Ian Timmis iantimmis

## Keras.ipynb

      
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                ravnoor
                / Keras.ipynb
            
            
              Created
              April 24, 2017 02:38
                — forked from prhbrt/Keras.ipynb
            
              
                V-Net in Keras and tensorflow
              
          
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## jaccard_coef_loss.py
from keras import backend as K

def jaccard_distance_loss(y_true, y_pred, smooth=100):
    """
    Jaccard = (|X & Y|)/ (|X|+ |Y| - |X & Y|)
            = sum(|A*B|)/(sum(|A|)+sum(|B|)-sum(|A*B|))

    The jaccard distance loss is usefull for unbalanced datasets. This has been
    shifted so it converges on 0 and is smoothed to avoid exploding or disapearing
    gradient.

## CreatePixelBuffer.swift
func createPixelBuffer(fromFrame frame: VideoFrameYUV) -> CVPixelBuffer? {
        var initialPixelBuffer: CVPixelBuffer?
        let _: CVReturn = CVPixelBufferCreate(kCFAllocatorDefault, Int(frame.width), Int(frame.height), kCVPixelFormatType_420YpCbCr8Planar, nil, &initialPixelBuffer)

        guard let pixelBuffer = initialPixelBuffer,
            CVPixelBufferLockBaseAddress(pixelBuffer, []) == kCVReturnSuccess
            else {
            return nil
        }
	from keras import backend as K

	def jaccard_distance_loss(y_true, y_pred, smooth=100):
	"""
	Jaccard = (\|X & Y\|)/ (\|X\|+ \|Y\| - \|X & Y\|)
	= sum(\|AB\|)/(sum(\|A\|)+sum(\|B\|)-sum(\|AB\|))

	The jaccard distance loss is usefull for unbalanced datasets. This has been
	shifted so it converges on 0 and is smoothed to avoid exploding or disapearing
	gradient.
	func createPixelBuffer(fromFrame frame: VideoFrameYUV) -> CVPixelBuffer? {
	var initialPixelBuffer: CVPixelBuffer?
	let _: CVReturn = CVPixelBufferCreate(kCFAllocatorDefault, Int(frame.width), Int(frame.height), kCVPixelFormatType_420YpCbCr8Planar, nil, &initialPixelBuffer)

	guard let pixelBuffer = initialPixelBuffer,
	CVPixelBufferLockBaseAddress(pixelBuffer, []) == kCVReturnSuccess
	else {
	return nil
	}