extractImageData = (image) => {
const width = image.naturalWidth; // retrieves the image's width
const height = image.naturalHeight; // retrieves the image's height
const context = DOM.context2d(width, height, 1); // create a canvas
context.drawImage(image, 0, 0); // draw the image
const {data} = context.getImageData(0, 0, width, height); // extract pixel data. this will return an array with a length = width * height (pixels) * 4 (it's four because by default, it's providing the red, green, blue and alpha value for each pixel)
// This is for the bins that we will use to group pixel colors together
const range = d3.range(0, 1, 1 / nBins);
// The Quantize Scale allows us to bin values. The domain is set to the [0, 255], the extent of values for RGBA (red, green, blue, alpha)
const bins = ({
r: d3.scaleQuantize().domain([0, 255]).range(range),
g: d3.scaleQuantize().domain([0, 255]).range(range),
b: d3.scaleQuantize().domain([0, 255]).range(range),
})
const pixelData = []; // create an empty array
let r = 0, g = 0, b = 0, a = 0;
for (let i = 0; i < data.length; i += 4) { // For every four datapoints = RGBA
r = data[i + 0];
g = data[i + 1];
b = data[i + 2];
a = data[i + 3];
const rgba = `rgba(${r}, ${g}, ${b}, ${a})`; // Get RGBA value
const hsl = d3.hsl(rgba); // Get HSL value
const rBin = bins.r(r); // Bin R
const gBin = bins.g(g); // Bin G
const bBin = bins.b(b); // Bin B
const rgbBinColor = d3.rgb(bins.r.invertExtent(rBin)[0],bins.g.invertExtent(gBin)[0], bins.b.invertExtent(bBin)[0]) // Create new color from the binned values
pixelData.push({ // Push all the data
r: r,
g: g,
b: b,
a: a,
h: hsl.h,
s: hsl.s,
l: hsl.l,
rgba: rgba,
hex: d3.color(rgba).hex(),
hsl: hsl,
rBin: rBin,
gBin: gBin,
bBin: bBin,
rgbBinR: rgbBinColor.r,
rgbBinG: rgbBinColor.g,
rgbBinB: rgbBinColor.b,
rgbBinColor: rgbBinColor.toString()
})
}
return {
width: width,
height: height,
pixelData: pixelData
}
}
imagePixelData = extractImageData(image)
lcolor = d3.lab("#ff0000")
imagePixelData.pixelData[0]
d3.lab("#ff0000")
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