docs

README.md

@@ -99,33 +99,6 @@ Options:
 
 The PLY uses the same binary format as [SHARP](https://github.com/apple/ml-sharp), with per-pixel positions projected onto a sphere using estimated depth, image-derived colors (SH0), uniform scale/opacity, and identity quaternions.
 
-## Quick Start — Xcode (iOS / macOS)
-
-Add `DAPModel.mlpackage` to your Xcode project (Xcode auto-generates the `DAPModel` Swift class), then use the included `DepthPredictor.swift`:
-
-```swift
-import Foundation
-import CoreML
-import Vision
-import CoreImage
-
-// Load the model from a .mlpackage URL
-let modelURL = Bundle.main.url(forResource: "DAPModel", withExtension: "mlpackage")!
-let predictor = DepthPredictor(modelURL: modelURL)
-
-// Run inference on a CGImage (equirectangular panorama)
-predictor.predictDepth(from: cgImage) { depth in
-    guard let depth = depth else { return }
-    // `depth` is a DepthResult with raw Float32 values and a CIImage
-
-    // Colorize with jet colormap
-    let colorized = predictor.applyJetColormap(to: depth)
-
-    // Or access raw depth values directly
-    let values = depth.getDepthValues()  // [Float32], row-major
-}
-```
-
 ## Files
 
 | File | Description |