// import 'dart:math';

// import 'package:image/image.dart' as image_lib;
// import "package:logging/logging.dart";
// import 'package:photos/services/object_detection/models/predictions.dart';
// import 'package:photos/services/object_detection/models/recognition.dart';
// import "package:photos/services/object_detection/models/stats.dart";
// import "package:photos/services/object_detection/tflite/classifier.dart";
// import "package:tflite_flutter/tflite_flutter.dart";
// import "package:tflite_flutter_helper/tflite_flutter_helper.dart";

// /// Classifier
// class CocoSSDClassifier extends Classifier {
//   static final _logger = Logger("CocoSSDClassifier");
//   static const double threshold = 0.4;

//   @override
//   String get modelPath => "models/cocossd/model.tflite";

//   @override
//   String get labelPath => "assets/models/cocossd/labels.txt";

//   @override
//   int get inputSize => 300;

//   @override
//   Logger get logger => _logger;

//   static const int numResults = 10;

//   CocoSSDClassifier({
//     Interpreter? interpreter,
//     List<String>? labels,
//   }) {
//     loadModel(interpreter);
//     loadLabels(labels);
//   }

//   @override
//   Predictions? predict(image_lib.Image image) {
//     final predictStartTime = DateTime.now().millisecondsSinceEpoch;

//     final preProcessStart = DateTime.now().millisecondsSinceEpoch;

//     // Create TensorImage from image
//     TensorImage inputImage = TensorImage.fromImage(image);

//     // Pre-process TensorImage
//     inputImage = getProcessedImage(inputImage);

//     final preProcessElapsedTime =
//         DateTime.now().millisecondsSinceEpoch - preProcessStart;

//     // TensorBuffers for output tensors
//     final outputLocations = TensorBufferFloat(outputShapes[0]);
//     final outputClasses = TensorBufferFloat(outputShapes[1]);
//     final outputScores = TensorBufferFloat(outputShapes[2]);
//     final numLocations = TensorBufferFloat(outputShapes[3]);

//     // Inputs object for runForMultipleInputs
//     // Use [TensorImage.buffer] or [TensorBuffer.buffer] to pass by reference
//     final inputs = [inputImage.buffer];

//     // Outputs map
//     final outputs = {
//       0: outputLocations.buffer,
//       1: outputClasses.buffer,
//       2: outputScores.buffer,
//       3: numLocations.buffer,
//     };

//     final inferenceTimeStart = DateTime.now().millisecondsSinceEpoch;

//     // run inference
//     interpreter.runForMultipleInputs(inputs, outputs);

//     final inferenceTimeElapsed =
//         DateTime.now().millisecondsSinceEpoch - inferenceTimeStart;

//     // Maximum number of results to show
//     final resultsCount = min(numResults, numLocations.getIntValue(0));

//     // Using labelOffset = 1 as ??? at index 0
//     const labelOffset = 1;

//     final recognitions = <Recognition>[];

//     for (int i = 0; i < resultsCount; i++) {
//       // Prediction score
//       final score = outputScores.getDoubleValue(i);

//       // Label string
//       final labelIndex = outputClasses.getIntValue(i) + labelOffset;
//       final label = labels.elementAt(labelIndex);

//       if (score > threshold) {
//         recognitions.add(
//           Recognition(i, label, score),
//         );
//       }
//     }

//     final predictElapsedTime =
//         DateTime.now().millisecondsSinceEpoch - predictStartTime;
//     return Predictions(
//       recognitions,
//       Stats(
//         predictElapsedTime,
//         predictElapsedTime,
//         inferenceTimeElapsed,
//         preProcessElapsedTime,
//       ),
//     );
//   }
// }