Hello, I am currently developping an app that counts coins using Computer vision to determine the total value in the picture. However I notice there are no apps in the app store that do anything similar which makes me wonder if there are any restrictions on publishing these types of apps from either apple or governments? I would like to know if it will be possible to launch my app in the European Union once it is finished. Thanks in advance, Guus

I'm developing 3D Scanner works on iPad. I'm using AVCapturePhoto and Photogrammetry Session. photoCaptureDelegate is like below: extension PhotoCaptureDelegate: AVCapturePhotoCaptureDelegate { func photoOutput(_ output: AVCapturePhotoOutput, didFinishProcessingPhoto photo: AVCapturePhoto, error: Error?) { let fileUrl = CameraViewModel.instance.imageDir!.appendingPathComponent("\(PhotoCaptureDelegate.name)\(id).heic") let img = CIImage(cvPixelBuffer: photo.pixelBuffer!, options: [ .auxiliaryDepth: true, .properties: photo.metadata ]) let depthData = photo.depthData!.converting(toDepthDataType: kCVPixelFormatType_DepthFloat32) let colorSpace = CGColorSpace(name: CGColorSpace.sRGB) let fileData = CIContext().heifRepresentation(of: img, format: .RGBA8, colorSpace: colorSpace!, options: [ .avDepthData: depthData ]) try? fileData!.write(to: fileUrl, options: .atomic) } } But, Photogrammetry session spits warning messages: Sample 0 missing LiDAR point cloud! Sample 1 missing LiDAR point cloud! Sample 2 missing LiDAR point cloud! Sample 3 missing LiDAR point cloud! Sample 4 missing LiDAR point cloud! Sample 5 missing LiDAR point cloud! Sample 6 missing LiDAR point cloud! Sample 7 missing LiDAR point cloud! Sample 8 missing LiDAR point cloud! Sample 9 missing LiDAR point cloud! Sample 10 missing LiDAR point cloud! The session creates a usdz 3d model but scale is not correct. I think the point cloud can help Photogrammetry session to find right scale, but I don't know how to attach point cloud.

i saw there is a way to track hands with vision, but is there also a way to record that movement and export it to fbx? Oh and is there a way to set only one hand to be recorded or both at the same time? Implementation will be in SwiftUI

Hi, I have a custom object detection CoreML model and I notice something strange when using the model with the Vision framework. I have tried two different approaches as to how to process an image and do inference on the CoreML model. The first one is using the CoreML "raw": initialising the model, getting the input image ready and using the model's .prediction() function to get the models output. The second one is using Vision to wrap the CoreML model in a VNCoreMLModel, creating a VNCoreMLRequest and using the VNImageRequestHandler to actually perform the model inference. The result of the VNCoreMLRequest is of type VNRecognizedObjectObservation. The issue I now face is in the difference in the output of both methods. The first method gives back the raw output of the CoreML model: confidence and coordinates. The confidence is an array with size equal to the number of classes in my model (3 in my case). The second method gives back the boundingBox, confidence and labels. However here the confidence is only the confidence for the most likely class (so size is equal to 1). But the confidence I get from the second approach is quite different from the confidence I get during the first approach. I can use either one of the approaches in my application. However, I really want to find out what is going on and understand how this difference occurred. Thanks!