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Add N100 to OpenVINO examples (#17845)

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Nicolas Mowen 2025-04-21 17:03:59 -06:00 committed by GitHub
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@ -118,6 +118,7 @@ Inference speeds vary greatly depending on the CPU or GPU used, some known examp
| Intel i3 12000 | | 320: ~ 19 ms 640: ~ 54 ms | | |
| Intel i5 12600K | ~ 15 ms | 320: ~ 20 ms 640: ~ 46 ms | | |
| Intel i7 12650H | ~ 15 ms | 320: ~ 20 ms 640: ~ 42 ms | 336: 50 ms | |
| Intel N100 | ~ 15 ms | 320: ~ 20 ms | | |
| Intel Arc A380 | ~ 6 ms | 320: ~ 10 ms 640: ~ 22 ms | 336: 20 ms 448: 27 ms | |
| Intel Arc A750 | ~ 4 ms | 320: ~ 8 ms | | |
@ -128,7 +129,7 @@ The TensortRT detector is able to run on x86 hosts that have an Nvidia GPU which
Inference speeds will vary greatly depending on the GPU and the model used.
`tiny` variants are faster than the equivalent non-tiny model, some known examples are below:
| Name | YoloV7 Inference Time | YOLO-NAS Inference Time | RF-DETR Inference Time |
| Name | YOLOv7 Inference Time | YOLO-NAS Inference Time | RF-DETR Inference Time |
| --------------- | --------------------- | ------------------------- | ------------------------- |
| GTX 1060 6GB | ~ 7 ms | | |
| GTX 1070 | ~ 6 ms | | |
@ -143,7 +144,7 @@ Inference speeds will vary greatly depending on the GPU and the model used.
With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detector Frigate can take advantage of many discrete AMD GPUs.
| Name | YoloV9 Inference Time | YOLO-NAS Inference Time |
| Name | YOLOv9 Inference Time | YOLO-NAS Inference Time |
| --------------- | --------------------- | ------------------------- |
| AMD 780M | ~ 14 ms | 320: ~ 30 ms 640: ~ 60 ms |