Update model card for yolov5-det

README.md

@@ -218,6 +218,12 @@ Row conventions in the table below:
 | Medium | NXP Ara240 (FRDM) — throughput | 60.70% | -2.59 | 43.54% | 24.36 | 37.19 | 47.0 | ~47 | [v-a2d](https://edgefirst.studio/public/validation/v-a2d/details?mode=charts) |
 | Medium | Raspberry Pi 5 + Hailo-8L NPU | 62.40% | -0.89 | 46.17% | 57.38 | 72.71 | 16.2 | ~16 | [v-906](https://edgefirst.studio/public/validation/v-906/details?mode=charts) |
 | Medium | NVIDIA Jetson Orin Nano (TensorRT FP16) | 63.31% | +0.02 | 46.96% | 44.49 | 56.80 | 88.2 | ~88 | [v-92a](https://edgefirst.studio/public/validation/v-92a/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML Neural Engine (FP16) | 62.78% | -0.51 | 46.53% | 14.41 | 18.32 | 131.8 | ~69 | [v-f59](https://edgefirst.studio/public/validation/v-f59/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML Metal GPU (FP16) | 62.80% | -0.49 | 46.51% | 32.08 | 40.59 | 59.7 | ~31 | [v-f54](https://edgefirst.studio/public/validation/v-f54/details?mode=charts) |
+|  | Apple iPhone 17 Pro — CoreML CPU (FP16) | 62.75% | -0.54 | 46.45% | 92.85 | 99.63 | 21.3 | ~11 | [v-f3d](https://edgefirst.studio/public/validation/v-f3d/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML Neural Engine (FP16) | 62.78% | -0.51 | 46.54% | 18.03 | 23.79 | 104.7 | ~55 | [v-f1b](https://edgefirst.studio/public/validation/v-f1b/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML Metal GPU (FP16) | 62.80% | -0.49 | 46.51% | 114.12 | 129.31 | 17.0 | ~9 | [v-f28](https://edgefirst.studio/public/validation/v-f28/details?mode=charts) |
+|  | Apple iPhone 15 Pro — CoreML CPU (FP16) | 62.75% | -0.54 | 46.46% | 121.21 | 129.68 | 16.3 | ~8 | [v-f29](https://edgefirst.studio/public/validation/v-f29/details?mode=charts) |