceDetections(faces, inBox, toBox);
return removeDuplicateDetections(faceDetections, maxFaceDistance);
};
const preprocessImageBitmapToFloat32ChannelsFirst = (
imageBitmap: ImageBitmap,
requiredWidth: number,
requiredHeight: number,
) => {
/**
* Convert {@link imageBitmap} into the format that the YOLO face detection
* model expects.
*/
const convertToYOLOInputFloat32ChannelsFirst = (imageBitmap: ImageBitmap) => {
const requiredWidth = 640;
const requiredHeight = 640;
const width = imageBitmap.width;
const height = imageBitmap.height;
@ -193,9 +191,8 @@ const preprocessImageBitmapToFloat32ChannelsFirst = (
const scaledWidth = clamp(Math.round(width * scale), 0, requiredWidth);
const scaledHeight = clamp(Math.round(height * scale), 0, requiredHeight);
const processedImage = new Float32Array(
1 * 3 * requiredWidth * requiredHeight,
);
const yoloInput = new Float32Array(1 * 3 * requiredWidth * requiredHeight);
const yoloSize = { width: scaledWidth, height: scaledHeight };
// Populate the Float32Array with normalized pixel values.
let pixelIndex = 0;
@ -213,20 +210,16 @@ const preprocessImageBitmapToFloat32ChannelsFirst = (
width,
height,
);
processedImage[pixelIndex] = normalizePixelBetween0And1(r);
processedImage[pixelIndex + channelOffsetGreen] =
yoloInput[pixelIndex] = normalizePixelBetween0And1(r);
yoloInput[pixelIndex + channelOffsetGreen] =
normalizePixelBetween0And1(g);
processedImage[pixelIndex + channelOffsetBlue] =
yoloInput[pixelIndex + channelOffsetBlue] =
normalizePixelBetween0And1(b);
pixelIndex++;
}
}
return {
data: processedImage,
originalSize: { width: width, height: height },
newSize: { width: scaledWidth, height: scaledHeight },
};
return { yoloInput, yoloSize };
};
/**