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

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

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776fa2d
Update tiny dataset for IMAGENET
anhappdev Feb 24, 2025
0434bbf
Update expected_accuracy for image_classification
anhappdev Feb 25, 2025
763689c
Update expected_accuracy for image_classification
anhappdev Feb 26, 2025
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8 changes: 4 additions & 4 deletions flutter/assets/tasks.pbtxt
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Original file line number Diff line number Diff line change
Expand Up @@ -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 {
Expand Down
26 changes: 19 additions & 7 deletions flutter/integration_test/expected_accuracy.dart
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Expand Up @@ -18,15 +18,27 @@ 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),
'snpe_dsp': Interval(min: 0.83, max: 0.85),
'psnpe_dsp': Interval(min: 0.83, max: 0.85),
'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),
'snpe_dsp': Interval(min: 0.88, max: 0.91),
'psnpe_dsp': Interval(min: 0.88, max: 0.91),
'neuron-mdla': Interval(min: 0.79, max: 0.91),
'samsung_npu': Interval(min: 0.99, max: 1.0),
'snpe_dsp': Interval(min: 0.89, max: 0.91),
'psnpe_dsp': Interval(min: 0.89, max: 0.91),
'neuron-mdla': Interval(min: 0.79, max: 0.81),
'samsung_npu': Interval(min: 0.98, max: 1.0),
};

const Map<String, Interval> _objectDetection = {
Expand Down Expand Up @@ -102,5 +114,5 @@ const benchmarkExpectedAccuracy = {
BenchmarkId.naturalLanguageProcessing: _naturalLanguageProcessing,
BenchmarkId.superResolution: _superResolution,
BenchmarkId.stableDiffusion: _stableDiffusion,
BenchmarkId.imageClassificationOfflineV2: _imageClassificationV2,
BenchmarkId.imageClassificationOfflineV2: _imageClassificationOfflineV2,
};
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