332 lines
12 KiB
Swift
332 lines
12 KiB
Swift
//
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// VideoGazeTests.swift
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// GazeTests
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//
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// Created by Mike Freno on 1/16/26.
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//
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import AVFoundation
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import Vision
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import XCTest
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@testable import Gaze
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final class VideoGazeTests: XCTestCase {
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var logLines: [String] = []
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private func log(_ message: String) {
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logLines.append(message)
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}
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private func attachLogs() {
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let attachment = XCTAttachment(string: logLines.joined(separator: "\n"))
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attachment.name = "Test Logs"
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attachment.lifetime = .keepAlways
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add(attachment)
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}
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/// Process the outer video (looking away from screen) - should detect "looking away"
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func testOuterVideoGazeDetection() async throws {
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logLines = []
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let projectPath = "/Users/mike/Code/Gaze/GazeTests/video-test-outer.mp4"
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guard FileManager.default.fileExists(atPath: projectPath) else {
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XCTFail("Video file not found at: \(projectPath)")
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return
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}
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let stats = try await processVideo(
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at: URL(fileURLWithPath: projectPath), expectLookingAway: true)
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// For outer video, most frames should detect gaze outside center
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let nonCenterRatio =
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Double(stats.nonCenterFrames) / Double(max(1, stats.pupilDetectedFrames))
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log(
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"🎯 OUTER video: \(String(format: "%.1f%%", nonCenterRatio * 100)) frames detected as non-center (expected: >50%)"
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)
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log(
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" H-range: \(String(format: "%.3f", stats.minH)) to \(String(format: "%.3f", stats.maxH))"
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)
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log(
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" V-range: \(String(format: "%.3f", stats.minV)) to \(String(format: "%.3f", stats.maxV))"
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)
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log(
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" Face width: \(String(format: "%.3f", stats.avgFaceWidth)) (range: \(String(format: "%.3f", stats.minFaceWidth))-\(String(format: "%.3f", stats.maxFaceWidth)))"
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)
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attachLogs()
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// At least 50% should be detected as non-center when looking away
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XCTAssertGreaterThan(
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nonCenterRatio, 0.5,
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"Looking away video should have >50% non-center detections. Log:\n\(logLines.joined(separator: "\n"))"
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)
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}
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/// Process the inner video (looking at screen) - should detect "looking at screen"
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func testInnerVideoGazeDetection() async throws {
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logLines = []
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let projectPath = "/Users/mike/Code/Gaze/GazeTests/video-test-inner.mp4"
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guard FileManager.default.fileExists(atPath: projectPath) else {
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XCTFail("Video file not found at: \(projectPath)")
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return
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}
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let stats = try await processVideo(
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at: URL(fileURLWithPath: projectPath), expectLookingAway: false)
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// For inner video, most frames should detect gaze at center
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let centerRatio = Double(stats.centerFrames) / Double(max(1, stats.pupilDetectedFrames))
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log(
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"🎯 INNER video: \(String(format: "%.1f%%", centerRatio * 100)) frames detected as center (expected: >50%)"
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)
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log(
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" H-range: \(String(format: "%.3f", stats.minH)) to \(String(format: "%.3f", stats.maxH))"
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)
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log(
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" V-range: \(String(format: "%.3f", stats.minV)) to \(String(format: "%.3f", stats.maxV))"
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)
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log(
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" Face width: \(String(format: "%.3f", stats.avgFaceWidth)) (range: \(String(format: "%.3f", stats.minFaceWidth))-\(String(format: "%.3f", stats.maxFaceWidth)))"
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)
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attachLogs()
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// At least 50% should be detected as center when looking at screen
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XCTAssertGreaterThan(
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centerRatio, 0.5,
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"Looking at screen video should have >50% center detections. Log:\n\(logLines.joined(separator: "\n"))"
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)
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}
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struct VideoStats {
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var totalFrames = 0
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var faceDetectedFrames = 0
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var pupilDetectedFrames = 0
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var centerFrames = 0
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var nonCenterFrames = 0
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var minH = Double.greatestFiniteMagnitude
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var maxH = -Double.greatestFiniteMagnitude
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var minV = Double.greatestFiniteMagnitude
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var maxV = -Double.greatestFiniteMagnitude
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var minFaceWidth = Double.greatestFiniteMagnitude
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var maxFaceWidth = -Double.greatestFiniteMagnitude
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var totalFaceWidth = 0.0
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var faceWidthCount = 0
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var avgFaceWidth: Double {
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faceWidthCount > 0 ? totalFaceWidth / Double(faceWidthCount) : 0
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}
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}
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private func processVideo(at url: URL, expectLookingAway: Bool) async throws -> VideoStats {
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var stats = VideoStats()
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log("\n" + String(repeating: "=", count: 60))
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log("Processing video: \(url.lastPathComponent)")
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log(
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"Expected behavior: \(expectLookingAway ? "LOOKING AWAY (non-center)" : "LOOKING AT SCREEN (center)")"
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)
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log(String(repeating: "=", count: 60))
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let asset = AVURLAsset(url: url)
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let duration = try await asset.load(.duration)
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let durationSeconds = CMTimeGetSeconds(duration)
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log("Duration: \(String(format: "%.2f", durationSeconds)) seconds")
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guard let track = try await asset.loadTracks(withMediaType: .video).first else {
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XCTFail("No video track found")
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return stats
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}
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let size = try await track.load(.naturalSize)
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let frameRate = try await track.load(.nominalFrameRate)
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log(
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"Size: \(Int(size.width))x\(Int(size.height)), FPS: \(String(format: "%.1f", frameRate))"
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)
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let reader = try AVAssetReader(asset: asset)
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let outputSettings: [String: Any] = [
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kCVPixelBufferPixelFormatTypeKey as String: kCVPixelFormatType_32BGRA
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]
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let trackOutput = AVAssetReaderTrackOutput(track: track, outputSettings: outputSettings)
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reader.add(trackOutput)
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reader.startReading()
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var frameIndex = 0
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let sampleInterval = max(1, Int(frameRate / 2)) // Sample ~2 frames per second
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log("\nFrame | Time | Face | H-Ratio L/R | V-Ratio L/R | Direction")
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log(String(repeating: "-", count: 75))
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// Reset calibration for fresh test
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PupilDetector.calibration.reset()
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// Disable frame skipping for video testing
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let originalFrameSkip = PupilDetector.frameSkipCount
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PupilDetector.frameSkipCount = 1
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defer { PupilDetector.frameSkipCount = originalFrameSkip }
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while let sampleBuffer = trackOutput.copyNextSampleBuffer() {
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defer {
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frameIndex += 1
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PupilDetector.advanceFrame()
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}
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// Only process every Nth frame
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if frameIndex % sampleInterval != 0 {
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continue
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}
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stats.totalFrames += 1
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guard let pixelBuffer = CMSampleBufferGetImageBuffer(sampleBuffer) else {
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continue
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}
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let timestamp = CMSampleBufferGetPresentationTimeStamp(sampleBuffer)
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let timeSeconds = CMTimeGetSeconds(timestamp)
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// Run face detection
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let request = VNDetectFaceLandmarksRequest()
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request.revision = VNDetectFaceLandmarksRequestRevision3
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let handler = VNImageRequestHandler(
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cvPixelBuffer: pixelBuffer,
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orientation: .leftMirrored,
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options: [:]
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)
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try handler.perform([request])
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guard let observations = request.results, !observations.isEmpty,
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let face = observations.first,
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let landmarks = face.landmarks,
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let leftEye = landmarks.leftEye,
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let rightEye = landmarks.rightEye
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else {
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log(
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String(
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format: "%5d | %5.1fs | NO | - | - | -",
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frameIndex, timeSeconds))
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continue
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}
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stats.faceDetectedFrames += 1
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// Track face width (bounding box width as ratio of image width)
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let faceWidth = face.boundingBox.width
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stats.minFaceWidth = min(stats.minFaceWidth, faceWidth)
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stats.maxFaceWidth = max(stats.maxFaceWidth, faceWidth)
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stats.totalFaceWidth += faceWidth
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stats.faceWidthCount += 1
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let imageSize = CGSize(
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width: CVPixelBufferGetWidth(pixelBuffer),
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height: CVPixelBufferGetHeight(pixelBuffer)
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)
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// Detect pupils
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var leftHRatio: Double?
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var rightHRatio: Double?
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var leftVRatio: Double?
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var rightVRatio: Double?
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if let leftResult = PupilDetector.detectPupil(
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in: pixelBuffer,
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eyeLandmarks: leftEye,
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faceBoundingBox: face.boundingBox,
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imageSize: imageSize,
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side: 0
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) {
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leftHRatio = calculateHorizontalRatio(
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pupilPosition: leftResult.pupilPosition, eyeRegion: leftResult.eyeRegion)
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leftVRatio = calculateVerticalRatio(
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pupilPosition: leftResult.pupilPosition, eyeRegion: leftResult.eyeRegion)
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}
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if let rightResult = PupilDetector.detectPupil(
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in: pixelBuffer,
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eyeLandmarks: rightEye,
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faceBoundingBox: face.boundingBox,
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imageSize: imageSize,
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side: 1
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) {
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rightHRatio = calculateHorizontalRatio(
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pupilPosition: rightResult.pupilPosition, eyeRegion: rightResult.eyeRegion)
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rightVRatio = calculateVerticalRatio(
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pupilPosition: rightResult.pupilPosition, eyeRegion: rightResult.eyeRegion)
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}
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if let lh = leftHRatio, let rh = rightHRatio,
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let lv = leftVRatio, let rv = rightVRatio
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{
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stats.pupilDetectedFrames += 1
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let avgH = (lh + rh) / 2.0
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let avgV = (lv + rv) / 2.0
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// Track min/max ranges
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stats.minH = min(stats.minH, avgH)
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stats.maxH = max(stats.maxH, avgH)
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stats.minV = min(stats.minV, avgV)
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stats.maxV = max(stats.maxV, avgV)
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let direction = GazeDirection.from(horizontal: avgH, vertical: avgV)
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if direction == .center {
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stats.centerFrames += 1
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} else {
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stats.nonCenterFrames += 1
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}
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log(
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String(
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format: "%5d | %5.1fs | YES | %.2f / %.2f | %.2f / %.2f | %@ %@",
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frameIndex, timeSeconds, lh, rh, lv, rv, direction.rawValue,
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String(describing: direction)))
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} else {
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log(
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String(
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format: "%5d | %5.1fs | YES | PUPIL FAIL | PUPIL FAIL | -",
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frameIndex, timeSeconds))
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}
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}
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log(String(repeating: "=", count: 75))
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log(
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"Summary: \(stats.totalFrames) frames sampled, \(stats.faceDetectedFrames) with face, \(stats.pupilDetectedFrames) with pupils"
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)
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log("Center frames: \(stats.centerFrames), Non-center: \(stats.nonCenterFrames)")
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log(
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"Face width: avg=\(String(format: "%.3f", stats.avgFaceWidth)), range=\(String(format: "%.3f", stats.minFaceWidth)) to \(String(format: "%.3f", stats.maxFaceWidth))"
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)
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log("Processing complete\n")
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return stats
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}
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private func calculateHorizontalRatio(pupilPosition: PupilPosition, eyeRegion: EyeRegion)
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-> Double
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{
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// pupilPosition.y controls horizontal gaze due to image orientation
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let pupilY = Double(pupilPosition.y)
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let eyeHeight = Double(eyeRegion.frame.height)
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guard eyeHeight > 0 else { return 0.5 }
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let ratio = pupilY / eyeHeight
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return max(0.0, min(1.0, ratio))
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}
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private func calculateVerticalRatio(pupilPosition: PupilPosition, eyeRegion: EyeRegion)
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-> Double
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{
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// pupilPosition.x controls vertical gaze due to image orientation
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let pupilX = Double(pupilPosition.x)
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let eyeWidth = Double(eyeRegion.frame.width)
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guard eyeWidth > 0 else { return 0.5 }
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let ratio = pupilX / eyeWidth
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return max(0.0, min(1.0, ratio))
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}
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}
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