Apply EdgeFirst/NXP branding rules (strict NXP i.MX prefixing, Ara240, trademark notice)

README.md

@@ -5,7 +5,7 @@ colorFrom: indigo
 colorTo: red
 sdk: static
 pinned: true
-license: apache-2.0
+license: cc-by-nc-4.0
 short_description: Multi-platform model zoo validated on real edge hardware
 thumbnail: https://huggingface.co/spaces/EdgeFirst/Models/resolve/main/social-card.png
 ---
@@ -86,14 +86,14 @@ EdgeFirst/yolov8-det/
 | ONNX FP32 (reference) | `yolov8n-det-fp32.onnx` |
 | Generic INT8 TFLite | `yolov8n-det-int8.tflite` |
 | Smart variant TFLite | `yolov8n-det-int8-smart.tflite` |
-| i.MX 95 TFLite | `yolov8n-det-int8.imx95.tflite` |
-| Smart i.MX 95 | `yolov8n-seg-int8-smart.imx95.tflite` |
+| NXP i.MX 95 TFLite | `yolov8n-det-int8.imx95.tflite` |
+| Smart NXP i.MX 95 | `yolov8n-seg-int8-smart.imx95.tflite` |
 | Hailo-8L HEF | `yolov8n-det-int8.hailo8l.hef` |
 | Jetson TensorRT FP16 | `yolov8n-det-fp16.orin-nano.engine` |
 
 ## Supported Hardware
 
-![x86_64 | Linux](https://img.shields.io/badge/x86__64-Linux-6C757D?style=flat-square) ![aarch64 | Linux](https://img.shields.io/badge/aarch64-Linux-718096?style=flat-square) ![Apple | macOS](https://img.shields.io/badge/Apple-macOS-4B0082?style=flat-square) ![NXP i.MX 8M Plus](https://img.shields.io/badge/NXP-i.MX_8M_Plus-E8B820?style=flat-square) ![NXP i.MX 93](https://img.shields.io/badge/NXP-i.MX_93-8B7DC4?style=flat-square) ![NXP i.MX 95](https://img.shields.io/badge/NXP-i.MX_95-1FA0A8?style=flat-square) ![NXP ARA240](https://img.shields.io/badge/NXP-ARA240-5BB8F5?style=flat-square) ![RPi5 + Hailo-8/8L](https://img.shields.io/badge/RPi5-Hailo--8%2F8L-D9534F?style=flat-square) ![NVIDIA Jetson](https://img.shields.io/badge/NVIDIA-Jetson-2E8B57?style=flat-square)
+![x86_64 | Linux](https://img.shields.io/badge/x86__64-Linux-6C757D?style=flat-square) ![aarch64 | Linux](https://img.shields.io/badge/aarch64-Linux-718096?style=flat-square) ![Apple | macOS](https://img.shields.io/badge/Apple-macOS-4B0082?style=flat-square) ![NXP i.MX 8M Plus](https://img.shields.io/badge/NXP-i.MX_8M_Plus-E8B820?style=flat-square) ![NXP i.MX 93](https://img.shields.io/badge/NXP-i.MX_93-8B7DC4?style=flat-square) ![NXP i.MX 95](https://img.shields.io/badge/NXP-i.MX_95-1FA0A8?style=flat-square) ![NXP Ara240](https://img.shields.io/badge/NXP-Ara240-5BB8F5?style=flat-square) ![RPi5 + Hailo-8/8L](https://img.shields.io/badge/RPi5-Hailo--8%2F8L-D9534F?style=flat-square) ![NVIDIA Jetson](https://img.shields.io/badge/NVIDIA-Jetson-2E8B57?style=flat-square)
 
 - **Linux x86_64** — ONNX Runtime CUDA / CPU (FP32 reference)
 - **Linux aarch64** — ONNX Runtime / TFLite (ARM64 generic Linux)
@@ -101,7 +101,7 @@ EdgeFirst/yolov8-det/
 - **NXP i.MX 8M Plus** — 2.3 TOPS, TFLite INT8
 - **NXP i.MX 93** — 1.0 TOPS, VELA TFLite
 - **NXP i.MX 95** — 2.0 TOPS, eIQ Neutron TFLite *(YOLOv5 / YOLOv8 only; YOLO11 / YOLO26 not yet supported)*
-- **NXP ARA240** — 40 eTOPS, Kinara DVM *(YOLOv5 / YOLOv8 only; YOLO11 / YOLO26 not yet supported)*
+- **NXP Ara240** — 40 eTOPS, .DVM *(YOLOv5 / YOLOv8 only; YOLO11 / YOLO26 not yet supported)*
 - **RPi5 + Hailo-8/8L** — 13–26 TOPS, HailoRT HEF
 - **NVIDIA Jetson Orin** — 67–157 TOPS, TensorRT
 
@@ -111,11 +111,11 @@ Every artifact in the Model Zoo is measured on the same dataset on the same hard
 
 ### End-to-end flow
 
-Each training session produces a single set of weights in [EdgeFirst Studio](https://edgefirst.studio). The export pipeline emits ONNX FP32, INT8 TFLite, and platform-specific compiled formats (i.MX 95 Neutron, NXP Ara-240 DVM, Hailo HEF, Jetson TensorRT). Every output is paired with an on-target validation that captures both accuracy (COCO mAP) and full-pipeline timing. The ONNX FP32 run from each training session is the reference baseline; quantization and runtime loss are measured relative to it.
+Each training session produces a single set of weights in [EdgeFirst Studio](https://edgefirst.studio). The export pipeline emits ONNX FP32, INT8 TFLite, and platform-specific compiled formats (NXP i.MX 95 Neutron, NXP Ara240 .DVM, Hailo HEF, Jetson TensorRT). Every output is paired with an on-target validation that captures both accuracy (COCO mAP) and full-pipeline timing. The ONNX FP32 run from each training session is the reference baseline; quantization and runtime loss are measured relative to it.
 
 ### EdgeFirst Profiler
 
-The on-target validation agent. Given a model and dataset, it runs full inference on the target device, captures per-image predictions in EdgeFirst Arrow/Parquet, and emits a Perfetto trace alongside. Loads each runtime through its native delegate — VX Delegate on i.MX 8M Plus, eIQ Neutron on i.MX 95, Kinara SDK on Ara-240, HailoRT on RPi5 + Hailo, TensorRT on Jetson — so timing reflects deployed-application reality.
+The on-target validation agent. Given a model and dataset, it runs full inference on the target device, captures per-image predictions in EdgeFirst Arrow/Parquet, and emits a Perfetto trace alongside. Loads each runtime through its native delegate — VX Delegate on NXP i.MX 8M Plus, eIQ Neutron on NXP i.MX 95, NXP Ara SDK on Ara240, HailoRT on RPi5 + Hailo, TensorRT on Jetson — so timing reflects deployed-application reality.
 
 ### EdgeFirst Validator
 
@@ -132,8 +132,10 @@ Two timing surfaces per validation:
 - **`timing.inline`** — per-image `preprocess_ms` / `inference_ms` / `postprocess_ms` with min / mean / median / p95 / p99 / max. The universal contract every producer fills.
 - **`timing.trace`** — full per-stage breakdown from the Perfetto trace (typically 25–33 stages), plus end-to-end FPS distribution.
 
-Throughput exceeds the sum of stage latencies because the runtime pipelines I/O, preprocessing, NPU inference, and decode across frames. The Model Zoo headlines `trace.fps.median` as the throughput number, not the derived `1000 / (preprocess + inference + postprocess)`. Example: YOLOv5n on i.MX 95 Neutron has per-stage means 21.7 + 12.2 + 15.8 ms (naive ≈ 20 FPS) but pipelined throughput of 56 FPS median.
+Throughput exceeds the sum of stage latencies because the runtime pipelines I/O, preprocessing, NPU inference, and decode across frames. The Model Zoo headlines `trace.fps.median` as the throughput number, not the derived `1000 / (preprocess + inference + postprocess)`. Example: YOLOv5n on NXP i.MX 95 Neutron has per-stage means 21.7 + 12.2 + 15.8 ms (naive ≈ 20 FPS) but pipelined throughput of 56 FPS median.
 
 ---
 
-Apache 2.0 · [Au-Zone Technologies Inc.](https://www.au-zone.com)
+Validation results & card data: [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) · YOLO model weights: © Ultralytics Inc. (AGPL-3.0) · © 2026 [Au-Zone Technologies](https://www.au-zone.com)
+
+<sub>NXP<sup>®</sup>, i.MX, eIQ<sup>®</sup>, Neutron, and Ara240 are trademarks or products of NXP Semiconductors. Hailo is a trademark of Hailo Technologies Ltd. Jetson is a trademark of NVIDIA Corporation. All other trademarks are the property of their respective owners.</sub>