hand_detection 3.3.0

Hand, gesture and landmark detection using on-device TFLite models

3.3.0

• Add MediaPipe-style detection + tracking: pass enableTracking: true to HandDetector.create / initialize / initializeFromBuffers. Each detected hand is followed frame-to-frame via a rotated region of interest derived from its own landmarks (wrist to middle-finger-MCP orientation, tight landmark box expanded 2x), and the palm detector only runs to acquire new hands or re-acquire lost ones. This removes the per-frame palm re-detection drop-outs on video and live camera (a sample origami clip went from 90% to 100% of frames with a hand at the same 0.5 thresholds). Off by default; existing behavior is unchanged.
• Add HandDetector.resetTracking() to clear the cross-frame tracking state between unrelated inputs (a new video, or independent still images). Safe to call when tracking is disabled; no-op on web.
• Tracking ROIs are gated by minLandmarkScore (keep it near 0.5 with tracking; permissive thresholds let garbage frames perpetuate) and guarded against degenerate or runaway regions, so a bad frame falls back to palm re-detection instead of drifting.
• Web: enableTracking is accepted for cross-platform API parity (the web implementation still runs palm detection every frame).
• Example app: the Live Camera and Video File screens expose a tracking toggle in their settings, off by default.
• Expose palm post-processing tuning on HandDetector.create / initialize / initializeFromBuffers: palmNmsIou (palm non-maximum-suppression IoU) and palmRoiScale (how much the palm box is expanded before it is cropped for the landmark model). Both were previously hardcoded (0.45 / 2.6); the defaults are unchanged.
• Add TrackingConfig to tune the cross-frame tracked ROI (roiScale, roiShiftY, associationIou, minRoiSize, maxRoiSize), passed via trackingConfig:. These were previously hardcoded constants; the defaults port MediaPipe's hand tracking graph and are unchanged. Only takes effect when enableTracking is true.
• Web: palmNmsIou / palmRoiScale are honored (they feed the shared palm post-processing), and the web palm detector now applies detectorConf (previously accepted but ignored). trackingConfig is accepted for API parity but ignored (web has no ROI tracking yet).

3.2.0

• Update flutter_litert -> 3.2.0
• Import native-only flutter_litert APIs via package:flutter_litert/native.dart so they resolve under static analysis (flutter_litert 3.2.0 moved InterpreterPool, IsolateWorkerBase, and TensorFloat32Views behind the native conditional export). No runtime or API change.
• Default the public entry's conditional export to the web implementation, gating native behind dart.library.io, restoring WASM compatibility (pub.dev WASM-ready). No behavior change on any platform.
• Add package:hand_detection/hand_detection_native.dart, a native-only entry point that re-exports the native implementation for code that runs only on native platforms.

3.1.2

• Update flutter_litert -> 3.1.1

3.1.1

• Update flutter_litert -> 2.8.3

3.1.0

• Update flutter_litert -> 2.8.0
• Complete Swift Package Manager migration: example apps build via SPM without CocoaPods

3.0.7

• Remove unused Darwin podspecs for Dart-only iOS/macOS plugin registration.

3.0.6

• Update flutter_litert -> 2.5.8

3.0.5

• Update flutter_litert -> 2.5.5

3.0.4

• Update flutter_litert to 2.5.3 and camera_desktop to 1.1.4

3.0.3

• Update flutter_litert -> 2.5.2

3.0.2

• Update flutter_litert -> 2.5.0

3.0.1

• Update flutter_litert -> 2.4.1

3.0.0

Breaking:

• HandDetector configuration moves from the constructor to initialize(). HandDetector({mode: ..., landmarkModel: ..., ...}) → HandDetector() + await detector.initialize(mode: ..., landmarkModel: ..., ...). Matches FaceDetector's shape. HandDetector.create({...}) continues to accept the same named params unchanged.

• HandDetector.detect now takes Uint8List instead of List<int>. Callers passing a plain List<int> must convert (Uint8List.fromList(...)); callers already passing Uint8List (including File.readAsBytes() and camera plugin bytes) are unaffected.

• detect(...) no longer swallows exceptions. Previously, malformed image bytes resolved to an empty list; now they surface as an exception. Genuine errors (StateError, isolate failures, dispose races) also propagate. Wrap detect(...) in a try/catch if your callsite depended on the previous silent-failure behavior.

• HandDetector now runs all TFLite inference in a dedicated background isolate automatically, keeping the UI thread free.

• Deprecate HandDetectorIsolate: use HandDetector directly. HandDetectorIsolate is kept as a thin wrapper for backward compatibility and will be removed in a future release.

• Add HandDetector.create({...}) static factory for one-step construction and initialization (mirrors FaceDetector.create).

• Add detectFromFilepath(String path) convenience method.

• Add detectFromMatBytes(Uint8List, {required int width, required int height, int matType}) fast path: transfers raw pixel bytes to the background isolate via zero-copy TransferableTypedData, avoiding cv.Mat construction on the calling thread.

• Rename detectOnMat to detectFromMat and detectOnMatBytes to detectFromMatBytes for naming parity with face_detection_tflite; old names kept as deprecated aliases.

• Expand flutter_litert re-exports through the hand_detection barrel to match face_detection_tflite: tensor helpers (createNHWCTensor4D, fillNHWC4D, allocTensorShape, flattenDynamicTensor), math helpers (sigmoid, sigmoidClipped, clamp01, clip), letterbox helpers (computeLetterboxParams, LetterboxParams), BGR→RGB byte helpers (bgrBytesToRgbFloat32, bgrBytesToSignedFloat32), and PerformanceMode. Consumers no longer need a direct flutter_litert import for these.

• Update example app to use HandDetector.create() instead of HandDetectorIsolate.spawn().

• Rewrite README's Live Camera Detection section around the shared packYuv420 + native cv.cvtColor pattern, and drop the "Background Isolate Detection" / "OpenCV Mat Support" sections that pointed users at the deprecated HandDetectorIsolate.

2.1.2

• Add public HandDetector.modelVersion and HandDetector.modelVersionFor(...) APIs for downstream cache invalidation.

2.1.1

• Fix iOS camera preview lifecycle in example

2.1.0

• Fix Android live camera in the example app:
  • Replace the per-pixel Dart YUV→BGR loop with flutter_litert's shared packYuv420 helper + native cv.cvtColor, matching face_detection_tflite.
  • _rotationFlagForFrame now handles all four device orientations (portrait up/down, landscape left/right) via a combined sensorOrientation + DeviceOrientation formula. Previously only one of the two landscape directions rendered correctly; the other was 180° off.
  • Mirror the detection overlay on Android front camera to match CameraPreview's auto-mirrored preview texture.
• Align example app live-camera layout with face_detection_tflite: Material+Row top bar (replaces AppBar), flip-camera button, FPS + detection-time display, rotating top bar in landscape with safe-area padding, and a settings popup housing hand-specific controls (Max Hands slider, gesture toggle).
• Re-export packYuv420, YuvPlane, YuvLayout, and PackedYuv from flutter_litert through the hand_detection barrel.
• Update flutter_litert to ^2.2.0.

2.0.9

• Update flutter_litert -> 2.1.0

2.0.8

• Update flutter_litert to 2.0.13

2.0.7

• Update flutter_litert -> 2.0.12

2.0.6

• Update flutter_litert 2.0.10 -> 2.0.11

2.0.5

• Update documentation

2.0.4

• Update flutter_litert 2.0.8 -> 2.0.10

2.0.3

• Enable auto hardware acceleration by default (XNNPACK on all native platforms, Metal GPU on iOS)
• Update flutter_litert 2.0.6 -> 2.0.8

2.0.2

• Update flutter_litert 2.0.5 -> 2.0.6

2.0.1

• Fix Xcode build warnings by declaring PrivacyInfo.xcprivacy as a resource bundle in iOS and macOS podspecs

2.0.0

Breaking: Point now uses double coordinates. BoundingBox.toMap() format changed to corner-based.

• Use shared Point and BoundingBox from flutter_litert 2.0.0
• toPixel() now returns full-precision double coordinates (was truncating to int)
• Remove duplicate NMS implementation, use shared nms() from flutter_litert
• Refactor isolate worker to use IsolateWorkerBase from flutter_litert
• Simplify model classes (PalmDetector, HandLandmarkModel, GestureRecognizer)
• Remove integration tests from unit test suite
• Remove dead test helpers (test_config.dart)

1.0.3

• Update camera_desktop 1.0.1 -> 1.0.3

1.0.2

• Update flutter_litert -> 1.2.0
• Refactor to use flutter_litert shared utilities (InterpreterFactory, InterpreterPool, PerformanceConfig, generateAnchors)

1.0.1

• Update opencv_dart 2.1.0 -> 2.2.1
• Update flutter_litert 1.0.2 -> 1.0.3

1.0.0

First stable release of hand_detection

Pipeline

• Palm detection, SSD model with rotation-aware bounding boxes
• Hand landmarks, 21-point 3D landmarks with visibility scores
• Gesture recognition, 7 gestures (fist, open palm, pointing up, thumbs down/up, victory, I love you)
• Handedness, Left/right classification

Features

• Two modes: HandMode.boxes (bounding boxes only) and HandMode.boxesAndLandmarks (full landmarks)
• HandDetectorIsolate for background-thread inference with zero-copy transfer
• Direct cv.Mat input for live camera processing
• XNNPACK hardware acceleration with configurable thread count
• Configurable confidence thresholds and detection limits

Platforms

• iOS, Android, macOS, Windows, Linux

0.0.4

• Update documentation

0.0.3

• Update flutter_litert to 1.0.1, camera to 0.12.0

0.0.2

• Update flutter_litert to 0.2.2

0.0.1

• Initial release