Following WWDC24 video "Discover Swift enhancements in the Vision framework" recommendations (cfr video at 10'41"), I used the following code to perform multiple new iOS 18 `RecognizedTextRequest' in parallel. Problem: if more than 2 request are run in parallel, the request will hang, leaving the app in a state where no more requests can be started. -> deadlock
I tried other ways to run the requests, but no matter the method employed, or what device I use: no more than 2 requests can ever be run in parallel.
func triggerDeadlock() {}
try await withThrowingTaskGroup(of: Void.self) { group in
// See: WWDC 2024 Discover Siwft enhancements in the Vision framework at 10:41
// ############## THIS IS KEY
let maxOCRTasks = 5 // On a real-device, if more than 2 RecognizeTextRequest are launched in parallel using tasks, the request hangs
// ############## THIS IS KEY
for idx in 0..<maxOCRTasks {
let url = ... // URL to some image
group.addTask {
// Perform OCR
let _ = await performOCRRequest(on: url: url)
}
}
var nextIndex = maxOCRTasks
for try await _ in group { // Wait for the result of the next child task that finished
if nextIndex < pageCount {
group.addTask {
let url = ... // URL to some image
// Perform OCR
let _ = await performOCRRequest(on: url: url)
}
nextIndex += 1
}
}
}
}
// MARK: - ASYNC/AWAIT version with iOS 18
@available(iOS 18, *)
func performOCRRequest(on url: URL) async throws -> [RecognizedText] {
// Create request
var request = RecognizeTextRequest() // Single request: no need for ImageRequestHandler
// Configure request
request.recognitionLevel = .accurate
request.automaticallyDetectsLanguage = true
request.usesLanguageCorrection = true
request.minimumTextHeightFraction = 0.016
// Perform request
let textObservations: [RecognizedTextObservation] = try await request.perform(on: url)
// Convert [RecognizedTextObservation] to [RecognizedText]
return textObservations.compactMap { observation in
observation.topCandidates(1).first
}
}
I also found this Swift forums post mentioning something very similar.
I also opened a feedback: FB17240843
To increase parallelism there is a tradeoff in workload complexity.
This OCR configuration appears to have high workload complexity, which may take a long time to process causing resource starvation.
// Configure request
request.recognitionLevel = .accurate
request.automaticallyDetectsLanguage = true
request.usesLanguageCorrection = true
request.minimumTextHeightFraction = 0.016
Can this configuration be simplified to accommodate higher throughput (more images than 2)?
Otherwise total performance is governed by the capabilities of the underlying hardware (which is ideally aligned with the software architecture) so you'll want to profile various iOS devices to empirically determine a working value for your app.
Note: there are additional suggestions for adjusting workload in my previous post.
