所以我理解为了跟踪图像,我们需要创建一个AR资源文件夹并放置我们打算在那里跟踪的所有图像,以及通过检查器配置它们的真实世界大小属性。
然后我们将ARReferenceImages数组设置为Session的World Config。
一切都很好。 但我们可以跟踪多少? 10? 100?百万?是否可以下载这些图像并动态创建ARReferences,而不是从一开始就将它们放在捆绑中?
答案 0 :(得分:5)
查看Apple Docs
它似乎没有指定限制。因此,可能会认为它可能取决于内存管理等。
关于动态创建图像,这绝对是可能的。
根据文档,这可以通过以下两种方式之一完成:
从Core Graphics图像对象创建新的参考图像:
init(CGImage, orientation: CGImagePropertyOrientation, physicalWidth: CGFloat)
从核心视频像素缓冲区创建新的参考图像:
init(CVPixelBuffer, orientation: CGImagePropertyOrientation, physicalWidth: CGFloat)
以下是使用标准 referenceImage
中的图像动态创建Assets Bundle
的示例,尽管这可以很容易地用于解析来自{的图像{1}}等:
URL
然后我们可以在// Create ARReference Images From Somewhere Other Than The Default Folder
func loadDynamicImageReferences(){
//1. Get The Image From The Folder
guard let imageFromBundle = UIImage(named: "moonTarget"),
//2. Convert It To A CIImage
let imageToCIImage = CIImage(image: imageFromBundle),
//3. Then Convert The CIImage To A CGImage
let cgImage = convertCIImageToCGImage(inputImage: imageToCIImage)else { return }
//4. Create An ARReference Image (Remembering Physical Width Is In Metres)
let arImage = ARReferenceImage(cgImage, orientation: CGImagePropertyOrientation.up, physicalWidth: 0.2)
//5. Name The Image
arImage.name = "CGImage Test"
//5. Set The ARWorldTrackingConfiguration Detection Images Assuming A Configuration Is Running
configuration.detectionImages = [arImage]
}
/// Converts A CIImage To A CGImage
///
/// - Parameter inputImage: CIImage
/// - Returns: CGImage
func convertCIImageToCGImage(inputImage: CIImage) -> CGImage? {
let context = CIContext(options: nil)
if let cgImage = context.createCGImage(inputImage, from: inputImage.extent) {
return cgImage
}
return nil
}
内进行测试,例如
ARSCNViewDelegate
正如您所看到的那样,过程非常简单。因此,在您的情况下,您可能对上面使用此方法创建动态图像的转换函数更感兴趣:
func renderer(_ renderer: SCNSceneRenderer, didAdd node: SCNNode, for anchor: ARAnchor) {
//1. If Out Target Image Has Been Detected Than Get The Corresponding Anchor
guard let currentImageAnchor = anchor as? ARImageAnchor else { return }
let x = currentImageAnchor.transform
print(x.columns.3.x, x.columns.3.y , x.columns.3.z)
//2. Get The Targets Name
let name = currentImageAnchor.referenceImage.name!
//3. Get The Targets Width & Height In Meters
let width = currentImageAnchor.referenceImage.physicalSize.width
let height = currentImageAnchor.referenceImage.physicalSize.height
print("""
Image Name = \(name)
Image Width = \(width)
Image Height = \(height)
""")
//4. Create A Plane Geometry To Cover The ARImageAnchor
let planeNode = SCNNode()
let planeGeometry = SCNPlane(width: width, height: height)
planeGeometry.firstMaterial?.diffuse.contents = UIColor.white
planeNode.opacity = 0.25
planeNode.geometry = planeGeometry
//5. Rotate The PlaneNode To Horizontal
planeNode.eulerAngles.x = -.pi/2
//The Node Is Centered In The Anchor (0,0,0)
node.addChildNode(planeNode)
//6. Create AN SCNBox
let boxNode = SCNNode()
let boxGeometry = SCNBox(width: 0.1, height: 0.1, length: 0.1, chamferRadius: 0)
//7. Create A Different Colour For Each Face
let faceColours = [UIColor.red, UIColor.green, UIColor.blue, UIColor.cyan, UIColor.yellow, UIColor.gray]
var faceMaterials = [SCNMaterial]()
//8. Apply It To Each Face
for face in 0 ..< 5{
let material = SCNMaterial()
material.diffuse.contents = faceColours[face]
faceMaterials.append(material)
}
boxGeometry.materials = faceMaterials
boxNode.geometry = boxGeometry
//9. Set The Boxes Position To Be Placed On The Plane (node.x + box.height)
boxNode.position = SCNVector3(0 , 0.05, 0)
//10. Add The Box To The Node
node.addChildNode(boxNode)
}
答案 1 :(得分:4)
将Human Interface Guidelines解释为AR ...图像检测性能/准确度随着图像数量的增加而恶化。因此API中没有硬性限制,但如果您尝试在当前检测集中放置超过25个图像,它将开始到达它太慢/不准确无用的地方。
还有很多其他因素影响性能/准确性,因此请考虑一个指南,而不是硬限制。根据您运行应用程序的地方的场景条件,您对其他任务施加压力的程度,参考图像彼此之间的差异等等,您可能会管理超过25个......或者开始有少于25的检测问题。