| User | petergrip |
| Upload Date | August 16 2024 07:06 AM |
| Views | 7 |
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 2200 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.10 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1536
285.7 IPS |
|
|
Image Classification (HP)
|
100% |
1336
248.4 IPS |
|
|
Image Classification (Q)
|
100% |
2235
415.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1440
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1471
23.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2432
39.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2542
2.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
2459
2.87 IPS |
|
|
Pose Estimation (Q)
|
84% |
5360
6.36 IPS |
|
|
Object Detection (SP)
|
98% |
1217
96.8 IPS |
|
|
Object Detection (HP)
|
98% |
1223
97.3 IPS |
|
|
Object Detection (Q)
|
87% |
1705
136.9 IPS |
|
|
Face Detection (SP)
|
100% |
1983
23.6 IPS |
|
|
Face Detection (HP)
|
100% |
2005
23.8 IPS |
|
|
Face Detection (Q)
|
95% |
3626
43.3 IPS |
|
|
Depth Estimation (SP)
|
98% |
2252
17.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2405
18.6 IPS |
|
|
Depth Estimation (Q)
|
75% |
3976
32.2 IPS |
|
|
Style Transfer (SP)
|
89% |
4974
6.46 IPS |
|
|
Style Transfer (HP)
|
89% |
4829
6.27 IPS |
|
|
Style Transfer (Q)
|
98% |
7955
10.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1032
38.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1023
37.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1932
71.6 IPS |
|
|
Text Classification (SP)
|
100% |
406
541.7 IPS |
|
|
Text Classification (HP)
|
99% |
391
521.4 IPS |
|
|
Text Classification (Q)
|
88% |
717
966.7 IPS |
|
|
Machine Translation (SP)
|
100% |
865
14.9 IPS |
|
|
Machine Translation (HP)
|
100% |
841
14.5 IPS |
|
|
Machine Translation (Q)
|
50% |
411
14.6 IPS |