<script src="https://cdn.jsdelivr.net/npm/skeleton-tracing-wasm/build/trace_skeleton_wasm.js"></script>
const TraceSkeleton = require('skeleton-tracing-wasm')
import TraceSkeleton from 'skeleton-tracing-wasm'
You first need to initiate/load the wasm module calling a static method load()
const tracer = await TraceSkeleton.load()
then you can use the API methods
const { polylines,rects } = tracer.fromCanvas(HTMLCANVAS)
Or instead of async/await you can do
TraceSkeleton.load().then(tracer => {
// wasm module loaded
// here is your code
const { polylines,rects } = tracer.fromCanvas(HTMLCANVAS)
})
The below API's take an image representation and returns an object holding the polylines as well as rects processed by the algorithm (the latter is mainly for visualization)
{
"polylines": [[[x,y],[x,y]],[[x,y],[x,y],[x,y],...],...],
"rects": [[x,y,w,h],[x,y,w,h],...]
}
Takes in an HTML Canvas object and returns the skeleton as polyilnes as well as the rects.
Takes JavaScript ImageData object (e.g. document.createElement("canvas").getContext('2d').getImageData(0,0,100,100)
)
Takes array of booleans (or truthy and falsy values), e.g. [0,1,0,1,1,1,0,0,...]
or [0,255,255,0,...]
or [true,false,true,false,...]
or even [undefined, "ok", null, "yes", ...]
Takes in a (char*)
such as "\0\1\0\0\1\1\0...."
. This is the fastest (though probably most obscure) API because it does not need to translate the input to C constructs.
Conveniently visualize the result from the previous functions, returns a string holding an SVG (scalable vector graphics).
Options:
scale
: factor to scale the drawingrects
: draw the rects?keypoints
: draw the keypoints on the polylines?strokeWidth
: weight of the polyline strokes.
See /index.html
for more detailed usage example, with animation, interactivity, webcam, etc.
https://skeleton-tracing.netlify.app/
Developed at Frank-Ratchye STUDIO for Creative Inquiry at Carnegie Mellon University.