1 files changed, 90 insertions, 0 deletions
diff --git a/testing/web-platform/tests/shape-detection/detected-postMessage.https.html b/testing/web-platform/tests/shape-detection/detected-postMessage.https.html
new file mode 100644
index 0000000000..8066984b26
--- /dev/null
+++ b/testing/web-platform/tests/shape-detection/detected-postMessage.https.html
@@ -0,0 +1,90 @@
+<!DOCTYPE html>
+<script src="/resources/testharness.js"></script>
+<script src="/resources/testharnessreport.js"></script>
+<script src="resources/shapedetection-helpers.js"></script>
+<script>
+
+// These tests verify that Detected{Face, Barcode, Text} can be passed to
+// postMessage().
+const postMessageTests =
+    [
+      {
+        createDetector: () => { return new FaceDetector(); },
+        mockTestName: "FaceDetectionTest",
+        detectionResultTest: FaceDetectorDetectionResultTest,
+        name: "Face - DetectedFace can be passed to postMessage()"
+      },
+      {
+        createDetector: () => { return new BarcodeDetector(); },
+        mockTestName: "BarcodeDetectionTest",
+        detectionResultTest: BarcodeDetectorDetectionResultTest,
+        name: "Barcode - DetectedBarcode can be passed to postMessage()"
+      },
+      {
+        createDetector: () => { return new TextDetector(); },
+        mockTestName: "TextDetectionTest",
+        detectionResultTest: TextDetectorDetectionResultTest,
+        name: "Text - DetectedText can be passed to postMessage()",
+      },
+    ];
+
+for (let postMessageTest of postMessageTests) {
+  detection_test(postMessageTest.mockTestName, async t => {
+    const img = new Image();
+    const imgWatcher = new EventWatcher(t, img, ["load", "error"]);
+    img.src = "/images/green-16x16.png";
+    await imgWatcher.wait_for("load");
+
+    const canvas = document.createElement("canvas");
+    canvas.getContext("2d").drawImage(img, 0, 0);
+
+    const detector = postMessageTest.createDetector();
+    const detectionResult = await detector.detect(canvas.getContext("2d")
+        .getImageData(0, 0, canvas.width, canvas.height));
+
+    const msgWatcher = new EventWatcher(t, window, ['message']);
+    window.postMessage(detectionResult);
+    const evt = await msgWatcher.wait_for('message');
+    postMessageTest.detectionResultTest(evt.data)
+  }, postMessageTest.name);
+}
+
+function FaceDetectorDetectionResultTest(detectionResult) {
+  assert_equals(detectionResult.length, 3, "Number of faces");
+  assert_equals(detectionResult[0].landmarks.length, 2, "Number of landmarks");
+  assert_object_equals(detectionResult[0].landmarks[0],
+                      {type : 'eye', locations : [{x : 4.0, y : 5.0}]},
+                      "landmark #1");
+  assert_equals(detectionResult[0].landmarks[1].locations.length, 8,
+                "Number of locations along eye");
+  assert_object_equals(detectionResult[1].landmarks[0],
+                      {type : 'nose', locations : [{x : 100.0, y : 50.0}]},
+                      "landmark #2");
+  assert_equals(detectionResult[1].landmarks[1].locations.length, 9,
+                "Number of locations along nose");
+}
+
+function BarcodeDetectorDetectionResultTest(detectionResult) {
+  assert_equals(detectionResult.length, 2, "Number of barcodes");
+  assert_equals(detectionResult[0].rawValue, "cats", "barcode 1");
+  assert_equals(detectionResult[0].format, "qr_code", "barcode 1 format");
+  assert_equals(detectionResult[1].rawValue, "dogs", "barcode 2");
+  assert_equals(detectionResult[1].format, "code_128", "barcode 2 format");
+}
+
+function TextDetectorDetectionResultTest(detectionResult) {
+  assert_equals(detectionResult.length, 2, "Number of textBlocks");
+  assert_equals(detectionResult[0].rawValue, "cats", "textBlock 1");
+  assert_equals(detectionResult[1].rawValue, "dogs", "textBlock 2");
+  for (let i = 0; i < detectionResult.length; i++) {
+    assert_equals(detectionResult[i].boundingBox.x, detectionResult[i].cornerPoints[0].x);
+    assert_equals(detectionResult[i].boundingBox.y, detectionResult[i].cornerPoints[0].y);
+    assert_equals(detectionResult[i].boundingBox.width,
+                  detectionResult[i].cornerPoints[2].x - detectionResult[i].cornerPoints[3].x);
+    assert_equals(detectionResult[i].boundingBox.height,
+                  detectionResult[i].cornerPoints[2].y - detectionResult[i].cornerPoints[1].y);
+  }
+
+}
+
+</script>