How to normalize disparity data in iOS? - ios

Question

In WWDC session "Image Editing with Depth" they mentioned few times normalizedDisparity and normalizedDisparityImage:
"The basic idea is that we're going to map our normalized disparity
values into values between 0 and 1"
"So once you know the min and max you can normalize the depth or disparity between 0 and 1."
I tried to first get the disparit image like this:
let disparityImage = depthImage.applyingFilter(
"CIDepthToDisparity", withInputParameters: nil)
Then I tried to get depthDataMap and do normalization but it didn't work. I'm I on the right track? would be appreciate some hint on what to do.
Edit:
This is my test code, sorry for the quality. I get the min and max then I try to loop over the data to normalize it (let normalizedPoint = (point - min) / (max - min))
let depthDataMap = depthData!.depthDataMap
let width = CVPixelBufferGetWidth(depthDataMap) //768 on an iPhone 7+
let height = CVPixelBufferGetHeight(depthDataMap) //576 on an iPhone 7+
CVPixelBufferLockBaseAddress(depthDataMap, CVPixelBufferLockFlags(rawValue: 0))
// Convert the base address to a safe pointer of the appropriate type
let floatBuffer = unsafeBitCast(CVPixelBufferGetBaseAddress(depthDataMap),
to: UnsafeMutablePointer<Float32>.self)
var min = floatBuffer[0]
var max = floatBuffer[0]
for x in 0..<width{
for y in 0..<height{
let distanceAtXYPoint = floatBuffer[Int(x * y)]
if(distanceAtXYPoint < min){
min = distanceAtXYPoint
}
if(distanceAtXYPoint > max){
max = distanceAtXYPoint
}
}
}
What I expected is the the data will reflect the disparity where the user clicked on the image but it didn't match. The code to find the disparity where the user clicked is here:
// Apply the filter with the sampleRect from the user’s tap. Don’t forget to clamp!
let minMaxImage = normalized?.clampingToExtent().applyingFilter(
"CIAreaMinMaxRed", withInputParameters:
[kCIInputExtentKey : CIVector(cgRect:rect2)])
// A four-byte buffer to store a single pixel value
var pixel = [UInt8](repeating: 0, count: 4)
// Render the image to a 1x1 rect. Be sure to use a nil color space.
context.render(minMaxImage!, toBitmap: &pixel, rowBytes: 4,
bounds: CGRect(x:0, y:0, width:1, height:1),
format: kCIFormatRGBA8, colorSpace: nil)
// The max is stored in the green channel. Min is in the red.
let disparity = Float(pixel[1]) / 255.0

Answer 1

There's a new blog post on raywenderlich.com called "Image Depth Maps Tutorial for iOS" contains sample app and details related to working with depth. The sample code shows how to normalize the depth data using a CVPixelBuffer extension:
extension CVPixelBuffer {
func normalize() {
let width = CVPixelBufferGetWidth(self)
let height = CVPixelBufferGetHeight(self)
CVPixelBufferLockBaseAddress(self, CVPixelBufferLockFlags(rawValue: 0))
let floatBuffer = unsafeBitCast(CVPixelBufferGetBaseAddress(self), to: UnsafeMutablePointer<Float>.self)
var minPixel: Float = 1.0
var maxPixel: Float = 0.0
for y in 0 ..< height {
for x in 0 ..< width {
let pixel = floatBuffer[y * width + x]
minPixel = min(pixel, minPixel)
maxPixel = max(pixel, maxPixel)
}
}
let range = maxPixel - minPixel
for y in 0 ..< height {
for x in 0 ..< width {
let pixel = floatBuffer[y * width + x]
floatBuffer[y * width + x] = (pixel - minPixel) / range
}
}
CVPixelBufferUnlockBaseAddress(self, CVPixelBufferLockFlags(rawValue: 0))
}
}
Something to keep in mind when working with depth data that they are lower resolution than the actual image so you need to scale up (more info in the blog and in the WWDC video)

Answer 2

Will's answer above is very good, but it can be improved as follows. I'm using it with depth data from a photo, it's possible that if the depth data doesn't follow 16-bits, as mentioned above, it won't work. Haven't found such a photo yet. I'm surprised there isn't a filter to handle this in Core Image.
extension CVPixelBuffer {
func normalize() {
CVPixelBufferLockBaseAddress(self, CVPixelBufferLockFlags(rawValue: 0))
let width = CVPixelBufferGetWidthOfPlane(self, 0)
let height = CVPixelBufferGetHeightOfPlane(self, 0)
let count = width * height
let pixelBufferBase = unsafeBitCast(CVPixelBufferGetBaseAddressOfPlane(self, 0), to: UnsafeMutablePointer<Float>.self)
let depthCopyBuffer = UnsafeMutableBufferPointer<Float>(start: pixelBufferBase, count: count)
let maxValue = vDSP.maximum(depthCopyBuffer)
let minValue = vDSP.minimum(depthCopyBuffer)
let range = maxValue - minValue
let negMinValue = -minValue
let subtractVector = vDSP.add(negMinValue, depthCopyBuffer)
let normalizedDisparity = vDSP.divide(subtractVector, range)
pixelBufferBase.initialize(from: normalizedDisparity, count: count)
CVPixelBufferUnlockBaseAddress(self, CVPixelBufferLockFlags(rawValue: 0))
}
}

Answer 3

Try using the Accelerate Framework vDSP vector functions.. here is a normalize in two functions.
to change the cvPixel buffer to a 0..1 normalized range
myCVPixelBuffer.setUpNormalize()
import Accelerate
extension CVPixelBuffer {
func vectorNormalize( targetVector: UnsafeMutableBufferPointer<Float>) -> [Float] {
// range = max - min
// normalized to 0..1 is (pixel - minPixel) / range
// see Documentation "Using vDSP for Vector-based Arithmetic" in vDSP under system "Accelerate" documentation
// see also the Accelerate documentation section 'Vector extrema calculation'
// Maximium static func maximum<U>(U) -> Float
// Returns the maximum element of a single-precision vector.
//static func minimum<U>(U) -> Float
// Returns the minimum element of a single-precision vector.
let maxValue = vDSP.maximum(targetVector)
let minValue = vDSP.minimum(targetVector)
let range = maxValue - minValue
let negMinValue = -minValue
let subtractVector = vDSP.add(negMinValue, targetVector)
// adding negative value is subtracting
let result = vDSP.divide(subtractVector, range)
return result
}
func setUpNormalize() -> CVPixelBuffer {
// grayscale buffer float32 ie Float
// return normalized CVPixelBuffer
CVPixelBufferLockBaseAddress(self,
CVPixelBufferLockFlags(rawValue: 0))
let width = CVPixelBufferGetWidthOfPlane(self, 0)
let height = CVPixelBufferGetHeightOfPlane(self, 0)
let count = width * height
let bufferBaseAddress = CVPixelBufferGetBaseAddressOfPlane(self, 0)
// UnsafeMutableRawPointer
let pixelBufferBase = unsafeBitCast(bufferBaseAddress, to: UnsafeMutablePointer<Float>.self)
let depthCopy = UnsafeMutablePointer<Float>.allocate(capacity: count)
depthCopy.initialize(from: pixelBufferBase, count: count)
let depthCopyBuffer = UnsafeMutableBufferPointer<Float>(start: depthCopy, count: count)
let normalizedDisparity = vectorNormalize(targetVector: depthCopyBuffer)
pixelBufferBase.initialize(from: normalizedDisparity, count: count)
// copy back the normalized map into the CVPixelBuffer
depthCopy.deallocate()
// depthCopyBuffer.deallocate()
CVPixelBufferUnlockBaseAddress(self, CVPixelBufferLockFlags(rawValue: 0))
return self
}
}
You can see it in action in a modified version of the Apple sample 'PhotoBrowse' app at
https://github.com/racewalkWill/PhotoBrowseModified