The code works great when the phone is portrait , But when the phone is placed landscape, it does not work

[maheralzoubi97]

import 'package:camera/camera.dart'; import 'package:flutter/material.dart'; import 'package:flutter/services.dart'; import 'package:pytorch_lite/pigeon.dart'; import 'package:pytorch_lite/pytorch_lite.dart';

import 'camera_view_singleton.dart';

/// [CameraView] sends each frame for inference class CameraView extends StatefulWidget { /// Callback to pass results after inference to [HomeView] final Function(List<ResultObjectDetection?> recognitions) resultsCallback; final Function(String classification) resultsCallbackClassification;

/// Constructor const CameraView(this.resultsCallback, this.resultsCallbackClassification, {Key? key}) : super(key: key); @override _CameraViewState createState() => _CameraViewState(); }

class _CameraViewState extends State with WidgetsBindingObserver { /// List of available cameras late List cameras;

/// Controller CameraController? cameraController;

/// true when inference is ongoing bool predicting = false;

ModelObjectDetection? _objectModel; ClassificationModel? _imageModel;

bool classification = false; @override void initState() { super.initState(); initStateAsync(); }

//load your model Future loadModel() async { String pathObjectDetectionModel = "assets/models/best2.torchscript"; try { _objectModel = await PytorchLite.loadObjectDetectionModel( pathObjectDetectionModel, 24, 640, 640, labelPath: "assets/labels/labels_objectDetection_Coco.txt", objectDetectionModelType: ObjectDetectionModelType.yolov8, ); } catch (e) { if (e is PlatformException) { print("only supported for android, Error is $e"); } else { print("Error is $e"); } } }

void initStateAsync() async { WidgetsBinding.instance.addObserver(this); await loadModel();

// Camera initialization
initializeCamera();

// Initially predicting = false
// predicting = false;

}

/// Initializes the camera by setting [cameraController] void initializeCamera() async { cameras = await availableCameras();

// cameras[0] for rear-camera
cameraController = CameraController(cameras[0], ResolutionPreset.veryHigh,
    enableAudio: false);

cameraController?.initialize().then((_) async {
  // Stream of image passed to [onLatestImageAvailable] callback
  await cameraController?.startImageStream(onLatestImageAvailable);

  /// previewSize is size of each image frame captured by controller
  ///
  /// 352x288 on iOS, 240p (320x240) on Android with ResolutionPreset.low
  Size? previewSize = cameraController?.value.previewSize;

  /// previewSize is size of raw input image to the model
  CameraViewSingleton.inputImageSize = previewSize!;

  // the display width of image on screen is
  // same as screenWidth while maintaining the aspectRatio
  Size screenSize = MediaQuery.of(context).size;
  CameraViewSingleton.screenSize = screenSize;
  CameraViewSingleton.ratio = screenSize.width / previewSize.height;
});

}

@override Widget build(BuildContext context) { // Return empty container while the camera is not initialized if (cameraController == null || !cameraController!.value.isInitialized) { return Container(); }

// return CameraPreview(cameraController!);
return cameraController!.buildPreview();

// return AspectRatio(
//     // aspectRatio: cameraController.value.aspectRatio,
//     child: CameraPreview(cameraController));

}

runObjectDetection(CameraImage cameraImage) async { if (_objectModel != null) { List<ResultObjectDetection?> objDetect = await _objectModel! .getImagePredictionFromBytesList( cameraImage.planes.map((e) => e.bytes).toList(), cameraImage.width, cameraImage.height, minimumScore: 0.3, iOUThreshold: 0.3);

  print("data outputted $objDetect");
  widget.resultsCallback(objDetect);
}

}

/// Callback to receive each frame [CameraImage] perform inference on it onLatestImageAvailable(CameraImage cameraImage) async { if (predicting) { return; } predicting = true;

var futures = <Future>[];

futures.add(runObjectDetection(cameraImage));
await Future.wait(futures);

predicting = false;

}

@override void didChangeAppLifecycleState(AppLifecycleState state) async { switch (state) { case AppLifecycleState.paused: cameraController?.stopImageStream(); break; case AppLifecycleState.resumed: if (!cameraController!.value.isStreamingImages) { await cameraController?.startImageStream(onLatestImageAvailable); } break; default: } }

@override void dispose() { WidgetsBinding.instance.removeObserver(this); cameraController?.dispose(); super.dispose(); } }

Could you please help me?

[abdelaziz-mahdy]

In landscape on Android or iOS? And what happens exactly

Does it show wrong results, or wrong boxes placements, shows nothing?

Please provide all the information about what happens so I can help you better

[maheralzoubi97]

in landscape on Android

show wrong results and show wrong boxes placement

in case real time object detection @zezo357

[abdelaziz-mahdy]

can you provide an example ? it will help me greatly, both the right and wrong ones

most probably i will work on it after i finish the opencv stuff, since i am thinking of moving the camera decoding logic to opencv, to be much faster

[maheralzoubi97]

show this image

[abdelaziz-mahdy]

Thank you

[abdelaziz-mahdy]

fixed by https://github.com/abdelaziz-mahdy/pytorch_lite/pull/81 and released