ultralytics_yolo 0.1.2

ultralytics_yolo: ^0.1.2 copied to clipboard

• Android: Fixed pose estimation keypoints not displaying correctly by properly implementing object pooling in PoseEstimator.kt.
• Android: Improved segmentation to work with all model classes, not just early ones like "person" and "car".
• Android: Enhanced model metadata loading to extract labels from model files with fallback to COCO dataset classes.
• Android: Fixed lifecycle management in YoloView.kt with proper onLifecycleOwnerAvailable implementation.
• Android: Made Box class fields mutable (var instead of val) to properly support object pooling.
• Performance: Various optimizations for faster inference and more reliable detection.

• iOS: Implemented direct FPS (Frames Per Second) reporting to Flutter, similar to Android. Native-calculated FPS is now included in the data sent to Dart during real-time inference.
• Android: Fixed an issue where the camera preview would remain black by improving native lifecycle management and camera initialization timing. (Previously part of 0.0.9 prep)
• Android: Added detailed debug logs to YoloPlatformView initialization. (Previously part of 0.0.9 prep)
• lib/yolo_view.dart: Added debug logs for communication channel creation and improved null checks. (Previously part of 0.0.9 prep)
• .pubignore: Updated to optimize the content of the published package. (Previously part of 0.0.9 prep)
• General: Incorporated various improvements from previous development versions (including enhanced model path resolution and logging). (Previously part of 0.0.9 prep)

• Android: Fixed an issue where the camera preview would remain black by improving native lifecycle management and camera initialization timing.
• Android: Added detailed debug logs to YoloPlatformView initialization for easier troubleshooting.
• lib/yolo_view.dart: Added debug logs for communication channel creation and improved null checks.
• .pubignore: Updated to optimize the content of the published package.
• General: Incorporated various improvements from previous development versions (including enhanced model path resolution and logging).

• Fix Android implementation for inference results not displaying or updating
• Fix "Unresolved reference: setIoUThreshold" error by fixing method name casing
• Add support for both "setIoUThreshold" and "setIouThreshold" method names for robustness
• Enhance error handling and logging for event channel communication
• Improve StreamHandler implementation for more reliable event dispatching
• Add fallback mechanisms for when direct method calls fail
• Fix reflection-based sink access for CustomStreamHandler
• Add test message mechanism to verify event channel connection
• Significantly increase logging for easier troubleshooting
• Update documentation with clear guidance on model placement and path resolution
• Recommend using model name only (without extension) for best cross-platform compatibility

• Fix iOS implementation for loading .mlmodel files from Flutter assets
• Significantly improve model path resolution for different path formats
• Add extensive logging to help debug model loading issues
• Fix Flutter asset bundle path issues with nested directories

0.0.7 #

• Fix iOS implementation to properly load models from Flutter assets
• Improve asset path resolution for paths like 'assets/models/yolo11n.mlmodel'
• Fix syntax errors in YoloPlugin.swift

• Add iOS implementation for checkModelExists method
• Add iOS implementation for getStoragePaths method
• Fix cross-platform consistency for model path resolution

• Update README to match current implementation of YOLO class constructor
• Fix documentation for threshold management in the API reference
• Add optional controller-based approach for managing YoloView settings
• Make onResult callback truly optional
• Improve threshold controls with IoU threshold support
• Update code documentation with detailed examples
• Add support for direct YoloView state access via GlobalKey
• Enhance error handling and debug logging
• Translate Japanese comments to English

• Initial release
• Object detection with YOLOv8 models
• Segmentation support
• Image classification support
• Pose estimation support
• Oriented Bounding Box (OBB) detection support
• Android/iOS platform support
• Real-time detection with camera feed
• Customizable confidence threshold
• YoloView Flutter widget implementation