I'm using the "Converting side-by-side 3D video to multiview HEVC and spatial video" sample code on iOS. It takes about 8 seconds to convert a 6-second video. At this rate, a 1-hour video would take 1.3 hours to convert. How can I speed up the conversion? BTW, are there solutions to convert side-by-side 3D video to spatial video for Windows?

I want to try an any resolution image input Core ML model. So I wrote the model following the Core ML Tools "Set the Range for Each Dimensionas" sample code, modified as below: # Trace the model with random input. example_input = torch.rand(1, 3, 50, 50) traced_model = torch.jit.trace(model.eval(), example_input) # Set the input_shape to use RangeDim for each dimension. input_shape = ct.Shape(shape=(1, 3, ct.RangeDim(lower_bound=25, upper_bound=1920, default=45), ct.RangeDim(lower_bound=25, upper_bound=1920, default=45))) scale = 1/(0.226*255.0) bias = [- 0.485/(0.229) , - 0.456/(0.224), - 0.406/(0.225)] # Convert the model with input_shape. mlmodel = ct.convert(traced_model, inputs=[ct.ImageType(shape=input_shape, name="input", scale=scale, bias=bias)], outputs=[ct.TensorType(name="output")], convert_to="mlprogram", ) # Save the Core ML model mlmodel.save("image_resize_model.mlpackage") It converts OK but when I predict the result with an image It will get the error as below: You will not be able to run predict() on this Core ML model. Underlying exception message was: { NSLocalizedDescription = "Failed to build the model execution plan using a model architecture file '/private/var/folders/8z/vtz02xrj781dxvz1v750skz40000gp/T/model-small.mlmodelc/model.mil' with error code: -7."; } Where did I do wrong?

Hi all, I tried the "isSpatialVideoCaptureEnabled" with AVCaptureMovieFileOutput mentioned in WWDC24: Build compelling spatial photo and video experiences, and it works. But there are some issues and questions: Below codes, the change.newValue always nil so the code seems not work. let observation = videoDevice.observe(\.spatialCaptureDiscomfortReasons) { (device, change) in guard let newValue = change.newValue else { return } if newValue.contains(.subjectTooClose) { // Guide user to move back } if newValue.contains(.notEnoughLight) { // Guide user to find a brighter environment } } AVCaptureMovieFileOutput is support spatial video capturing. May I ask if AVCaptureVideoDataOutput will also support spatial video capturing?

Deploy machine learning and AI models on-device with Core ML say the performance report can see the ops run on which unit and why it cannot run on Neural Engine. I tested my model and the report shows a gray checkmark at the Neural Engine, indicating it can run on the Neural Engine. However, it's not executing on the Neural Engine but on the CPU. Why is this happening?

I just follow the video and add the codes, but when I switch to spatial video capturing, the videoPreviewLayer shows black. <<<< FigCaptureSessionRemote >>>> Fig assert: "! storage->connectionDied" at bail (FigCaptureSessionRemote.m:405) - (err=0) <<<< FigCaptureSessionRemote >>>> captureSessionRemote_getObjectID signalled err=-16405 (kFigCaptureSessionError_ServerConnectionDied) (Server connection was lost) at FigCaptureSessionRemote.m:405 <<<< FigCaptureSessionRemote >>>> Fig assert: "err == 0 " at bail (FigCaptureSessionRemote.m:421) - (err=-16405) <<<< FigCaptureSessionRemote >>>> Fig assert: "msg" at bail (FigCaptureSessionRemote.m:744) - (err=0) Did I miss something?