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use convex quads for chest x-ray and only requre top vertices to pass…
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… visibility threshold
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@eyaler
eyaler committed May 24, 2024
1 parent 9707663 commit 7f52589
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Showing 2 changed files with 71 additions and 51 deletions.
2 changes: 1 addition & 1 deletion index.html
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Original file line number Diff line number Diff line change
Expand Up @@ -13,9 +13,9 @@
<select id="effect">
<option value="recode_landmarks">Recode + landmarks</option>
<option value="pose_landmarks">Pose landmarks</option>
<option value="chest_xray">Chest X-ray</option>
<option value="pixel_sorting">Pixel sorting</option>
<option value="bayer_dithering">Bayer dithering</option>
<option value="chest_xray">Chest X-ray</option>
<option value="recode_original">Recode original</option>
</select>
</div>
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120 changes: 70 additions & 50 deletions script.js
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Original file line number Diff line number Diff line change
Expand Up @@ -43,11 +43,31 @@ function yuv2rgb(Y, U, V) { // https://github.com/pps83/libyuv/blob/master/sour
return [Y + 1.793*V, Y - .213*U - .533*V, Y + 2.112*U]
}

function is_inside(edges, x, y) {
return edges.reduce((cnt, [x1, y1], i) => {
const [x2, y2] = edges[(i + 1) % edges.length]
return cnt + ((y < y1) != (y < y2) && x < x1 + ((y-y1)/(y2-y1))*(x2-x1))
}, 0) % 2 == 1
function cross_product(A, B, C) {
return (B[0]-A[0])*(C[1]-A[1]) - (B[1]-A[1])*(C[0]-A[0])
}

function is_convex(A, B, C, D) {
const cross1 = cross_product(A, B, C)
const cross2 = cross_product(B, C, D)
const cross3 = cross_product(C, D, A)
const cross4 = cross_product(D, A, B)

return (cross1 > 0 && cross2 > 0 && cross3 > 0 && cross4 > 0) ||
(cross1 < 0 && cross2 < 0 && cross3 < 0 && cross4 < 0)
}

function is_same_side(P1, P2, A, B) {
const cross1 = cross_product(A, B, P1)
const cross2 = cross_product(A, B, P2)
return cross1 * cross2 >= 0
}

function is_inside_convex(P, [A, B, C, D]) {
return is_same_side(P, C, A, B) &&
is_same_side(P, D, B, C) &&
is_same_side(P, A, C, D) &&
is_same_side(P, B, D, A)
}

const colors = ['lime', 'red', 'cyan', 'magenta']
Expand All @@ -72,6 +92,51 @@ const effect_funcs = {
}
},

'chest_xray': (W, H, stride, Voffset, Uoffset, yuv, rgba, videoFrame, poseLandmarker) => {
for (let y = 0; y < H; y++) {
const yUV = (y >> 1) * stride
for (let x = 0; x < W; x++) {
const xUV = x >> 1
const Y = yuv[x + y*W]
const U = yuv[Voffset + xUV + yUV]
const V = yuv[Uoffset + xUV + yUV]
;[rgba[x*4 + y*W*4], rgba[1 + x*4 + y*W*4], rgba[2 + x*4 + y*W*4]] = yuv2rgb(Y, U, V)
rgba[3 + x*4 + y*W*4] = 255
}
}
const startTimeMs = performance.now()
if (lastVideoTime != videoFrame.timestamp) {
lastVideoTime = videoFrame.timestamp
poseLandmarker.detectForVideo(videoFrame, startTimeMs, result => {
result.landmarks.forEach(landmarks => {
if (Math.min(landmarks[11].visibility, landmarks[12].visibility) >= .9 && is_convex([landmarks[11].x, landmarks[11].y], [landmarks[12].x, landmarks[12].y], [landmarks[24].x, landmarks[24].y], [landmarks[23].x, landmarks[23].y])) {
const ax = landmarks[11].x * W
const ay = landmarks[11].y * H
const bx = landmarks[12].x * W
const by = landmarks[12].y * H
const cx = (bx+landmarks[24].x*W) / 2
const cy = (by+landmarks[24].y*H) / 2
const dx = (ax+landmarks[23].x*W) / 2
const dy = (ay+landmarks[23].y*H) / 2
const min_x = Math.min(ax, bx, cx, dx)
const max_x = Math.max(ax, bx, cx, dx)
const min_y = Math.min(ay, by, cy, dy)
const max_y = Math.max(ay, by, cy, dy)
const vertices = [[ax, ay], [bx, by], [cx, cy], [dx, dy]]
for (let y = min_y | 0; y <= max_y; y++)
for (let x = min_x | 0; x <= max_x; x++)
if (is_inside_convex([x, y], vertices)) {
rgba[0 + x*4 + y*W*4] = 255 - rgba[0 + x*4 + y*W*4]
rgba[1 + x*4 + y*W*4] = 255 - rgba[1 + x*4 + y*W*4]
rgba[2 + x*4 + y*W*4] = 255 - rgba[2 + x*4 + y*W*4]
rgba[3 + x*4 + y*W*4] = 255
}
}
})
})
}
},

'pixel_sorting': (W, H, stride, Voffset, Uoffset, yuv, rgba) => {
for (let y = 0; y < H; y++) {
const yUV = (y >> 1) * stride
Expand Down Expand Up @@ -124,51 +189,6 @@ const effect_funcs = {
}
},

'chest_xray': (W, H, stride, Voffset, Uoffset, yuv, rgba, videoFrame, poseLandmarker) => {
for (let y = 0; y < H; y++) {
const yUV = (y >> 1) * stride
for (let x = 0; x < W; x++) {
const xUV = x >> 1
const Y = yuv[x + y*W]
const U = yuv[Voffset + xUV + yUV]
const V = yuv[Uoffset + xUV + yUV]
;[rgba[x*4 + y*W*4], rgba[1 + x*4 + y*W*4], rgba[2 + x*4 + y*W*4]] = yuv2rgb(Y, U, V)
rgba[3 + x*4 + y*W*4] = 255
}
}
const startTimeMs = performance.now()
if (lastVideoTime != videoFrame.timestamp) {
lastVideoTime = videoFrame.timestamp
poseLandmarker.detectForVideo(videoFrame, startTimeMs, result => {
result.landmarks.forEach(landmarks => {
if (Math.min(landmarks[11].visibility, landmarks[12].visibility, landmarks[23].visibility, landmarks[24].visibility) >= .95) {
const ax = landmarks[11].x * W
const ay = landmarks[11].y * H
const bx = landmarks[12].x * W
const by = landmarks[12].y * H
const cx = (bx+landmarks[24].x*W) / 2
const cy = (by+landmarks[24].y*H) / 2
const dx = (ax+landmarks[23].x*W) / 2
const dy = (ay+landmarks[23].y*H) / 2
const min_x = Math.min(ax, bx, cx, dx)
const max_x = Math.max(ax, bx, cx, dx)
const min_y = Math.min(ay, by, cy, dy)
const max_y = Math.max(ay, by, cy, dy)
const edges = [[ax, ay], [bx, by], [cx, cy], [dx, dy]]
for (let y = min_y | 0; y <= max_y; y++)
for (let x = min_x | 0; x <= max_x; x++)
if (is_inside(edges, x, y)) {
rgba[0 + x*4 + y*W*4] = 255 - rgba[0 + x*4 + y*W*4]
rgba[1 + x*4 + y*W*4] = 255 - rgba[1 + x*4 + y*W*4]
rgba[2 + x*4 + y*W*4] = 255 - rgba[2 + x*4 + y*W*4]
rgba[3 + x*4 + y*W*4] = 255
}
}
})
})
}
},

'recode_original': (W, H, stride, Voffset, Uoffset, yuv, rgba) => {
for (let y = 0; y < H; y++) {
const yUV = (y >> 1) * stride
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