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Hello- what was the data set size for labeling for this application? Also how did you train new data on new environment. For example, at different times of day, different shadows, different objects, etc…

Hello All, I am trying to build a Document scanner where I can manually / automatically detect Documents/receipts/letters from the camera and preview it with the respective crop layer just like VNDocumentCameraViewController does. Can someone guide me in the right direction or if anyone has any examples? I have gone through these WWDC links but didn't get good results. https://developer.apple.com/videos/play/wwdc2021/10041/ https://developer.apple.com/videos/play/wwdc2019/234

I'm training a machine learning model in PyTorch using YOLOv5 from Ultralytics. CoreMLTools from Apple is used to convert the PyTorch (.pt) model into a CoreML model (.mlmodel). This works fine, and I can use it in my iOS App, but I have to access the prediction output of the Model manually. The output shape of the model is MultiArray : Float32 1 × 25500 × 46 array. From the VNCoreMLRequest I receive only VNCoreMLFeatureValueObservation from this I can get the MultiArray and iterate through it, to find the data I need. But I see that Apple offers for Object Detection models VNRecognizedObjectObservation type, which is not returned for my model. What is the reason why my model is not supported to return the VNRecognizedObjectObservation type? Can I use CoreMLTools to enable it?

Hello, I am trying to integrate DetectingHandPosesWithVision to my flutter app. However, I am struggling so much, since I only know how to call each swift functions to flutter's dart file. Since DetectingHandPosesWithVision folder and my flutter app are seperate app, what would be the best approach to integrate DetectingHandPosesWithVision app to my flutter app? If I press the button in my app, I want DetectingHandPosesWithVision program to run on my app. If anybody has link explaining how to use swift files in flutter, that will be awesome too! Help will be greatly appreciated. Thanks!

I'm attempting to get the Xcode model preview to work with instance segmentation models, specifically RegNetX Mask R-CNN. I've already tried using the imageSegmenter model preview type and setting it in my Core ML model specification. However, this crashes the preview when attempting to load the model. I believe this might be due to a slightly different output format. The model I'm using gives three outputs: Detections with bounding boxes, (x1, y1, x2, y2, confidence) Labels, the index of the detected label Masks, 28×28 image, which should be resized to the dimensions of the bounding boxes and fit on the x1, y1 position I'm not sure how the Xcode preview handles different output formats, or if it only supports one specific format. Ultimately, my goal in this effort is to use the Vision framework for instance segmentation models. I'm not sure if this is currently supported, as I am unable to find proper information on existing solutions. I'm also unsure which VN object would be necessary for this, if it even e

We're well into COVID times now so building vision app involving people wearing masks should be expected. Vision's face rectangle detector works perfectly fine on faces with masks, but that's not the case for face landmarks. Even when someone is wearing a mask, there are still a lot of landmarks exposed (e.g., pupils, eyes, nose, eyebrows, etc.). When can expect face landmark detection to work on faces with masks?

I want to get real time camera frames to apply machine learning in swiftui. i made camera app with swiftui like this. but, i don't know how to get camera frame and how to apply machine learning techniques to camera frames struct ImagePicker: UIViewControllerRepresentable { var sourceType: UIImagePickerController.SourceType = .camera func makeUIViewController(context: UIViewControllerRepresentableContext) -> UIImagePickerController { let imagePicker = UIImagePickerController() imagePicker.allowsEditing = false imagePicker.sourceType = sourceType return imagePicker } func updateUIViewController(_ uiViewController: UIImagePickerController, context: UIViewControllerRepresentableContext) { } }

I downloaded the sample code from the WWDC 2022 session Counting human body action repetitions in a live video feed and ran it on my new iPhone SE (which has an A15 Bionic chip). Unfortunately, this sample project (whose action repetition counter was mentioned multiple times during WWDC, was extremely inconsistent in tracking reps. It rarely worked for me, which was disappointing because I was really excited about this functionality. I'd like to use this action repetition counting in an app of my own, it would be very useful if it worked, but I'm skeptical after struggling to get Apple's sample app to accurately count reps. Does anyone have any suggestions for getting this sample project or action repetition counting in general, to accurately work? Any help would be really appreciated, thanks!

i'm learning about swiftui and machine learning(by python pytorch). I want to use machine learning in swiftui like coreml or vision. but, almost reference of coreml or vision are written in uikit. so, any references(book or lecture or document, yotube) to machine learning with swiftui?

Hi there, I am trying to combine this code I have for stereo vision as well as the hand tracking code available (drawing when pinch) but I'm running into trouble with this. I believe it is to do with the fact that the hand tracking code sets up AV Session where as the stereo vision uses SceneKit. Could you please provide me with some feedback as how to start integrating these two very different sets of code? StereoVision Hand Tracking

Is it possible to use SNAudioFileAnalyzer with live HLS(m3u8) stream? Maybe we need to extract somehow audio from it? And Can we use SNAudioFileAnalyzer with real remote url? Or we can use it only with files in file system?