Public
Edited
Dec 16, 2023
apple_result = {
// Sampled middle-most colors of each image
const colors = [[179,63,48],[167,207,103],[252,219,3],[44,42,66]]
const curr = Number(apple[6])-1
// Computing max distance excluding a selected apple
var max = -1
for (let i = 0; i < colors.length; i++) {
if (i != curr){
for (let j = 0; j < colors.length; j++) {
if (j != curr && j != i) {
const val = (colors[i][0]-colors[j][0])**2 + (colors[i][1]-colors[j][1])**2 + (colors[i][2]-colors[j][2])**2
if (val > max){
max = val
}
}
}
}
}
// Checking whether or not the test apple falls within the range
for (let i = 0; i < colors.length; i++){
const val = (colors[i][0]-colors[curr][0])**2 + (colors[i][1]-colors[curr][1])**2 + (colors[i][2]-colors[curr][2])**2
if (val > max){
return "Apple "+(curr+1)+" is not an apple."
}
}
return "Apple "+(curr+1)+" is an apple."
}
{
const image = await FileAttachment("splay_test6@1.jpeg").image()
const canvas = DOM.canvas(image.width, image.height);
const data = cv.imread(image);
cv.cvtColor(data, data, cv.COLOR_RGB2HLS);
const ksize = {width : 2, height : 2};
var rgb = hexToRgb(color)
// NOTE THESE VALUES ARE BGR NOT RGB
// Lower-bound Skin Color
const l_skin = cv.matFromArray(1,3, cv.CV_8UC1, [0, 30, 50])
// Upper-bound Skin Color
const u_skin = cv.matFromArray(1,3, cv.CV_8UC1, [rgb.b,rgb.g+30,rgb.r+30])
// Computing skin threshold
const skin_threshold = new cv.Mat();
// Selecting all pixels in that threshold
cv.inRange(data, l_skin, u_skin,data)
// Blurring the hand
cv.blur(data,data, ksize)
cv.imshow(canvas,data)
data.delete();
return sideBySide(image,canvas)
}
{
const image = await FileAttachment("splay_test6@1.jpeg").image()
const canvas = DOM.canvas(image.width, image.height);
const img = cv.imread(image);
const data = img.clone();
cv.cvtColor(data, data, cv.COLOR_RGB2HLS);
const ksize = {width : 2, height : 2};
var rgb = hexToRgb(color)
// NOTE THESE VALUES ARE BGR NOT RGB
// Lower-bound Skin Color
const l_skin = cv.matFromArray(1,3, cv.CV_8UC1, [0, 30, 50])
// Upper-bound Skin Color
const u_skin = cv.matFromArray(1,3, cv.CV_8UC1, [165,218,246])
// Computing skin threshold
const skin_threshold = new cv.Mat();
// Selecting all pixels in that threshold
cv.inRange(data, l_skin, u_skin,data)
// Blurring the hand
cv.blur(data,data, ksize)
// ----------------------- NEW -----------------------
const offset = cv.Point(0,0)
let contours = new cv.MatVector();
let hierarchy = new cv.Mat();
// Extracting the contours
cv.findContours(data,contours,hierarchy,cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
// Drawing them on photo for visual representation
cv.drawContours(img, contours, -1, [255,0,0,255], 10, cv.LINE_8, hierarchy, 100)
cv.imshow(canvas,img)
data.delete();
return sideBySide(image,canvas)
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
