Apparence-io/CamerAwesome

This system is a Flutter plugin that provides a comprehensive camera interface for capturing photos and videos across Android, iOS, and Web platforms. It features advanced image analysis capabilities, including real-time barcode scanning, face detection, and text recognition via Google ML Kit, alongside a modular architecture for multi-camera support and Picture-in-Picture previews. The plugin also includes a customizable UI framework with themeable controls, gesture-based zoom and focus, and a suite of photo filters for post-capture image processing.

14 changes.

This period established the foundational structure of the CamerAwesome plugin, including documentation, licensing, and linting configurations. It involved a major architectural overhaul, migrating the Android implementation to CameraX and replacing the legacy Dart method channels with a Pigeon-based platform channel interface. The example application was also reset and upgraded to modern Flutter and native standards to support new AI and multi-camera features.

23 changes.

The project underwent a significant architectural refactoring, introducing a centralized CameraContext and a structured Pigeon interface for native platform communication. This period also saw the expansion of the UI layer with comprehensive theming, gesture controls, and new widgets for filters, zoom, and media preview, alongside enhanced image analysis capabilities.

5 changes.

The iOS implementation of the Camerawesome plugin was refactored to support Swift Package Manager integration, involving a comprehensive restructuring of source files and headers. This work decomposed the monolithic camera logic into modular Objective-C controllers and utility classes, enhancing maintainability and adding compliance with Apple's privacy requirements.

A new RGBA model class has been introduced to represent pixel color data with red, green, blue, and alpha channels, providing a structured way to handle color values within the photo filters library.

lib/src/photofilters · high confidence

Added new Objective-C utility files in the iOS Utils directory to handle camera-specific conversions and selections. These include AspectRatioUtils for mapping aspect ratio strings to modes, CameraQualities for selecting optimal video capture presets based on device capabilities, CaptureModeUtils for converting capture mode types, FlashModeUtils for mapping flash settings, and SensorUtils for translating between iOS AVCaptureDeviceTypes and internal sensor type enums. These utilities support the underlying camera engine by providing standardized conversion logic for aspect ratios, video qualities, capture modes, flash states, and sensor hardware types.

ios/camerawesome/Sources/camerawesome/Utils · high confidence

A new zoom indicator UI component has been added to the camera interface. This widget displays the current zoom level and allows users to tap on specific zoom points (minimum, 1x, and maximum) to adjust the camera zoom. The indicator dynamically updates based on the camera's sensor configuration and provides visual feedback for the selected zoom level.

lib/src/widgets/zoom · high confidence

New utility files have been added to the photofilters module to support image processing capabilities. \color\_filter\_utils.dart\ and \image\_filter\_utils.dart\ provide functions for applying color adjustments such as saturation, hue rotation, grayscale, sepia, invert, brightness, hue saturation, contrast, color overlay, RGB scale, and addictive color effects. \convolution\_kernels.dart\ defines standard convolution kernels (e.g., sharpen, emboss, blur, Gaussian, edge detection) used for image filtering. \utils.dart\ includes helper functions for RGB to HSV and HSV to RGB conversions. These utilities enable the application to apply various visual filters to images.

lib/src/photofilters/utils · high confidence

New shell scripts have been added to the example project to streamline running integration tests. \run\_firebase\_test\_lab.sh\ and \run\_firebase\_test\_lab\_multicam.sh\ automate the build and execution of instrumentation tests on Firebase Test Lab for standard and concurrent camera scenarios, respectively. Additionally, \run\_native\_android\_tests.sh\ and \run\_native\_android\_multicam\_tests.sh\ provide direct Gradle wrappers for running native Android tests, while \run\_patrol.sh\ facilitates executing tests via the Patrol CLI.

example/scripts · high confidence

New utility files have been added to the example app to support image capture and processing workflows. file\_utils.dart provides a helper to generate temporary file paths for photos and videos, along with an extension to open saved files using the open\_filex package. mlkit\_utils.dart introduces an extension on AnalysisImage that converts camera frames into the InputImage format required by Google ML Kit, handling both NV21 and BGRA8888 pixel formats.

example/lib/utils · high confidence

The example application now includes a comprehensive set of new demonstration files in the \example/lib\ directory. These additions showcase advanced capabilities: AI-powered analysis with dedicated examples for barcode scanning (\ai\_analysis\_barcode.dart\), face detection (\ai\_analysis\_faces.dart\), and text recognition (\ai\_analysis\_text.dart\) using Google ML Kit; real-time image processing with filter application examples (\analysis\_image\_filter.dart\, \analysis\_image\_filter\_picker.dart\); and multi-camera integration (\multi\_camera.dart\) featuring Picture-in-Picture support. The library also provides extensive UI customization guides (\custom\_awesome\_ui.dart\, \custom\_theme.dart\, \custom\_ui\example\\*.dart\) and a new utility for checking simultaneous video and analysis capabilities (\camera\_analysis\_capabilities.dart\).

example/lib · high confidence

This change establishes the foundational structure for the CamerAwesome plugin by adding essential documentation and configuration files. It introduces a CONTRIBUTING.md guide for contributors, a comprehensive README.md (including a Chinese translation) detailing installation, platform-specific permissions, and feature parity, and a docs.json configuration for the documentation site. Additionally, it sets up an analysis\_options.yaml for linting, updates the .gitignore to exclude build artifacts and sensitive files, and replaces the placeholder LICENSE with the standard MIT license text.

(repo-wide) · high confidence

The preview widget area now supports a Picture-in-Picture mode, allowing a draggable, floating preview window for additional sensors alongside the main view. This is configured via \PictureInPictureConfig\ (position, draggability, builder) and rendered by \AwesomeCameraFloatingPreview\. The main fullscreen preview (\AwesomeCameraPreview\) now exposes \onPreviewTap\ and \onPreviewScale\ callbacks, enabling users to tap for focus (with a platform-specific \AwesomeFocusIndicator\) and pinch-to-zoom directly on the preview surface. These changes also include the underlying \AwesomeCameraGestureDetector\ and \AnimatedPreviewFit\ logic to handle gesture routing and smooth aspect-ratio/fit animations.

lib/src/widgets/preview · high confidence

The application now includes a new set of photo filters (AwesomeFilter) that can be applied to images. This update introduces several new filter presets, including Aden, Ashby, and Brannan, alongside existing options like AddictiveBlue, Clarendon, and Inkwell. These filters are defined in the new awesome\_filter.dart and awesome\_filters.dart files, providing users with additional creative options for enhancing their photos.

lib/src/orchestrator/models/filters · high confidence

The \lib/src/widgets\ area now includes three new widgets: \AwesomeCameraModeSelector\ for switching between capture modes (e.g., photo, video) via a pager, \AwesomeMediaPreview\ for displaying thumbnails of captured media with loading and error states, and \AwesomeSensorTypeSelector\ for switching between camera sensors (ultra-wide, wide, telephoto) with zoom indicators. These are exported via \widgets.dart\ and integrated into the \CameraAwesomeBuilder\ entry point, enabling users to interact with camera modes, view captured content, and switch lenses directly within the camera interface.

lib/src/widgets · high confidence

The orchestrator now supports two additional camera modes: analysis-only and preview. The new AnalysisCameraState allows running image analysis without displaying a preview or capturing media, while PreviewCameraState displays the camera feed without enabling photo or video captures. These states are integrated into the existing state machine alongside the standard photo, video, and recording states, allowing developers to use the camera for background processing or simple monitoring without the overhead of capture capabilities.

lib/src/orchestrator/states · high confidence

The example app now includes three new widget components to demonstrate advanced usage patterns. \BarcodePreviewOverlay\ provides a visual overlay that detects barcodes within a specific scan area and displays their content and status. \CustomMediaPreview\ offers a customizable view for displaying captured photos and videos, handling loading states and platform-specific UI elements. \MiniVideoPlayer\ is a lightweight widget for playing back recorded video files within the preview interface.

example/lib/widgets · high confidence

The filters location now includes a complete UI for selecting photo filters, introducing \AwesomeFilterWidget\ which manages the toggle state and layout, \AwesomeFilterButton\ for the trigger action, \AwesomeFilterSelector\ for the carousel-style preview list, and \AwesomeFilterNameIndicator\ to display the active filter's name. This change adds the visual components and interaction logic for the filter feature within this directory.

lib/src/widgets/filters · high confidence

The image analysis subsystem has been restructured with new model classes in the analysis module, including \AnalysisImage\ and its format-specific subclasses (NV21, BGRA8888, YUV420, JPEG) along with configuration and plane handling. This change introduces native conversion capabilities, allowing developers to convert analysis images to JPEG format on both Android and iOS, and adds support for the BGRA8888 format on iOS. The models now handle platform-specific image transformations and provide a unified interface for working with camera image analysis data across different platforms.

lib/src/orchestrator/models/analysis · high confidence

The layout package now exports three new reusable widgets: AwesomeCameraLayout, AwesomeTopActions, and AwesomeBottomActions. AwesomeCameraLayout assembles the camera UI, conditionally displaying filters for photo mode or a zoom selector on Android, while AwesomeTopActions and AwesomeBottomActions provide customizable top and bottom action bars with default buttons for flash, aspect ratio, location, capture, and media preview.

lib/src/widgets/layout · high confidence

Added a new set of reusable, theme-customizable camera control widgets (aspect ratio, camera switch, capture, flash, location, and pause/resume) in lib/src/widgets/buttons. These buttons support theming via AwesomeTheme/AwesomeButtonTheme, respect device rotation, and expose callback hooks for icon and tap behavior, giving users a consistent, customizable UI for camera interactions.

lib/src/widgets/buttons · high confidence

This change introduces a new theming system and several utility widgets within the \lib/src/widgets/utils\ directory to enhance UI customization. It adds \AwesomeTheme\ and \AwesomeThemeProvider\ to manage global styles, specifically allowing customization of button appearance (colors, size, shape, padding) and providing a pluggable \ButtonBuilder\ for custom button behaviors. Additionally, it includes \AwesomeBouncingWidget\ for tactile tap feedback with haptic support, \AwesomeCircleIcon\ for styled circular buttons, \AnimatedClipRect\ for animated reveal/hide effects, and \AwesomeOrientedWidget\ to automatically rotate UI elements based on device orientation.

lib/src/widgets/utils · high confidence

The legacy Objective-C wrapper (CamerawesomePlugin.m) and the original Swift plugin implementation (SwiftCamerawesomePlugin.swift) have been removed from the iOS classes directory. This cleanup eliminates the manual method channel registration and stub implementation that previously served as the plugin's entry point, indicating a migration to a different plugin architecture or code generation strategy.

ios/Classes · high confidence

The \pigeons\ directory now contains the core interface definition (\interface.dart\) and the generation script (\pigeon.sh\) that bridge the Dart layer with iOS and Android native code. This change establishes the data structures and method signatures for camera control, including sensor identification (back/front, wide-angle, telephoto), video recording options (quality, codec, FPS, audio), and EXIF preferences. It replaces or supplements previous ad-hoc communication mechanisms with a structured, code-generated contract for platform interactions.

pigeons · high confidence

The iOS camera preview implementation has been refactored to support Swift Package Manager. This change introduces new Objective-C source files (CameraDeviceInfo, CameraPreviewTexture, MultiCameraPreview, SingleCameraPreview) that manage camera session configuration, pixel buffer handling, and device controls (zoom, focus, brightness, flash). These components replace the previous structure to provide a more modular foundation for camera operations, including support for multi-camera setups and physical button integration.

ios/camerawesome/Sources/camerawesome/CameraPreview · high confidence

The iOS implementation of the Camerawesome plugin has been restructured to support Swift Package Manager integration. This change introduces a new \CamerawesomePlugin.m\ entry point that manages camera sensors, preview streams, and event channels, alongside autogenerated Pigeon serialization code (\Pigeon.m\) for cross-platform communication. Additionally, a \PrivacyInfo.xcprivacy\ manifest has been added to declare data collection practices, ensuring compliance with Apple's privacy requirements.

ios/camerawesome/Sources/camerawesome · high confidence

The iOS native headers in the \ios/camerawesome/Sources/camerawesome/include\ directory have been restructured to support Swift Package Manager. This change moves the main plugin interface (\CamerawesomePlugin.h\) from the legacy \ios/Classes\ path into the new SPM-compatible source tree and updates it to conform to \FlutterStreamHandler\. Additionally, a comprehensive set of new header files (including \AnalysisController\, \CameraDeviceInfo\, \MultiCameraPreview\, and \Pigeon\) has been added to this location to define the types, controllers, and interfaces required by the refactored architecture.

ios/camerawesome/Sources/camerawesome/include · high confidence

The Android native plugin has been rewritten to use the CameraX library, replacing the previous camera2-based implementation. This migration introduces support for new capture modes (preview-only and image-analysis-only), enables multi-camera (concurrent) support on compatible devices, and adds physical volume button handling via a background media session. The change also includes a new image analysis pipeline with format conversion utilities (NV21, YUV\_420, BGRA8888 to JPEG) and an auto-fit preview builder that correctly handles device rotation and aspect ratios.

android · high confidence

The Android example app has been updated to use the Flutter V2 embedding, which changes the MainActivity implementation to extend FlutterActivity and updates the AndroidManifest.xml to remove the deprecated FlutterApplication class and SplashScreenDrawable metadata. The app's package name and label have been updated, and the manifest now includes optional permissions for audio recording and location access, along with a queries block for text processing. Additionally, the launch theme has been adjusted to support dark mode via a new values-night/styles.xml file.

example/android · high confidence

The iOS example app has been upgraded to Xcode 15.1 and requires iOS 12.0 or later, reflecting a move to modern development practices. The app bundle name is now 'camera\_app' and includes updated usage descriptions for camera, microphone, and location services. The project structure has been modernized to use the Swift \@main\ entry point, CocoaPods for dependency management, and includes new native unit and UI test targets (RunnerTests and RunnerUITests) to support automated testing of the plugin's Swift implementation.

example/ios · high confidence

The example application has been replaced with a standard Flutter starter project, changing the app name to 'camera\_app' and updating the README with current documentation links. The project configuration has been updated to include a new analysis options file for linting, and the .gitignore file has been significantly expanded to exclude generated files, IDE artifacts, and platform-specific build outputs across Android, iOS, macOS, Windows, Linux, and Web. Additionally, the .metadata file now tracks migration state for all supported platforms.

example · high confidence

The camera orchestrator logic has been refactored into a new \CameraContext\ class, which now centrally manages the camera's state, configuration, and user interactions. This change consolidates handling for capture modes, sensor configurations, filters, and image analysis into a single context object, replacing the previous scattered orchestration approach. Users will experience more consistent state management, particularly regarding zoom retention when switching capture modes and improved focus handling on iOS, as the context now explicitly tracks and applies these settings during state transitions.

lib/src/orchestrator · high confidence

The \lib/src/orchestrator/models\ directory has been restructured with new model classes that define core camera behaviors. \CaptureMode\ now supports \photo\, \video\, \preview\, and a new \analysis\_only\ mode, allowing users to restrict the camera to specific functions. \SaveConfig\ provides a simplified API for configuring these modes, including options for video settings, EXIF preferences, and front-camera mirroring. Additionally, \SensorConfig\ manages real-time camera adjustments like flash mode, zoom, aspect ratio, and brightness, while new enums and classes (\Sensor\, \SensorType\, \CameraFlashes\, \VideoOptions\) provide granular control over hardware sensors and recording parameters.

lib/src/orchestrator/models · high confidence

The plugin has replaced its legacy MethodChannel implementation with a new Pigeon-generated interface (lib/pigeon.dart), introducing a more robust and type-safe communication layer between Dart and native code. This architectural shift brings several behavioral changes: the old \Camerawesome\ class and \Sensors\ enum have been removed in favor of the new \CamerawesomePlugin\ and \SensorConfig\ models, and the API now supports advanced features like multi-sensor configuration, video recording quality options, and image analysis formats. Users will need to update their initialization code to use the new \CameraAwesomeBuilder\ and \SensorConfig\ structures, as the previous direct method calls are no longer available.

lib · high confidence

The analysis subsystem now uses a dedicated AnalysisController to manage the lifecycle of image analysis, allowing users to explicitly start and stop the stream via start() and stop() methods rather than relying solely on auto-start behavior. This controller handles platform-specific setup (iOS vs. Android) and integrates with the plugin's image stream. Additionally, a new AnalysisPreview class is introduced to handle coordinate conversion between analysis images and the UI preview, correctly accounting for platform-specific differences such as Android's width/height inversion and sensor orientation.

lib/src/orchestrator/analysis · high confidence

Added two new exception classes, CameraNotReadyException and NoValidCaptureModeException, to the orchestrator's exception handling. These provide specific error messages to users when attempting to perform actions while the camera is still loading or when an invalid capture mode is selected during the preparation state.

lib/src/orchestrator/exceptions · high confidence

The file orchestrator now uses platform-specific implementations to handle capture request building and file content operations. On native platforms (IO), capture requests generate actual file paths in the temporary directory, while on Web, they return null paths. Similarly, file reading and writing are implemented using native file I/O on IO and XFile operations on Web, with stubs for other platforms. This change ensures correct file path generation and content handling across different execution environments.

lib/src/orchestrator/file · high confidence

The empty English localization file (strings\_en.arb) has been removed from the resources directory. This cleanup eliminates an unused asset that contained no translation keys, streamlining the localization structure without affecting any user-facing strings or application behavior.

res · high confidence

The auto-generated internationalization file (lib/generated/i18n.dart) has been removed from the project. This file previously handled locale resolution and provided the base structure for English localizations; its deletion indicates a shift in how localization is managed, likely moving away from this specific generated implementation.

lib/generated · high confidence

The iOS camera functionality has been restructured into a set of dedicated Objective-C controllers within the \Controllers\ directory, replacing the previous monolithic implementation. This change introduces specialized modules for handling image analysis (including a fix to swap red and blue channels in BGRA8888 JPEG conversion), EXIF metadata and GPS location embedding, live image streaming with FPS and overflow guards, video recording with configurable quality and codec options, and device sensor discovery. It also adds controllers for managing camera permissions, motion detection for orientation, multi-camera support checks, and physical button event listening, providing a more maintainable and feature-complete foundation for the plugin's iOS integration.

ios/camerawesome/Sources/camerawesome/Controllers · high confidence

The filter implementation in \lib/src/photofilters/filters\ has been refactored to ensure compatibility with the \image\ package version 4. This change introduces a new filter architecture with distinct \ColorFilter\ and \ImageFilter\ classes, along with corresponding sub-filters for effects like brightness, contrast, and convolution. A key behavioral update is in \ColorFilter.apply\, which now processes pixel data in 3-byte RGB steps (ignoring the alpha channel) instead of the previous 4-byte RGBA format, aligning with the new image package's pixel representation.

lib/src/photofilters/filters · high confidence

Added unit tests for image filters and updated test suite structure; Integration tests disabled pending Patrol 3.x migration; Removed outdated example widget test.

The Android example project now uses Gradle 8.12 instead of the previous version 5.6.2. This update ensures the build environment is aligned with modern Gradle standards, which may require users to have a compatible Java version installed and could affect build performance or compatibility with existing plugins.

example/android/gradle · high confidence

The plugin and example app have been upgraded to support modern Flutter versions (SDK \>=3.1.0/3.2.6) and Android tooling, including Android Gradle Plugin 7.3.1 and Kotlin 1.8.10. On Android, the implementation migrates to CameraX 1.4.2 and updates Google ML Kit dependencies to version 7.0 (via ML Kit 8.0/6.0), which requires a minimum SDK of 24 and compile SDK 34. On iOS, the example app now targets iOS 15.5 and uses the modern Flutter podfile setup, while the plugin adds a Swift Package Manager manifest for iOS 12+. These changes improve stability and access to the latest camera and image analysis capabilities.

(dependencies) · high confidence

Written by watchdog.canine.dev from the codebase's own history, inside the signed delivery this page is composed from.

• First survey — no prior run to compare against. CAI 61.

• Code Health 91
• Architecture 96
• Maturity 56
• Readiness 43
• Security 100
• Domain Modelling 100

• 300 commits — 223 feature/other, 77 fixes

• (repo) — 57 commits
• lib/src — 53 commits
• ios/Classes — 52 commits
• (root) — 36 commits
• android/src — 29 commits
• example/lib — 24 commits
• ios/camerawesome — 13 commits
• example/ios — 9 commits
• docs/getting_started — 8 commits
• docs/image_analysis — 3 commits
• lib/camerawesome_plugin.dart — 3 commits
• android/build.gradle — 2 commits
• docs/img — 2 commits
• example/android — 2 commits
• example/integration_test — 2 commits
• .run/analysis_native_conversion.run.xml — 1 commit
• doc/img — 1 commit
• example/pubspec.lock — 1 commit
• lib/pigeon.dart — 1 commit
• pigeons/interface.dart — 1 commit

• fix: FIX: Brightness commands
• fix: Fix alignment
• fix: Fix different previewFit for inverted moe
• fix: Fix first recording audio/video desync with proper frame synchronization
• fix: Fix lint errors
• fix: Fix orientation when device lock orientation
• fix: Fix previewAlignment
• fix: Fix previewAlignment
• fix: Fix previewAlignment and previewPadding
• fix: Fix setting zoom while stream is closed error
• fix: Fix(ios) setRecordingAudioMode not competed
• fix: Merge branch 'bug/camera-zoom' of github.com:Shamsudeen12/CamerAwesome into bug/camera-zoom
• fix: Merge branch 'master' into bug/camera-zoom
• fix: Merge pull request #305 from Apparence-io/fix/release-1.4.0
• fix: Merge pull request #307 from Apparence-io/fix/patrol_tests
• fix: Merge pull request #317 from juliuszmandrosz/fix/capture_button_bottom_actions
• fix: Merge pull request #570 from minimistapp/b/fix-421
• fix: Merge pull request #572 from juarezfranco/bugfix/preview-conflict-with-flutter
• fix: Merge pull request #578 from Apparence-io/fix/previewfit_contain
• fix: Merge pull request #595 from dyno-nexsoft/fix-orientation
• …and 280 more

• 0 containers · 1 bounded contexts · 0 dependency edges (baseline)

Written by watchdog.canine.dev from the codebase's own history, inside the signed delivery this page is composed from.

Apparence-io/CamerAwesome was measured the same way every project in this corpus was: the same rubric, at a pinned commit, with the result published in full. Point a surveyor at a repository you know and see whether you agree with it.