one_dollar_unistroke_recognizer 0.6.1 one_dollar_unistroke_recognizer: ^0.6.1 copied to clipboard
The $1 Unistroke Recognizer, a 2D single-stroke recognizer. This is a Dart port of the original JavaScript implementation.
A Dart port of the $1 Unistroke Recognizer, with some additional features planned.
Usage #
Basic usage
final points = <Offset>[...];
final recognized = recognizeUnistroke(points);
if (recognized == null) {
print('No match found');
} else {
// e.g. DefaultUnistrokeNames.circle
print('Stroke recognized as ${recognized.name}');
}
Protractor enhancement
The Protractor enhancement is enabled by default. You can disable it by setting useProtractor
to false
.
final recognized = recognizeUnistroke(
points,
useProtractor: false,
);
Getting the "perfect" (canonical) shape
You can get a "perfect" shape from the user's stroke by calling one of the following methods on the RecognizedUnistroke
object:
convertToCanonicalPolygon()
: Returns the closest template match, scaled and translated to match the input gesture. Note that this method returns a list of points, instead of a perfect circle or rectangle like the other methods. (Shown in 🔴red in the examples below.)convertToLine()
: Returns the first and last input points. (Shown in 🟠orange in the examples below.)convertToCircle()
: Returns the radius and center of the best-fit circle. (Shown in 🔵blue in the examples below.)convertToOval()
: The same asconvertToCircle()
but doesn't take the average of the width and height. (Not shown in the examples below.)convertToRect()
: Returns theRect
of the best-fit (bounding box) rectangle. Tip: you can round the corners of the Rect withRRect.fromRectAndRadius
. (Shown in 🟢green in the examples below.)
Line | Circle | Rectangle | Triangle |
---|---|---|---|
final recognized = recognizeUnistroke(points);
switch (recognized?.name) {
case null:
break;
case DefaultUnistrokeNames.line:
final (start, end) = recognized!.convertToLine();
canvas.drawLine(start, end, paint);
case DefaultUnistrokeNames.circle:
final (center, radius) = recognized!.convertToCircle();
canvas.drawCircle(center, radius, paint);
case DefaultUnistrokeNames.rectangle:
final rect = recognized!.convertToRect();
if (youWantARoundedRectangle) {
canvas.drawRRect(
RRect.fromRectAndRadius(rect, Radius.circular(10)),
paint,
);
} else {
canvas.drawRect(rect, paint);
}
case DefaultUnistrokeNames.triangle:
final polygon = recognized!.convertToCanonicalPolygon();
canvas.drawPoints(PointMode.polygon, polygon, paint);
}
Using custom unistroke templates
You can recognize custom unistrokes by setting the referenceUnistrokes
list.
Note that this will disable the default unistroke templates defined in default$1Unistrokes
.
If your key type isn't DefaultUnistrokeNames
, you'll need to call
recognizeUnistrokeOfType<MyKey>(...)
instead of recognizeUnistroke()
.
referenceUnistrokes = <Unistroke<MyUnistrokeNames>>[
Unistroke(MyUnistrokeNames.circle, [...]),
Unistroke(MyUnistrokeNames.rectangle, [...]),
Unistroke(MyUnistrokeNames.triangle, [...]),
Unistroke(MyUnistrokeNames.leaf, [...]),
];
enum MyUnistrokeNames {
circle,
rectangle,
triangle,
leaf,
}
final recognized = recognizeUnistrokeOfType<MyUnistrokeNames>(points);
Alternatively, you can temporarily override the referenceUnistrokes
list for a single call to recognizeUnistroke
by setting the overrideReferenceUnistrokes
list.
final recognized = recognizeUnistrokeOfType<MyUnistrokeNames>(
points,
overrideReferenceUnistrokes: [...],
);
You could also set referenceUnistrokes
to example$1Unistrokes
to use the templates that were originally defined in the paper, though they're not very pretty and were probably intended to just be a proof-of-concept. (The key type for example$1Unistrokes
is String
.)
About the $1 Unistroke Recognizer #
The $1 Unistroke Recognizer is a 2-D single-stroke recognizer designed for rapid prototyping of gesture-based user interfaces. In machine learning terms, $1 is an instance-based nearest-neighbor classifier with a 2-D Euclidean distance function, i.e., a geometric template matcher. $1 is a significant extension of the proportional shape matching approach used in SHARK2, which itself is an adaptation of Tappert's elastic matching approach with zero look-ahead. Despite its simplicity, $1 requires very few templates to perform well and is only about 100 lines of code, making it easy to deploy. An optional enhancement called Protractor improves $1's speed.
You can read more about the $1 Unistroke Recognizer at depts.washington.edu/acelab/proj/dollar.
This Dart package is a port of the JavaScript version of the $1 Unistroke Recognizer, which you can find at depts.washington.edu/acelab/proj/dollar/dollar.js.