flutter_litert 2.8.2

LiteRT (formerly TensorFlow Lite) Flutter plugin. Drop-in on-device ML inference with bundled native libraries for supported native platforms and web runtimes.

2.8.2

• Fix GPU and CoreML delegates silently falling back to CPU on macOS and iOS (#11). macOS now bundles the GPU/CoreML dylibs that were previously omitted from the Swift Package manifest. iOS retains all 212 packaged LiteRT, Metal, and CoreML symbols that Dart FFI resolves but linker stripping would otherwise drop. They are kept through a generated anchor on both CocoaPods and SPM, plus an embedded dynamic SPM framework so they survive App Store archive stripping. This extends the 2.8.0 mitigation (#8, #9) to every packaged API.
• Log delegate initialization failures before falling back to CPU. A packaging regression can no longer masquerade as unexpectedly slow GPU/CoreML performance.
• On Apple Silicon the Metal GPU is substantially faster for conv-heavy models once actually loaded (for example, selfie segmentation ~27ms -> ~3ms versus XNNPACK).

2.8.1

• Complete the AGP 9 / built-in Kotlin fix from 2.8.0 (#10). 2.8.0 resolved the "Inconsistent JVM-target ... (17) and (21)" error on the AGP 8.11 transitional path, but a full migration to android.builtInKotlin=true on AGP 9 still failed with "The 'org.jetbrains.kotlin.android' plugin is no longer required since AGP 9.0": the Flutter Gradle plugin auto-applies the legacy Kotlin plugin to this module, and AGP 9 rejects it. The plugin now applies kotlin-android only on AGP < 9 (which also stops Flutter from auto-applying it), and keeps the JVM-target pin guarded so the AGP-9-without-built-in-Kotlin case is skipped. Verified building against AGP 8.11.1 and 9.0.1 with built-in Kotlin both enabled and disabled.

2.8.0

• Fix the "Inconsistent JVM-target compatibility detected ... (17) and (21)" Android build failure under AGP 9 / Flutter 3.44+ (#10). The fix pins the Kotlin JVM target to 17 only when AGP >= 9 is in use, so older Flutter/AGP toolchains are unaffected and the minimum supported versions are unchanged.
• Fix iOS "Failed to lookup symbol 'TfLiteInterpreterOptionsCreate'" crash on App Store / TestFlight builds (#8, #9). The TFLite C symbols are resolved at runtime via dlsym and were stripped during App Store distribution; the CocoaPods podspec now disables that stripping on the app target so no manual Xcode build-setting changes are required.

2.7.0

• Add InterpreterOptions.addCustomOp(...): high-level method for registering custom TFLite ops; handles native string allocation and lifetime internally, replacing the previous raw tfliteBinding call pattern.
• Add Interpreter.fromBytes(Uint8List): async cross-platform constructor, matching the web API. Native platforms complete immediately; unsupported stub throws UnsupportedError.
• Rename lastNativeInferenceDurationMicroSeconds → lastInferenceDurationMicroseconds on Interpreter, SignatureRunner, and LiteRtInterpreter (all platform variants). Old name kept as a @Deprecated alias.
• Rename configureLiteRtLoader → configureLiteRtWebLoader. Old name kept as a @Deprecated alias and re-exported from all_web.dart.
• Fix camera_frame.dart: widen .planes cast from List<dynamic> to Iterable<dynamic> for broader compatibility.

2.6.0

• Fix iOS Swift Package Manager builds: repackage the bundled TensorFlowLite xcframeworks (correct simulator slice identifiers and framework structure) so they resolve under SPM, including on the iOS simulator.
• Add a standalone example that depends only on flutter_litert and opencv_dart.

2.5.8

• Raise minimum deployment targets to iOS 13.0 / macOS 10.15 to satisfy Swift Package Manager's FlutterFramework requirement (fixes SPM build failures on macOS/iOS).
• Update example and documentation to use flutter_litert_flex: ^1.0.0.

2.5.7

• Update example to use flutter_litert_flex: ^0.0.8.

2.5.6

• Fix SPM: add missing FlutterFramework dependency to iOS and macOS Package.swift.

2.5.5

• Add SPM support for iOS: TensorFlowLiteC, TensorFlowLiteCMetal and TensorFlowLiteCCoreML are now declared as binary targets in Package.swift so the plugin works with Flutter Swift Package Manager integration.
• Fix duplicate XNNPack symbol linker errors when flutter litert flex is used alongside flutter litert by removing XNNPack definitions from TFLiteFlex and hiding overlapping symbols in TensorFlowLiteC via nmedit.
• Fix stale flex dedup marker in podspec that caused nmedit to be skipped on re-downloaded xcframeworks.

2.5.4

• Fix WASM compatibility: replace dart:io import in camera_frame.dart with flutter/foundation.dart to allow package to compile under the WASM runtime.

2.5.3

• prepareCameraFrameFromImage and prepareCameraFrame now auto-detect isBgra based on platform. macOS uses BGRA, Windows and Linux use RGBA. The isBgra parameter is now nullable and no longer needs to be passed manually.

2.5.2

• Update documentation

2.5.1

• Add decodeBitmap(Uint8List bytes) free function: decodes encoded image bytes (JPEG, PNG, etc.) to a web.ImageBitmap via createImageBitmap, off the main thread.
• Add WebGpuFallback mixin: transparent WebGPU-to-WASM runtime fallback for web detector classes. Provides withFallback<T>() which catches GPU errors, swaps all runners to WASM via swapToWasm(), and retries once. Apply with with WebGpuFallback; implement activeAccelerator and swapToWasm().
• Both exported from package:flutter_litert/flutter_litert.dart on web.

2.5.0

• Add LiteRtInterpreter, an alternative web inference path backed by Google's official LiteRT.js runtime (@litertjs/core). Selectable at construction time via LiteRtInterpreter.fromBytes(bytes, accelerator: 'webgpu' | 'wasm'), with automatic fallback from webgpu to wasm when ops aren't supported by the GPU delegate.
  • Surface chosen to match the Interpreter hot path used by detector packages: fromBytes, getInputTensor / getOutputTensors, runForMultipleInputs(inputs, outputs). runForMultipleInputs is async (LiteRT.js run returns a Promise).
  • Output buffers can be supplied as Float32List, ByteBuffer, or the legacy nested List<List<List<double>>> shape used by tflite-js callers; the float-typed buffer paths take a single bulk copy.
  • Read paths use JSFloat32Array.toDart directly, skipping the dataSync().dartify() round-trip.
  • Faster output readback in the existing tflite-js Interpreter._tensorFromJSTensor: replaces dataSync().dartify() as List<double> + Float32List.fromList(...) with a single bulk copy via JSTensorExtensions.dataSyncFloat32. ~25 ms / call savings on a 705k-element YOLOv8n output.
  • Auto-loader: by default the first LiteRtInterpreter.fromBytes(...) call programmatically appends a <script type="module"> to <head> that imports @litertjs/core from jsDelivr and calls loadLiteRt(...); consumers don't have to touch their web/index.html. Override URLs (for self-hosting / strict CSP) or disable auto-loading via configureLiteRtLoader(moduleUrl: ..., wasmUrl: ..., autoLoad: ...). Existing host-page loaders that assign window.LiteRt and dispatch a litert-ready event still work.
  • Pure additive: native and unsupported targets are unchanged; the existing tflite-js Interpreter remains the default web runtime.

2.4.1

• Make camera_overlay.dart WASM-compatible on Flutter Web

2.4.0

• Add painter primitives drawLandmarkMarker, drawSkeletonConnections, and drawBoundingBoxOutline for reuse by detector example apps and overlay widgets. Pure Dart + dart:ui, no new dependencies.

2.3.0

• Add camera-overlay helpers used across detector example apps: rotationForFrame, detectionSize, coverFitScaleOffset, barQuarterTurns, and FpsCounter. All pure Dart + Flutter SDK, no new dependencies. Lets example apps drop ~200 lines of duplicated orientation / sizing / FPS boilerplate.

2.2.2

• Add prepareCameraFrameFromImage, a duck-typed wrapper around prepareCameraFrame that accepts a CameraImage-shaped object directly (any object exposing width, height, planes with bytes/bytesPerRow/bytesPerPixel). Lets detector packages expose one-line camera-stream APIs without adding package:camera as a dependency here. Pure Dart, no new dependencies.

2.2.1

• Add prepareCameraFrame helper plus CameraFrame, CameraFrameConversion, and CameraFrameRotation types. Describes a camera frame (YUV420 or packed BGRA/RGBA) in a pure-Dart descriptor that detector packages can hand to their existing detection isolate, moving the cvtColor / rotate work off the UI thread without adding opencv_dart as a dependency here.
• Add CameraPlane typedef (structurally identical to YuvPlane; use whichever name reads better at the call site).
• Add TensorFloat32Views (native only): captures Float32List views of an Interpreter's input/output tensors once after allocateTensors, letting detector packages reuse the same view wrappers on every inference instead of recreating them per-call. Pure Dart, no new dependencies.

2.2.0

• Add packYuv420 helper for packing NV12 / NV21 / I420 camera frames into a contiguous buffer

2.1.0

• Minor performance/accuracy optimizations:
  • Remove unnecessary rounding in fillNHWC4D
  • Add direct Float32List fast paths for common tensor flattening shapes

2.0.13

• Fix Android JVM target mismatch: bump Java compile target to 17 to match Kotlin target set by Flutter toolchain

2.0.12

• Fix Android Flutter beta builds by aligning Kotlin and Java JVM targets to 11

2.0.11

• Fix edge case in output buffer allocation

2.0.10

• Update documentation

2.0.9

• Enable XNNPACK delegate on Android (ARM NEON SIMD acceleration in auto mode)
• Allow explicit PerformanceConfig.xnnpack() on iOS
• Initialize XNNPackDelegateOptions from native defaults (preserves QS8/QU8 quantization flags)

2.0.8

• Add Windows XNNPack delegate support (2-5x CPU inference speedup via SIMD)
• Add CI workflow to build Windows TFLite C DLL from source with XNNPack symbols

2.0.7

• Fix Android custom ops library alignment for 16 KB page-size devices

2.0.6

• Add useIsolateInterpreter parameter to skip nested isolate creation

2.0.5

• Fix native crash during repeated inference by removing unsafe output tensor writeback

2.0.4

• Fix macOS native crashes by disabling auto IsolateInterpreter for no-delegate interpreters.

2.0.3

• Fix WASM compatibility: move dart:isolate imports behind conditional exports so web compilation path is WASM-safe

2.0.2

• Fix: use-after-free when interpreter reads model weights from freed buffer, transfer buffer ownership from Model to Interpreter

2.0.1

• Add IsolateWorkerBase for shared isolate lifecycle management
• Add RoundRobinPool generic round-robin pool utility
• Add TensorType enum, LandmarkMixin, listUtils shared helpers
• Add weighted NMS with spatial grid optimization to nms()
• Consolidate platform-specific byte conversion into shared implementation
• Consolidate platform-specific tensor logic (native/web/unsupported)
• Consolidate desktop library loading into DelegateLibraryLoader
• Remove dead files: all_unsupported.dart, version.dart, flutter_litert_method_channel.dart, flutter_litert_platform_interface.dart
• Fix: Model buffer leak, delegate options leak, stale tensor cache

2.0.0

Breaking: Point.x and Point.y changed from int to double.

• Upgrade Point to double-precision with optional z depth, ==/hashCode, toMap()/fromMap(), is3D
• Add shared BoundingBox class (4-corner Point-based, supports rotated boxes)
  • BoundingBox.ltrb() factory for axis-aligned boxes
  • left/top/right/bottom convenience getters
  • width, height, center, corners computed properties
  • toMap()/fromMap() serialization

1.4.0

• Fix tensor cache bug, add shared Point class, dedup internals

1.3.1

• Add NaN handling to clamp01(), returns 0.0 for NaN inputs

1.3.0

• Add IsolateRpcClient and setupIsolateHandshake for reusable isolate request/response communication

1.2.0

• Add shared ML utility functions
  • sigmoid, sigmoidClipped, clip, clamp01, argSortDesc, median, normalizeRadians (math utilities)
  • iouXYXY, nms (non-maximum suppression)
  • computeLetterboxParams, computeAspectPadParams, LetterboxParams, AspectPadParams (image preprocessing)
  • bgrBytesToRgbFloat32, bgrBytesToSignedFloat32, fillNHWC4DFromBgrBytes (image-to-tensor conversion)
  • allocTensorShape, createOutputBuffers, zeroOutputBuffers, createNHWCTensor4D, fillNHWC4D, flattenDynamicTensor (tensor allocation)
  • decodeDetectionOutputs, transpose2D, concat0, ensure2D, xywhToXyxy (model output decoding)
  • postProcessDetections, Detection, decodeAndSplitOutputs (end-to-end detection post-processing with NMS)

1.1.1

• Fix package layout to follow Pub conventions

1.1.0

• Add PerformanceConfig and PerformanceMode,
• Add InterpreterFactory and InterpreterPool
• Add generateAnchors() and SSDAnchorOptions
• Add scaleFromLetterbox() utility for letterbox-to-original coordinate mapping

1.0.3

• Add SignatureRunner for on-device training workflows (train, infer, get_weights, set_weights signatures)
• Add Linux FlexDelegate support via flutter_litert_flex (Linux x86_64, built from TF 2.20.0 source). All three desktop platforms (macOS, Windows, Linux) now fully support on-device training with SELECT_TF_OPS models and checkpoint save/restore.
• Add Interpreter.signatureCount, signatureKeys, getSignatureKey(), getSignatureRunner()
• Add SignatureRunner.cancel(), getInputTensors(), getOutputTensors(), lastNativeInferenceDurationMicroSeconds

1.0.2

• Add native dylibs to SPM Package.swift
• Update Dart loading paths for SPM bundle

1.0.1

• Improve Custom Ops documentation

1.0.0

• Upgrade Linux TFLite native library from 2.9.3 to 2.20.0 (built from source via CMake + Ninja + GCC x86_64)
• First stable release:
  • All platforms are on updated 2.20.0 library files, official final stable release of TFLite
  • Pre-bundling works on supported native platforms: users no longer need to bundle native libraries manually as was required with tflite_flutter
  • Custom ops supported, see face_detection_tflite v5.0.2 example directory for a working example (the binary segmentation model selfie_segmenter.tflite uses custom ops)
  • Web support (experimental) functional, see pose_detection v1.0.1 web_example directory for a working example

0.2.2

• Update dependencies

0.2.1

• Update documentation

0.2.0

• Web support (experimental)

0.1.16

• Register iOS pluginClass

0.1.15

• Add missing null check in interpreter teardown path on macOS

0.1.14

• Improve IsolateInterpreter shutdown reliability on iOS to prevent rare use-after-free when closing during active inference

0.1.13

• Add Swift Package Manager (SPM) support for iOS and macOS

0.1.12

• Upgrade Windows TFLite native library from 2.18.0 to 2.20.0 (built from source via CMake + Ninja + MSVC x64)

0.1.11

• Fix iOS: download xcframeworks at pod install time so static linking works on first build

0.1.10

• Fix macOS: bundle native libraries in pub package so flutter test works without manual setup

0.1.9

• Fix iOS and macOS podspec compatibility with Ruby 3.4+ (Prism parser)

0.1.8

• Upgrade iOS TensorFlow Lite from 2.17.0 (CocoaPods) to 2.20.0 (built from source via Bazel)
• Replace CocoaPods TensorFlowLiteSwift dependency with vendored xcframeworks (TensorFlowLiteC, Metal delegate, CoreML delegate)
• All xcframeworks support device arm64 + simulator arm64/x86_64 (Apple Silicon and Intel Macs)

0.1.7

• Improved documentation

0.1.6

• Upgrade macOS TFLite native library from 2.17.1 to 2.20.0 (latest stable, universal binary: arm64 + x86_64)
• Update all C API headers to TFLite 2.20.0
• Regenerate FFI bindings (TfLiteOperatorCreate now takes 4 params, TfLiteOperatorCreateWithData removed, new kTfLiteOutputShapeNotKnown status, new builtin ops)
• Rebuild macOS custom ops dylib against 2.20.0

0.1.5

• Upgrade macOS TFLite native library from 2.11.0 to 2.17.1 (universal binary: arm64 + x86_64)
• Update all C API headers to TFLite 2.17.1 (including new TfLiteOperator API replacing TfLiteRegistrationExternal)
• Regenerate FFI bindings with new APIs (SignatureRunner, TfLiteInterpreterCancel, and more)
• Rebuild macOS custom ops dylib as universal binary (arm64 + x86_64)

0.1.4

• Bundle libtensorflowlite_c-win.dll from flutter_litert Windows plugin instead of downstream packages

0.1.3

• Fix Windows: build and bundle custom ops DLL (tflite_custom_ops.dll) for MediaPipe models
• Fix heap corruption crash when switching between segmentation models (custom op name string was freed prematurely)

0.1.2

• Fix Linux: build and bundle custom ops library (libtflite_custom_ops.so) so MediaPipe models with custom ops (e.g. selfie segmentation) work on Linux

0.1.1

• Update AndroidManifest.xml

0.1.0

• Fix IsolateInterpreter thread-safety bug causing intermittent native crashes when hardware delegates are active

0.0.1

• Initial release, forked from tflite_flutter_custom v1.2.5
• Rebranded to flutter_litert for LiteRT ecosystem
• All native libraries bundled automatically
• Custom ops support (MediaPipe models)
• Full platform support: Android, iOS, macOS, Windows, Linux