chore: use larger dataset for integration test of image_classification_v2 (#968)

* Update tiny dataset for IMAGENET

* Update expected_accuracy for image_classification

* Update expected_accuracy for image_classification

* Update expected_accuracy

* Update expected_accuracy

Author: anhappdev

Diff for: flutter/assets/tasks.pbtxt

@@ -42,10 +42,10 @@ task {
     }
     tiny {
       name: "Imagenet dataset for integration test"
-      input_path: "https://mobile.mlcommons-storage.org/app-resources/datasets/v0_7/imagenet_tiny.zip"
-      input_checksum: "42cb83d80d0341d6719d68b32322adf2"
-      groundtruth_path: "https://mobile.mlcommons-storage.org/app-resources/datasets/v3_0/imagenet_tiny-groundtruth.txt"
-      groundtruth_checksum: "cc6d83ca25daeb2475f36c079e53bc26"
+      input_path: "https://mobile.mlcommons-storage.org/app-resources/datasets/v5_0/imagenet_tiny.zip"
+      input_checksum: "2cde6f1d741b9c1834db261ac6e43a6e"
+      groundtruth_path: "https://mobile.mlcommons-storage.org/app-resources/datasets/v5_0/imagenet_tiny_val.txt"
+      groundtruth_checksum: "086f99eff3d1b93fd41e7f35498570a7"
     }
   }
   model {

Diff for: flutter/integration_test/expected_accuracy.dart

@@ -18,16 +18,29 @@ key: <accelerator> OR <accelerator>|<backendName>
 */
 
 const Map<String, Interval> _imageClassificationV2 = {
+  'cpu': Interval(min: 0.82, max: 0.84),
+  'npu': Interval(min: 0.80, max: 0.82),
+  'tpu': Interval(min: 0.82, max: 0.84),
+  'ane': Interval(min: 0.69, max: 0.91),
+  'cpu&gpu&ane': Interval(min: 0.69, max: 0.91),
+  // TODO (anhappdev): check expected accuracy for snpe_dsp, psnpe_dsp
+  'snpe_dsp': Interval(min: 0.0, max: 1.0),
+  'psnpe_dsp': Interval(min: 0.0, max: 1.0),
+  'neuron-mdla': Interval(min: 0.81, max: 0.83),
+  'samsung_npu': Interval(min: 0.83, max: 0.85),
+};
+
+const Map<String, Interval> _imageClassificationOfflineV2 = {
   'cpu': Interval(min: 0.88, max: 0.91),
-  'npu': Interval(min: 0.69, max: 0.91),
-  'tpu': Interval(min: 0.88, max: 0.91),
+  'npu': Interval(min: 0.69, max: 0.71),
+  'tpu': Interval(min: 0.89, max: 0.91),
   'ane': Interval(min: 0.69, max: 0.91),
   'cpu&gpu&ane': Interval(min: 0.69, max: 0.91),
   // TODO (anhappdev): check expected accuracy for snpe_dsp, psnpe_dsp
   'snpe_dsp': Interval(min: 0.0, max: 1.0),
   'psnpe_dsp': Interval(min: 0.0, max: 1.0),
-  'neuron-mdla': Interval(min: 0.79, max: 0.91),
-  'samsung_npu': Interval(min: 0.99, max: 1.0),
+  'neuron-mdla': Interval(min: 0.79, max: 0.81),
+  'samsung_npu': Interval(min: 0.98, max: 1.0),
 };
 
 const Map<String, Interval> _objectDetection = {
@@ -105,5 +118,5 @@ const benchmarkExpectedAccuracy = {
   BenchmarkId.naturalLanguageProcessing: _naturalLanguageProcessing,
   BenchmarkId.superResolution: _superResolution,
   BenchmarkId.stableDiffusion: _stableDiffusion,
-  BenchmarkId.imageClassificationOfflineV2: _imageClassificationV2,
+  BenchmarkId.imageClassificationOfflineV2: _imageClassificationOfflineV2,
 };