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[英]iOS Training model with CreateML MLTextClassifier class unable to filter from JSON
[英]ObjectDetection: Output different from CreateML vs programatically
我想從圖像中提取已知對象。 我使用 CreateML App 創建了一個ObjectDetector
model。 當我使用 CreateML 預覽進行測試時,檢測工作正常,但是通過代碼,似乎有些問題。
下面是我編寫的示例代碼部分。 我正在使用boundingbox
保存圖片,但是,當我使用 CreateML 預覽進行測試時,預測的圖像完全不同。 我已經嘗試了所有選項,請讓我知道我的代碼有什么問題。
func extractSpecifcSectioninImage(image: NSImage){
var requests = [VNRequest]()
var picCount = 1
let modelURL = Bundle.main.url(forResource: "ObjectDetection", withExtension: "mlmodelc")!
do {
let visionModel = try VNCoreMLModel(for: MLModel(contentsOf: modelURL))
let objectRecognition = VNCoreMLRequest(model: visionModel, completionHandler: { (request, error) in
if let results = request.results {
for observation in results where observation is VNRecognizedObjectObservation {
guard let objectObservation = observation as? VNRecognizedObjectObservation else {
continue
}
let cropsize = VNImageRectForNormalizedRect(objectObservation.boundingBox, Int((image.size.width)), Int((image.size.height)))
let topLabelObservation = objectObservation.labels[0]
guard let cgImage = image.cgImage(forProposedRect: nil, context: nil, hints: nil) else{break}
guard let cutImageRef: CGImage = cgImage.cropping(to:cropsize)else {break}
let sie = NSSize(width: cropsize.width,height: cropsize.height)
let objectImg = NSImage(cgImage: cutImageRef, size: sie)
if objectImg.save(as: "CroppedImage\(picCount)") {
picCount += 1
}
}
}
})
objectRecognition.imageCropAndScaleOption = .scaleFill
guard let cgImage = image.cgImage(forProposedRect: nil, context: nil, hints: nil) else{
print("Failed to get cgimage from input image")
return
}
let handler = VNImageRequestHandler(cgImage: cgImage, options: [:])
do {
try handler.perform([objectRecognition])
} catch {
print(error)
}
requests = [objectRecognition]
} catch let error as NSError {
print("Model loading went wrong: \(error)")
}
}
您沒有說邊界框出了什么問題,但我的猜測是它們是正確的,但它們根本沒有被繪制在正確的位置。 我寫了一篇關於這個的博客文章: https://machinethink.net/blog/bounding-boxes/
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