Hello everybody,
I am trying to run inference on a CoreML Model created by me using CreateML. I am following the sample code provided by Apple on the CoreML documentation page and every time I try to classify an image I get this error: "Could not create Espresso context".
Has this ever happened to anyone? How did you solve it?
Here is my code:
import Foundation
import Vision
import UIKit
import ImageIO
final class ButterflyClassification {
var classificationResult: Result?
lazy var classificationRequest: VNCoreMLRequest = {
do {
let model = try VNCoreMLModel(for: ButterfliesModel_1(configuration: MLModelConfiguration()).model)
return VNCoreMLRequest(model: model, completionHandler: { [weak self] request, error in
self?.processClassification(for: request, error: error)
})
}
catch {
fatalError("Failed to lead model.")
}
}()
func processClassification(for request: VNRequest, error: Error?) {
DispatchQueue.main.async {
guard let results = request.results else {
print("Unable to classify image.")
return
}
let classifications = results as! [VNClassificationObservation]
if classifications.isEmpty {
print("No classification was provided.")
return
}
else {
let firstClassification = classifications[0]
self.classificationResult = Result(speciesName: firstClassification.identifier, confidence: Double(firstClassification.confidence))
}
}
}
func classifyButterfly(image: UIImage) - Result? {
guard let ciImage = CIImage(image: image) else {
fatalError("Unable to create ciImage")
}
DispatchQueue.global(qos: .userInitiated).async {
let handler = VNImageRequestHandler(ciImage: ciImage, options: [:])
do {
try handler.perform([self.classificationRequest])
}
catch {
print("Failed to perform classification.\n\(error.localizedDescription)")
}
}
return classificationResult
}
}
Thank you for your help!
Selecting any option will automatically load the page
Post
Replies
Boosts
Views
Activity
Hello everybody,
I am trying to navigate from one view to another using NavigationView and NavigationLink.
I can't figure out what I am doing wrong, but the way I am doing it I get a warning saying:
"Result of NavigationLink<Label, Destination> is unused".
In fact, I can't navigate to the view I want to open.
Here is my code so far:
NavigationView {
VStack {
Button(action: {
let observation = self.createObservation()
self.records.addObservation(observation)
self.isPresented.toggle()
NavigationLink(destination: ObservationDetails(observation: observation).environmentObject(self.records)) {
EmptyView()
}
}) {
Text("Classify")
}
}
Thank you for your help!
Hello everybody ,Two days ago I submitted my first iOS app. I was super excited. Yesterday my app came back rejected with “metadata rejected”. I am very inexperienced and I kind of panic and tried everything to solve it. I replied in the resolution center and then I made the mistake of clicking submit for review. And now I am waiting.Sorry to bother you but I really would like to hear from somebody with experience what is going to happen now...- Since I clicked submit for review will my app be again in the beginning of the queue?- what happens to my response in the resolution center? Will my reviewer still read it?- How long, in the worst case scenario will it take to get some feedback back?Thank you so much.Best regards,
Hello everybody,I am new to iOS development and I found an error that I can not get past. I have read a lot online and on Stackoverflow but I don't understand why this error keeps coming up.I have a table view controller and I want to write text to other view controller using:navigationController?.pushViewController(viewController, animated: true)I have this class where I already have an outlet for the label.import UIKit
class PetitionDetailsViewController: UIViewController {
@IBOutlet weak var PetitionDetailsOutlet: UILabel!
override func viewDidLoad() {
super.viewDidLoad()
}
}On the other class I have this code where I try to add text to the label in the PetitionDetailsViewController after tapping one of the rows in the table view.override func tableView(_ tableView: UITableView, didSelectRowAt indexPath: IndexPath) {
let viewController = PetitionDetailsViewController()
print(petitions[indexPath.row].body)
viewController.PetitionDetailsOutlet.text = petitions[indexPath.row].body
navigationController?.pushViewController(viewController, animated: true)
}I don't understand why this error keeps coming up. I have the outlet and initially the label is empty.Why is it nil?
Hello everyone,
I trying to draw a custom view inside a for each (list style), that is inside a Scroll View, that is inside a Navigation view. Like this.
Navigation View {
ScrollView {
ForEach(array of objects ...) {
CustomView()
}
}
}
The custom view calls up a sheet that has a button that is able to delete elements inside the collection used in the foreach.
Unless I use this asyncAfter after dismissing the sheet I always get index out of bounds when I try to remove the last element of the array of objects in the for each:
DispatchQueue.main.asyncAfter(deadline: .now() + 0.5) {
workouts.removeAll(where: { $0.id == workoutToRemoveID })
}
I have been trying to solve this bug, but so far no luck. Could you give me a hand?
Thank you for your help!
Hello everybody,
For the past week I have been struggling to run inference on a classifier I built using Google's AutoML Vision tool.
At first I thought everything would go smoothly because Google allows to export a CoreML version of the final model. I assumed I would only need to use Apple's CoreML library to make it work. When I export the model Google provides a .mlmodel file and a dict.txt file with the classification labels. For the current model I have 100 labels.
This is my Swift code to run inference on the model.
private lazy var classificationRequest: VNCoreMLRequest = {
				do {
						let classificationModel = try VNCoreMLModel(for: NewGenusModel().model)
						let request = VNCoreMLRequest(model: classificationModel, completionHandler: { [weak self] request, error in
								self?.processClassifications(for: request, error: error)
						})
						request.imageCropAndScaleOption = .scaleFit
						return request
				}
				catch {
						fatalError("Error! Can't use Model.")
				}
		}()
		func classifyImage(receivedImage: UIImage) {
				let orientation = CGImagePropertyOrientation(rawValue: UInt32(receivedImage.imageOrientation.rawValue))
				if let image = CIImage(image: receivedImage) {
						DispatchQueue.global(qos: .userInitiated).async {
								let handler = VNImageRequestHandler(ciImage: image, orientation: orientation!)
								do {
										try handler.perform([self.classificationRequest])
								}
								catch {
										fatalError("Error classifying image!")
								}
						}
				}
		}
The problem started when I tried to pass a UIImage to run inference on the model. The input type of the original model was MultiArray (Float32 1 x 224 x 224 x 3). Using Coremltools library I was able to convert the input type to Image (Color 224 x 224) using Python.
This worked and here is my code:
import coremltools
import coremltools.proto.FeatureTypes_pb2 as ft
spec = coremltools.utils.load_spec("model.mlmodel")
input = spec.description.input[0]
input.type.imageType.colorSpace = ft.ImageFeatureType.RGB
input.type.imageType.height = 224
input.type.imageType.width = 224
coremltools.utils.save_spec(spec, "newModel.mlmodel")
My problem now is with the output type. I want to be able to access the confidence of the classification as well as the result label of the classification. Again using coremltools I was able to to access the output description and I got this.
name: "scores"
type {
	multiArrayType {
		dataType: FLOAT32
	}
}
I am trying to change it this way:
f = open("dict.txt", "r")
labels = f.read()
class_labels = labels.splitlines()
print(class_labels)
class_labels = class_labels[1:]
assert len(class_labels) == 57
for i, label in enumerate(class_labels):
	if isinstance(label, bytes):
		class_labels[i] = label.decode("utf8")
classifier_config = ct.ClassifierConfig(class_labels)
output = spec.description.output[0]
output.type = ft.DictionaryFeatureType
Unfortunately this is not working and I can't find information only that can help me... This I don't know what to do next.
Thank you for your help!
Hello everybody,
I have very little experience developing applications for the Apple Watch. I want to use the Apple Watch to capture accelerometer and gyroscope data to create a CoreML model.
Could you give me some pointers on what I would have to do to be able to gather the data I need from the Apple Watch?
Do I need to create a simple Watch app to gather this data first and save it to a txt file, for exemple?
Thank you for your help.
Best regards,
Tomás
Hello everybody,
I am relatively new to ARKit and SceneKit and I have been experimenting with it.
I have been exploring plane detection and I want to keep only one plane in the view. If other planes are found I want the old ones to be removed.
This is the solution I found: I have an array with all found anchors and before adding a new child node I remove all the anchors from my scene.
What do you think of this solution? Do you think I should do it in any other way? Thank you!
private var planes = [UUID: Plane]()
private var anchors = [UUID: ARAnchor]()
func renderer(_ renderer: SCNSceneRenderer, didAdd node: SCNNode, for anchor: ARAnchor) {
// we only care about planes
guard let planeAnchor = anchor as? ARPlaneAnchor else {
return
}
print("Found plane: \(planeAnchor)")
for anchor in anchors {
sceneView?.session.remove(anchor: anchor.value)
}
let plane = Plane(anchor: planeAnchor)
planes[anchor.identifier] = plane
anchors[anchor.identifier] = anchor
node.addChildNode(plane)
}
Hello everybody,
I am new to Machine Learning but I want to get started with developing CoreML models to try them out in a few apps of my own.
What is the best way to build a dataset from Apple Watch data to build an activity model?
Do I build an iPhone app that works with the Apple Watch in order to get the data I need, or is there a more direct way to do it through Xcode, maybe?
Thank you for for help.
Best regards,
Tomás
Topic:
App & System Services
SubTopic:
Hardware
Tags:
SensorKit
Machine Learning
Apple Watch
Core ML
Hello everyone!
I am trying to implement push notifications in my WatchOS app. I have created the delegate class that handles the registration for remote notifications and that allows me to obtain the device token. Then I take the token and send it to Firebase, like this:
func didRegisterForRemoteNotifications(withDeviceToken deviceToken: Data) {
FirebaseApp.configure()
var ref: DatabaseReference!
ref = Database.database().reference().ref.child("/")
let tokenParts = deviceToken.map { data in String(format: "%02.2hhx", data) }
let token = tokenParts.joined()
if let userID = UserDefaults.standard.object(forKey: "id") as? String {
ref.child("users/\(userID)/token").setValue(token)
}
}
Then I am using a Python Script to communicate with APNS. I am using the http library to get access to HTTP2. This is what I have got:
payload = {
"aps" : {
"alert" : {
"title" : "Hello Push",
"message": "This is a notification!"
},
"category": "myCategory"
}
}
dev_server = "https://api.sandbox.push.apple.com:443"
device_token = "9fe2814b6586bbb683b1a3efabdbe1ddd7c6918f51a3b83e90fce038dc058550"
headers = {
'method': 'POST',
'path': '/3/device/{}'.format(device_token),
'autorization': 'bearer' + 'provider_token',
'apns-push-type': 'myCategory',
'apns-expiration': '0',
'apns-priority': '10',
}
async def test():
async with httpx.AsyncClient(http2=True) as client:
client = httpx.AsyncClient(http2=True)
r = await client.post(dev_server, headers=headers, data=payload)
print(r.text)
asyncio.run(test())
I have also downloaded the .p8 auth key file. But I don't really understand from the Apple Documentation what I have to do with it.
What is the provider token in the headers?
Am I doing the right thing with the token I receive from didRegisterForRemoteNotifications?
Topic:
Programming Languages
SubTopic:
Swift
Tags:
APNS
Swift
Notification Center
User Notifications