如何解决在设备上训练声音分类器
我正在尝试在 iOS 设备上训练 CoreML 声音分类器,并且一直在努力寻找有关该主题的学习资源。声音分类器用于确定一段音乐是否与其他歌曲的集合相似。因此分类器的输出只是“匹配”/“不匹配”的标签。
使用 CreateML 应用工作流程进行训练非常简单。我只是想在 iOS 设备上获得相同类型的培训,但据我所知(如果我错了,请纠正我)iOS 不支持 createML。
我一直在尝试调整来自各种来源的代码,以使其在 iOS 游乐场中工作。我只能找到有关训练图像分类器的资源,这两个最有帮助 (1,2)。
请参阅我在下面提出的代码。
import UIKit
import CoreML
func convertDataToArray<T>(count: Int,data: Data) -> [T] {
let array = data.withUnsafeBytes { (pointer: UnsafePointer<T>) -> [T] in
let buffer = UnsafeBufferPointer(start: pointer,count: count / MemoryLayout<Float32>.size)
return Array<T>(buffer)
}
return array
}
// Get files (names and paths) in directory
public func getAllFilesInDirectory(bundle: Bundle,directory: String,extensionWanted: String) -> (names: [String],paths: [URL]) {
let cachesURL = URL(fileURLWithPath: "/Users/...../Playgrounds/MLPlayground.playground/Resources")
let directoryURL = cachesURL.appendingPathComponent(directory)
do {
try FileManager.default.createDirectory(atPath: directoryURL.relativePath,withIntermediateDirectories: true)
// Get the directory contents urls (including subfolders urls)
let directoryContents = try FileManager.default.contentsOfDirectory(at: directoryURL,includingPropertiesForKeys: nil,options: [])
// Filter the directory contents
let filesPath = directoryContents.filter{ $0.pathExtension == extensionWanted }
let fileNames = filesPath.map{ $0.deletingPathExtension().lastPathComponent }
return (names: fileNames,paths: filesPath);
} catch {
print("Failed to fetch contents of directory: \(error.localizedDescription)")
}
return (names: [],paths: [])
}
let bundle = Bundle.main
var featureProviders = [MLFeatureProvider]()
let matchDir = getAllFilesInDirectory(bundle: bundle,directory: "Match",extensionWanted: "m4a")
let noMatchDir = getAllFilesInDirectory(bundle: bundle,directory: "No Match",extensionWanted: "m4a")
// I have ommited the full path directories for Stack Overflow
try! MLModel.compileModel(at: URL(fileURLWithPath: "/Users/...../Playgrounds/MLPlayground.playground/Resources/UpdateableML.mlmodel"))
let modelDir = URL(fileURLWithPath: "/Users/....../Playgrounds/MLPlayground.playground/Resources/UpdateableML.mlmodel")
let outputDir = URL(fileURLWithPath: "/Users/....../Playgrounds/MLPlayground.playground/Resources/Output/outputmodel.mlmodel")
func getFeatureProvider(forLabel: String,directory: URL) {
let data = try! Data(contentsOf: directory.appendingPathComponent("\(forLabel).m4a"))
// MultiArray (Float32 15600)
let mlInputData = try! MLMultiArray(shape: [15600],dataType: .float32)
let songDataArray: [Float32] = convertDataToArray(count: data.count,data: data)
let count = songDataArray.count
for i in 0..<mlInputData.count {
mlInputData[i] = NSNumber(value: songDataArray[i])
}
let soundValue = MLFeatureValue(multiArray: mlInputData)
let outputValue = MLFeatureValue(string: forLabel)
let dataPointFeatures: [String: MLFeatureValue] = ["audioSamples": soundValue,"classLabel": outputValue]
if let provider = try? MLDictionaryFeatureProvider(dictionary: dataPointFeatures) {
featureProviders.append(provider)
} else {
print("Failed to get provider")
}
}
// Get features
for s in matchDir.names {
getFeatureProvider(forLabel: s,directory: matchDir.paths.first!.deletingLastPathComponent())
}
for s in noMatchDir.names {
getFeatureProvider(forLabel: s,directory: noMatchDir.paths.first!.deletingLastPathComponent())
}
var batchProvider = MLArrayBatchProvider(array: featureProviders)
func updateModel(at url: URL,with trainingData: MLBatchProvider,completionHandler: @escaping (MLUpdateContext) -> Void) {
let updateTask = try! MLUpdateTask(
forModelAt: url,trainingData: trainingData,configuration: nil,completionHandler: completionHandler
)
updateTask.resume()
}
func saveUpdatedModel(_ updateContext: MLUpdateContext) {
let updatedModel = updateContext.model
let fileManager = FileManager.default
do {
try fileManager.createDirectory(
at: outputDir,withIntermediateDirectories: true,attributes: nil)
try updatedModel.write(to: outputDir)
print("Updated model saved to:\n\t\(outputDir)")
} catch let error {
print("Could not save updated model to the file system: \(error)")
return
}
}
func updateWith(trainingData: MLBatchProvider,completionHandler: @escaping () -> Void) {
updateModel(at: modelDir,with: trainingData) { context in
print("Update Complete")
saveUpdatedModel(context)
completionHandler()
}
}
updateWith(trainingData: batchProvider,completionHandler: {
print("Final Complete")
})
我目前有两个问题:
- 我从函数“updateModel”处的 MLUpdateTask 收到以下错误:
Fatal error: 'try!' expression unexpectedly raised an error: Error Domain=com.apple.CoreML Code=0 "Unable to load model at file:///Users/....../Playgrounds/CuratorMLPlayground.playground/Resources/UpdateableML.mlmodel with error: Error opening file stream: /Users/....../Playgrounds/CuratorMLPlayground.playground/Resources/UpdateableML.mlmodel/coremldata.bin: unspecified iostream_category error"
- 我不知道我是否在“getFeatureProvider”函数中正确获取了音频数据,因为“songDataArray”的大小大约为 260000,模型/“mlInputData”的形状为 15600?有人可以向我解释一下吗。
更新: 我已将其复制到我的实际 iOS 应用程序项目中。我现在收到以下错误,而不是上面的错误。
Fatal error: 'try!' expression unexpectedly raised an error: Error Domain=com.apple.CoreML Code=0 "Invalid URL for .mlmodel." UserInfo={NSLocalizedDescription=Invalid URL for .mlmodel.}:
但是,我几乎可以肯定 URL 正确指向了 mlmodel
解决方法
我设法解决了与 mlUpdate 任务相关的错误,问题是我引用的是 .mlmodel 而不是编译版本,即 .mlmodelc 。从 Xcode 构建 iOS 应用程序时,会自动生成此文件。
我现在收到以下错误:
Fatal error: 'try!' expression unexpectedly raised an error: Error Domain=com.apple.CoreML Code=6 "Pipeline is not marked as updatable to perform update." UserInfo={NSLocalizedDescription=Pipeline is not marked as updatable to perform update.}:
因此,我可以得出结论,现在只是构建更好的模型的问题。我现在假设如果我有合适的模型,更新/个性化设备上的代码会起作用。
所以现在这只是构建一个可以在这里工作的模型的问题。感谢 another answer by Matthjis,我现在意识到我在 CreateML 中创建的模型无法更新,因为它是 GLM 分类器。
感谢 this git repo,我想我还发现了快速加载音频数据的正确方法。
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