@@ -10,7 +10,7 @@ window.addEventListener("DOMContentLoaded", () => {
10
10
} ) ;
11
11
12
12
/**
13
- * @typedef {Object } TextRecognitionResult
13
+ * @typedef {object } TextRecognitionResult
14
14
* @property {number } confidence
15
15
* @property {string } string
16
16
* @property {DOMQuad } quad
@@ -19,8 +19,11 @@ window.addEventListener("DOMContentLoaded", () => {
19
19
class TextRecognitionModal {
20
20
/**
21
21
* @param {Promise<TextRecognitionResult[]> } resultsPromise
22
- * @param {() => {} } resizeVertically
23
- * @param {(url: string, where: string, params: Object) => {} } openLinkIn
22
+ * @param {Function } resizeVertically
23
+ * @param {object } [openLinkIn]
24
+ * @param {string } openLinkIn.url
25
+ * @param {string } openLinkIn.where
26
+ * @param {object } openLinkIn.params
24
27
*/
25
28
constructor ( resultsPromise , resizeVertically , openLinkIn ) {
26
29
/** @type {HTMLElement } */
@@ -114,6 +117,7 @@ class TextRecognitionModal {
114
117
115
118
/**
116
119
* After the results are shown, measure how long a user interacts with the modal.
120
+ *
117
121
* @param {number } textLength
118
122
*/
119
123
static recordTextLengthTelemetry ( textLength ) {
@@ -241,7 +245,7 @@ class TextRecognitionModal {
241
245
/**
242
246
* A two dimensional vector.
243
247
*
244
- * @typedef {[ number, number ] } Vec2
248
+ * @typedef {number[ ] } Vec2
245
249
*/
246
250
247
251
/**
@@ -357,7 +361,7 @@ function densityCluster(points, distance, minPoints) {
357
361
/**
358
362
* @param {Vec2[] } points
359
363
* @param {number } distance
360
- * @param {number } index,
364
+ * @param {number } index
361
365
* @returns {Index[] }
362
366
*/
363
367
function getNeighborsWithinDistance ( points , distance , index ) {
0 commit comments