如需通过蓝牙传输功能发送来自其他设备的录音等大型对象,您可以将 Asset
附加到数据项,然后将数据项放入重复数据存储区。
资源会自动处理数据的缓存,以防止重新传输,并节省蓝牙带宽。对于手持设备应用来说,一种常见模式是,下载图片,将其缩小到适合在穿戴式设备上显示的尺寸,然后将其作为资源传输到穿戴式应用。以下示例演示了这一模式。
注意:虽然理论上数据项大小上限为 100 KB,但实际上,您可以使用更大的数据项。对于更大的数据项,请将数据分隔到专属路径,并避免对所有数据使用一条路径。不过,在许多情况下,传输大型资源会影响用户体验,因此请测试您的应用,以便确保应用在传输大型资源时能够保持良好的性能。
传输资源
使用 Asset
类中的一个 create...()
方法创建资源。将一个位图转换成字节流,然后调用 createFromBytes()
来创建资源,如以下示例所示。
Kotlin
private fun createAssetFromBitmap(bitmap: Bitmap): Asset = ByteArrayOutputStream().let { byteStream -> bitmap.compress(Bitmap.CompressFormat.PNG, 100, byteStream) Asset.createFromBytes(byteStream.toByteArray()) }
Java
private static Asset createAssetFromBitmap(Bitmap bitmap) { final ByteArrayOutputStream byteStream = new ByteArrayOutputStream(); bitmap.compress(Bitmap.CompressFormat.PNG, 100, byteStream); return Asset.createFromBytes(byteStream.toByteArray()); }
接下来,使用 DataMap
或 PutDataRequest
中的 putAsset()
方法将资源附加到数据项。然后,使用 putDataItem()
方法将数据项放入数据存储区,如以下示例所示。
Kotlin
val asset: Asset = BitmapFactory.decodeResource(resources, R.drawable.image).let { bitmap -> createAssetFromBitmap(bitmap) } val request: PutDataRequest = PutDataRequest.create("/image").apply { putAsset("profileImage", asset) } val putTask: Task<DataItem> = Wearable.getDataClient(context).putDataItem(request)
Java
Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.image); Asset asset = createAssetFromBitmap(bitmap); PutDataRequest request = PutDataRequest.create("/image"); request.putAsset("profileImage", asset); Task<DataItem> putTask = Wearable.getDataClient(context).putDataItem(request);
Kotlin
val asset: Asset = BitmapFactory.decodeResource(resources, R.drawable.image).let { bitmap -> createAssetFromBitmap(bitmap) } val request: PutDataRequest = PutDataMapRequest.create("/image").run { dataMap.putAsset("profileImage", asset) asPutDataRequest() } val putTask: Task<DataItem> = Wearable.getDataClient(context).putDataItem(request)
Java
Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.image); Asset asset = createAssetFromBitmap(bitmap); PutDataMapRequest dataMap = PutDataMapRequest.create("/image"); dataMap.getDataMap().putAsset("profileImage", asset); PutDataRequest request = dataMap.asPutDataRequest(); Task<DataItem> putTask = Wearable.getDataClient(context).putDataItem(request);
接收资源
创建资源后,您可能需要在连接的另一端读取并提取该资源。以下示例说明了如何实现回调来检测资源变化并提取资源:
Kotlin
override fun onDataChanged(dataEvents: DataEventBuffer) { dataEvents .filter { it.type == DataEvent.TYPE_CHANGED && it.dataItem.uri.path == "/image" } .forEach { event -> val bitmap: Bitmap? = DataMapItem.fromDataItem(event.dataItem) .dataMap.getAsset("profileImage") .let { asset -> loadBitmapFromAsset(asset) } // Do something with the bitmap } } fun loadBitmapFromAsset(asset: Asset): Bitmap? { // Convert asset into a file descriptor and block until it's ready val assetInputStream: InputStream? = Tasks.await(Wearable.getDataClient(context).getFdForAsset(asset)) ?.inputStream return assetInputStream?.let { inputStream -> // Decode the stream into a bitmap BitmapFactory.decodeStream(inputStream) } ?: run { Log.w(TAG, "Requested an unknown Asset.") null } }
Java
@Override public void onDataChanged(DataEventBuffer dataEvents) { for (DataEvent event : dataEvents) { if (event.getType() == DataEvent.TYPE_CHANGED && event.getDataItem().getUri().getPath().equals("/image")) { DataMapItem dataMapItem = DataMapItem.fromDataItem(event.getDataItem()); Asset profileAsset = dataMapItem.getDataMap().getAsset("profileImage"); Bitmap bitmap = loadBitmapFromAsset(profileAsset); // Do something with the bitmap } } } public Bitmap loadBitmapFromAsset(Asset asset) { if (asset == null) { throw new IllegalArgumentException("Asset must be non-null"); } // Convert asset into a file descriptor and block until it's ready InputStream assetInputStream = Tasks.await(Wearable.getDataClient(context).getFdForAsset(asset)) .getInputStream(); if (assetInputStream == null) { Log.w(TAG, "Requested an unknown Asset."); return null; } // Decode the stream into a bitmap return BitmapFactory.decodeStream(assetInputStream); }
如需了解详情,请参阅 GitHub 上的 DataLayer 示例项目。