While trying to learn about coreML, I ran into an issue. Using a model from Apple's website (MobileNetV2) I had no issues. When I tried to use my own model that I created, I ran into the issue and the localized description was "Could not create inference context" when using the iPhone simulator. After a quick search I tested this using the arm64 simulator and it worked just fine. I believe this is an m1 related bug because another forum said it worked without any issues on intel Mac, but not their m1.
if let data = self.animal.imageData {
do {
let modelFile = try! DogorCatmodel1(configuration: MLModelConfiguration())
let model = try VNCoreMLModel(for: modelFile.model)
let handler = VNImageRequestHandler(data: data)
let request = VNCoreMLRequest(model: model) { (request, error) in
guard let results = request.results as? [VNClassificationObservation] else {
print("Could not classify")
return
}
for classification in results {
var identifier = classification.identifier
identifier = identifier.prefix(1).capitalized + identifier.dropFirst()
print(identifier)
print(classification.confidence)
}
}
do {
try handler.perform([request])
}
catch {
print(error.localizedDescription)
print("Invalid")
}
}
catch {
print(error.localizedDescription)
}
}
}
elichartnett
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