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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<title>Image Segmentation</title>
<link rel="icon" type="image/x-icon" href="favicon.png" />
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width" />
<script type="text/javascript">
const utf8_decoder = new TextDecoder();
function c_strlen(mem, ptr) {
let len = 0;
while (mem[ptr++]) len++;
return len;
}
function c_string(buffer, ptr) {
const mem = new Uint8Array(buffer);
const len = c_strlen(mem, ptr);
const bytes = new Uint8Array(buffer, ptr, len);
return utf8_decoder.decode(bytes);
}
function puts(ptr) {
console.log(c_string(wasm.memory.buffer, ptr));
}
function random_int() {
return parseInt(Math.random() * (1 << 31));
}
if (!WebAssembly.instantiateStreaming) {
WebAssembly.instantiateStreaming = (promise, env) =>
promise
.then((r) => r.arrayBuffer())
.then((bytes) => WebAssembly.instantiate(bytes, env));
}
const wasmFetch = (file) =>
WebAssembly.instantiateStreaming(fetch(file), {
env: {
puts,
random_int,
},
});
const wasmStatus = new Promise((resolve, reject) => {
wasmFetch("main.wasm")
.then((w) => {
window.wasm_ref = w;
window.wasm = w.instance.exports;
window.isSlow = false;
resolve();
})
.catch(() => {
wasmFetch("main-slow.wasm")
.then((w) => {
window.wasm_ref = w;
window.wasm = w.instance.exports;
window.isSlow = true;
resolve();
})
.catch((err) => {
console.error(err);
reject();
});
});
});
</script>
<style>
body {
background-color: beige;
}
input {
font-family: inherit;
}
.alg {
display: flex;
flex-direction: column;
align-items: center;
}
.alg h2 {
margin-bottom: 5px;
}
.alg div {
margin: 5px;
}
.alg canvas,
.alg img {
border: 5px solid black;
border-radius: 10px;
margin: 10px;
}
.row {
display: flex;
flex-wrap: wrap;
align-items: center;
justify-content: center;
}
.alert {
padding: 20px;
background-color: #ff9800;
color: white;
margin-bottom: 15px;
display: none;
justify-content: center;
font-size: 2em;
border: 2px solid #965a00;
text-align: center;
position: sticky;
top: 0px;
}
@media (max-width: 786px) {
.alert {
font-size: 1em;
padding: 10px;
}
}
.view-code {
padding: 10px;
background-color: beige;
color: white;
margin-bottom: 5px;
font-size: 1em;
border: 2px solid #0d0582;
position: fixed;
bottom: 0;
display: flex;
}
img {
width: min(400px, 80vw);
height: auto;
}
</style>
</head>
<body>
<div id="warn" class="alert">
Because this browser does not support the optimized build,
computation time may be slower than expected.
</div>
<h1 style="text-align: center; margin-top: 20px">
Image Segmentation Methods Comparison
</h1>
<div class="row" style="justify-content: space-evenly">
<div style="display: flex; flex-direction: column">
<div class="alg" id="source">
<h2>Source</h2>
<div>
<label> Source: <input type="file" /> </label>
</div>
<img
src="source.webp"
width="400"
height="268"
alt="source"
/>
</div>
<div style="width: min(400px, 80vw)">
<p>
<em>
Collection of image segmentation techniques written
in C and compiled to WebAssembly. Computation time
in parentheses.
</em>
</p>
<p>
Digital images use gamma encodings to store luminance.
Gamma correction can make image luminance appear more
realistic.
<label>
<input
type="checkbox"
id="gamma"
name="gamma"
checked="true"
/>
use gamma correction
</label>
</p>
<p>
<b>K-Means:</b> A randomized clustering algorithm to
group pixels into K groups based on Euclidean distance
between RGB values. A higher K leads to more detailed
results.
</p>
<p>
<b>Mean Shift:</b> A hill climbing algorithm to
iteratively find local maxima. The kernel size controls
the sensitivity to smaller modes. The least two
significant bits are dropped from each color component.
</p>
<p>
<b>Split & Merge:</b> A two stage algorithm to split an
image into homogenous regions (by subdividing
nonhomogeneous blocks into quadrants) and then merge
similar neighboring blocks into groups. The tolerance
controls the threshold at which blocks are deemed
homogenous.
</p>
<p>
<b>Balanced Histogram Thresholding:</b> An automatic
thresholding method that divides the color space by
finding the midpoint of an RGB histogram.
</p>
</div>
</div>
<div
style="
display: flex;
flex-direction: column;
justify-content: space-evenly;
align-items: center;
"
>
<div class="row">
<div class="alg" id="kmeans">
<h2>K-Means</h2>
<div>
<label>
K:
<input
type="number"
value="3"
min="2"
max="25"
/>
</label>
<input
type="number"
value="200"
style="display: none"
/>
</div>
<canvas></canvas>
</div>
<div class="alg" id="meanshift">
<h2>Mean Shift</h2>
<div>
<label>
Kernel Size:
<input
type="number"
value="4"
min="1"
max="25"
/>
</label>
<input
type="number"
value="100"
style="display: none"
/>
</div>
<canvas></canvas>
</div>
</div>
<div class="row">
<div class="alg" id="split_and_merge">
<h2>Split & Merge</h2>
<div>
<label>
Tolerance:
<input
type="number"
value="200"
min="50"
max="350"
step="10"
/>
</label>
</div>
<canvas></canvas>
</div>
<div class="alg" id="histogram">
<h2>Balanced Histogram Thresholding</h2>
<div>
<label>no parameters</label>
</div>
<canvas style="margin-top: 13px"></canvas>
</div>
</div>
</div>
</div>
<div class="view-code">
<a
href="https://github.com/inventshah/image-segmentation"
target="_blank"
>
view code
</a>
</div>
<script type="text/javascript">
function load(source) {
for (const elm of document.getElementsByTagName("canvas")) {
if (
elm.width === source.width &&
elm.height === source.height
)
continue;
elm.width = source.width;
elm.height = source.height;
run_alg(elm.parentElement.id);
}
}
const source = document.querySelector("img");
source.onload = () => {
window.width = parseInt(source.width);
window.height = parseInt(source.height);
load(source);
};
window.addEventListener("resize", () => {
window.width = parseInt(source.width);
window.height = parseInt(source.height);
load(source);
});
function run_alg(alg) {
if (window.wasm == undefined || window.width == undefined)
return;
const container = document.getElementById(alg);
const canvas = container.getElementsByTagName("canvas")[0];
const ctx = canvas.getContext("2d");
ctx.drawImage(source, 0, 0, width, height);
const args = [...container.getElementsByTagName("input")].map(
(elm) => +elm.value
);
const img_ptr = wasm.malloc(width * height * 4);
const data = ctx.getImageData(0, 0, width, height).data;
const bytes = new Uint8ClampedArray(
wasm.memory.buffer,
img_ptr,
width * height * 4
);
bytes.set(data);
const title = container.getElementsByTagName("h2")[0].innerText;
const name = title.replace(/ \(.*\)$/, "");
try {
const start = performance.now();
wasm[alg](img_ptr, width, height, ...args);
wasm.memory_reset();
const end = performance.now();
container.getElementsByTagName(
"h2"
)[0].innerHTML = `${name} <span style="font-size: .8em"> <em> (${Math.round(
end - start
)} ms)</em> </span>`;
} catch (err) {
container.getElementsByTagName(
"h2"
)[0].innerText = `${name} (error)`;
console.error(err);
}
const imageData = ctx.getImageData(0, 0, width, height);
imageData.data.set(
new Uint8ClampedArray(
wasm.memory.buffer,
img_ptr,
width * height * 4
)
);
ctx.putImageData(imageData, 0, 0);
}
function* alg_iter() {
for (const elm of document.getElementsByClassName("alg")) {
if (elm.id == "source") continue;
yield elm;
}
}
document.getElementById("gamma").onchange = (e) => {
wasm.change_gamma_status(e.target.checked ? 1 : 0);
for (const elm of alg_iter()) run_alg(elm.id);
};
document.querySelector('input[type="file"]').onchange = (e) => {
console.log(e.target.files);
if (!e.target.files) return;
source.src = URL.createObjectURL(e.target.files[0]);
};
for (const elm of alg_iter()) {
for (const input of elm.getElementsByTagName("input")) {
input.onchange = () => {
run_alg(elm.id);
};
}
const canvas = elm.getElementsByTagName("canvas")[0];
canvas.onclick = () => run_alg(elm.id);
}
window.onload = () =>
wasmStatus.then(() => {
if (window.isSlow == true) {
document.getElementById("warn").style.display = "flex";
setTimeout(() => {
for (const elm of alg_iter()) run_alg(elm.id);
}, 50);
} else {
for (const elm of alg_iter()) run_alg(elm.id);
}
});
</script>
</body>
</html>