I've spent way too long today trying to convert an Object Detection TensorFlow2 model to a CoreML object classifier (with bounding boxes, labels and probability score) The 'SSD MobileNet v2 320x320' is here: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2_detection_zoo.md And I've been following all sorts of posts and ChatGPT https://apple.github.io/coremltools/docs-guides/source/tensorflow-2.html#convert-a-tensorflow-concrete-function https://developer.apple.com/videos/play/wwdc2020/10153/?time=402 To convert it. I keep hitting the same errors though, mostly around: NotImplementedError: Expected model format: [SavedModel | concrete_function | tf.keras.Model | .h5 | GraphDef], got <ConcreteFunction signature_wrapper(input_tensor) at 0x366B87790> I've had varying success including missing output labels/predictions. But I simply want to create the CoreML model with all the right inputs and outputs (including correct names) as detailed in the docs here: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/running_on_mobile_tf2.md It goes without saying I don't have much (any) experience with this stuff including Python so the whole thing's been a bit of a headache. If anyone is able to help that would be great. FWIW I'm not attached to any one specific model, but what I do need at minimum is a CoreML model that can detect objects (has to at least include lights and lamps) within a live video image, detecting where in the image the object is. The simplest script I have looks like this: import coremltools as ct import tensorflow as tf model = tf.saved_model.load("~/tf_models/ssd_mobilenet_v2_320x320_coco17_tpu-8/saved_model") concrete_func = model.signatures[tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY] mlmodel = ct.convert( concrete_func, source="tensorflow", inputs=[ct.TensorType(shape=(1, 320, 320, 3))] ) mlmodel.save("YourModel.mlpackage", save_format="mlpackage")

Overview I have the following view hierarchy that mixes SwiftUI and UIKit: AccordionView └─ VStack ├─ Text ├─ Button └─ UIViewRepresentable └─ UIStackView ├─ UILabel └─ UILabel When tapping the button, the UIViewRepresentable hides and shows its content. This all works as expected. However, in certain circumstances the view's sizing is rendered with the correct size, but the text can often render incorrectly, despite the frame seemingly looking as though it has enough room to render the text. More info Below you can see the UILabel has the correct frame height (the light grey background and coloured borders) but the text is rendered as though it has infinite width along one line. There's a few configurations of my view hierarchy that seem to have this effect. I've added a playground to the bottom of this post of various configurations to show what does and doesn't work, just copy and paste to see for yourself... It seems of the ones that don't work, there's a couple of reasons why that may be: HostedView and TextViewContainer do not do the following (I think we only need to do one of these things for auto layout/stack views to work effectively): a) implement an intrinsic content size b) return a 'good' size for systemLayoutSizeFitting(). UIHostingController shouldn't use intrinsic size (although I'm sure it should) Something related to setting setContentCompressionResistancePriority() or setContentHuggingPriority() but having played about with this it doesn't seem relevant here... I've played around with everything I can think of here but can't find a solution that works for all, although I'm 99% sure it's one or all of the points above. If there are any UIKit gurus out there that can help that would be great! Ive already spent so much time on this 🫨 Playground Swift Playground