When working with the Vision framework in Swift, proper error handling is crucial for creating robust applications. Below are some common error handling patterns that developers use to manage Vision-related errors:
Here is an example of how to handle errors using a Do-Catch block when requesting face detection in a given image:
import Vision
func detectFaces(in image: UIImage) {
guard let cgImage = image.cgImage else {
print("Could not convert UIImage to CGImage.")
return
}
let faceDetector = VNDetectFaceRectanglesRequest { request, error in
if let error = error {
print("Face detection error: \(error.localizedDescription)")
return
}
// Process the results if no error occurred
for observation in request.results as? [VNFaceObservation] ?? [] {
print("Detected face at \(observation.boundingBox)")
}
}
let handler = VNImageRequestHandler(cgImage: cgImage, options: [:])
do {
try handler.perform([faceDetector])
} catch {
print("Error performing face detection: \(error.localizedDescription)")
}
}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?