_classifyDog

_classifyDog.dart

  Future<String> _classifyDog(imglib.Image croppedImage) async {
    while (_tfliteBusy) await Future.delayed(Duration(milliseconds: 100));
    _tfliteBusy = true;

    Uint8List croppedPng = imglib.encodePng(croppedImage);
    try {
      File(_tempPath).deleteSync();
    } catch (e) {
      print(e);
    }
    File(_tempPath).writeAsBytesSync(croppedPng);

    await Tflite.loadModel(
      model: 'assets/dogs.tflite',
      labels: 'assets/dog_labels.txt',
    );
    var resultList = await Tflite.runModelOnImage(
      path: _tempPath,
      numResults: 2,
      threshold: 0.05,
      imageMean: 127.5,
      imageStd: 127.5,
    );
    if (resultList.length == 0) return 'Cannot determine breed';

    String breed = resultList[0]["label"].replaceAll('\t', ' ').substring(10);
    breed = breed[0].toUpperCase() + breed.substring(1);
    String conf = (resultList[0]["confidence"] * 100).toStringAsFixed(0);
    String reply = breed + ' (' + conf + '%)';

    if (resultList.length > 1) {
      breed = resultList[1]["label"].replaceAll('\t', ' ').substring(10);
      breed = breed[0].toUpperCase() + breed.substring(1);
      conf = (resultList[1]["confidence"] * 100).toStringAsFixed(0);
      reply = reply + '\n' + breed + ' (' + conf + '%)';
    }

    await Tflite.loadModel(
        model: "assets/ssd_mobilenet.tflite",
        labels: "assets/ssd_mobilenet.txt");
    _tfliteBusy = false;

    return reply;