Core ML prediction for Image Classification Create ml model predict same result for different images

I am exploring the Apple Core ML framework.

I created a training model using Create ML app. Image Classification to identify the image is cat or a dog. The data set I used is referred from https://www.kaggle.com/datasets/samuelcortinhas/cats-and-dogs-image-classification?resource=download

I created my .mlmodel file from create ml by providing the training data. Now I am doing the prediction in the app and it is giving me same target and probability results and different images(either cat or dog, giving same result - ["cats": 0.6281524444894766, "dogs": 0.3718475555105234]

App Code:

override func viewDidLoad() {
        if  let img = UIImage(named: "dog_29.jpg") {
            predictImage(image: img)
        }  else {
            print("image  not captured")
        }
    }
    
    
    private func predictImage(image: UIImage) {
        

        let inputImageSize: CGFloat = 299.0
                let minLen = min(image.size.width, image.size.height)
                let resizedImage = image.resize(to: CGSize(width: inputImageSize * image.size.width / minLen, height: inputImageSize * image.size.height / minLen))

        guard let pixelBuffer = resizedImage.pixelBuffer() else {
                    fatalError()
                }
        
        do {
            let config = MLModelConfiguration()
            let model = try CatsAndDogs(configuration:config)
            let result = try model.prediction(image: pixelBuffer)
            print(result.target)
            print(result.targetProbability)

            print(result)
        } catch {
            print("image classification error")
        }
        
    }

Code of resize and getcvbuffer:

  func resize(to newSize: CGSize) -> UIImage {
        UIGraphicsBeginImageContextWithOptions(CGSize(width: newSize.width, height: newSize.height), true, 1.0)
        self.draw(in: CGRect(x: 0, y: 0, width: newSize.width, height: newSize.height))
        let resizedImage = UIGraphicsGetImageFromCurrentImageContext()!
        UIGraphicsEndImageContext()

        return resizedImage
    }

  func pixelBuffer() -> CVPixelBuffer? {
        let width = self.size.width
        let height = self.size.height
        let attrs = [kCVPixelBufferCGImageCompatibilityKey: kCFBooleanTrue,
                     kCVPixelBufferCGBitmapContextCompatibilityKey: kCFBooleanTrue] as CFDictionary
        var pixelBuffer: CVPixelBuffer?
        let status = CVPixelBufferCreate(kCFAllocatorDefault,
                                         Int(width),
                                         Int(height),
                                         kCVPixelFormatType_32ARGB,
                                         attrs,
                                         &pixelBuffer)

        guard let resultPixelBuffer = pixelBuffer, status == kCVReturnSuccess else {
            return nil
        }

        CVPixelBufferLockBaseAddress(resultPixelBuffer, CVPixelBufferLockFlags(rawValue: 0))
        let pixelData = CVPixelBufferGetBaseAddress(resultPixelBuffer)

        let rgbColorSpace = CGColorSpaceCreateDeviceRGB()
        guard let context = CGContext(data: pixelData,
                                      width: Int(width),
                                      height: Int(height),
                                      bitsPerComponent: 8,
                                      bytesPerRow: CVPixelBufferGetBytesPerRow(resultPixelBuffer),
                                      space: rgbColorSpace,
                                      bitmapInfo: CGImageAlphaInfo.noneSkipFirst.rawValue) else {
                                        return nil
        }

        context.translateBy(x: 0, y: height)
        context.scaleBy(x: 1.0, y: -1.0)

        UIGraphicsPushContext(context)
        self.draw(in: CGRect(x: 0, y: 0, width: width, height: height))
        UIGraphicsPopContext()
        CVPixelBufferUnlockBaseAddress(resultPixelBuffer, CVPixelBufferLockFlags(rawValue: 0))

        return resultPixelBuffer
    }

I also have tried various methods of resizing and getcvbuffer available on net but all giving same result.

I tried different images of cat and dog from test folder from the dataset link. Still the result is the same.

Why the predictions are not correct?