Add NOTICE.md (clean MIT chain)

NOTICE.md

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+# NOTICE — Attribution and Provenance
+
+This repository hosts an **INT8-quantized ONNX derivative** of
+**YOLOv4-tiny-416**, prepared by **Pablo Mendoza** (`@thefalley`) for
+deployment on a custom INT8 DPU (ZedBoard XC7Z020 FPGA).
+
+The work this repo adds (ONNX export pipeline + INT8 quantization with
+COCO calibration) is released under the MIT License (see `LICENSE`). All
+upstream components keep their original licenses, listed below in
+dependency order.
+
+---
+
+## Provenance chain
+
+```
+AlexeyAB / darknet                    (YOLO License v2 = public domain)
+  yolov4-tiny.weights  (23.13 MiB)
+  yolov4-tiny.cfg
+        │
+        │  parsed and loaded by:
+        ▼
+gwinndr / YOLOv4-Pytorch (MIT)         (used as conversion tool)
+  utilities/configs.py::parse_config       — parses darknet .cfg dynamically
+  utilities/weights.py::load_weights        — reads AlexeyAB binary .weights
+  + small in-repo patch to handle [route] groups
+  + DarknetRaw wrapper (this repo, MIT) that captures pre-YoloLayer outputs
+        │
+        │  torch.onnx.export(opset=13)
+        ▼
+yolov4-tiny-416_float.onnx            (this repo, MIT — derivative)
+  2 raw outputs:
+    out_stride16  — shape (1, 255, 26, 26)
+    out_stride32  — shape (1, 255, 13, 13)
+        │
+        │  onnxruntime.quantize_static (MIT, used as tool)
+        │  + COCO val2017 calibration (1000 images, CC BY 4.0)
+        ▼
+yolov4-tiny-416_int8_qop.onnx         (this repo, MIT — derivative)
+
+External Python decoder (this repo, MIT) reproduces the standard YOLOv4
+post-processing: sigmoid + scale_xy + grid offset + anchor multiplication
++ NMS. This decoder is not part of the ONNX graph (matches the standard
+deployable design where the decoder runs on the host CPU after the DPU
+executes the conv backbone+neck+head).
+```
+
+---
+
+## Component-level attribution
+
+### 1. Model weights — AlexeyAB / darknet
+
+- **Project**: `AlexeyAB/darknet`
+- **Source**: https://github.com/AlexeyAB/darknet
+- **Weights URL**: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-tiny.weights
+- **License**: YOLO License v2 — *"Darknet is public domain. Do whatever you want with it."*
+- **What we use**: the trained `yolov4-tiny.weights` file (23.13 MiB) and the corresponding `yolov4-tiny.cfg`. No modifications.
+
+### 2. Darknet → PyTorch conversion — gwinndr / YOLOv4-Pytorch
+
+- **Project**: `gwinndr/YOLOv4-Pytorch`
+- **Source**: https://github.com/gwinndr/YOLOv4-Pytorch
+- **License**: MIT (Copyright (c) 2020 Damon Gwinn)
+- **What we use**: the `parse_config` cfg parser and the `load_weights` AlexeyAB binary loader.
+- **Modifications we made** (to handle yolov4-tiny's CSPDarknet route trick):
+  - Patched `utilities/configs.py::parse_route_block` to read `groups` and `group_id` from `[route]` blocks.
+  - Patched `model/layers/route.py::RouteLayer` to apply channel-wise split when `groups > 1`.
+  - These patches are also released under MIT.
+- We do NOT redistribute gwinndr's source code in this HF repo. We reference it as a build-time tool. To reproduce, clone gwinndr's repo and apply the patches in our companion firmware repository.
+
+### 3. ONNX export
+
+- **Tool**: `torch.onnx.export` (PyTorch core, BSD-3-Clause). Used as a tool, not redistributed.
+- **Wrapper**: `DarknetRaw` (≈ 30 lines, this work, MIT) intercepts the pre-YoloLayer feature maps and exports them as 2 raw 4D tensors. The decoder lives in `inference.py` (Python, MIT).
+
+### 4. INT8 quantization
+
+- **Tool**: `onnxruntime.quantization.quantize_static` (Microsoft, MIT). Used as a tool, not redistributed.
+- **Configuration**:
+  - `quant_format = QuantFormat.QOperator`
+  - `weight_type = QuantType.QInt8` (per-tensor, symmetric)
+  - `activation_type = QuantType.QInt8` (per-tensor, asymmetric)
+  - `per_channel = False`
+  - `reduce_range = False`
+- **Calibration data**: 1000 randomly-sampled images from MS COCO val2017 (CC BY 4.0). No COCO image is embedded inside the ONNX file; the dataset's role ends after calibration.
+
+### 5. Calibration dataset — COCO val2017
+
+- **Source**: https://cocodataset.org
+- **License**: Creative Commons Attribution 4.0 (CC BY 4.0) for both images and annotations.
+
+---
+
+## File-level integrity (SHA-256)
+
+| File | Size | SHA-256 |
+|---|---:|---|
+| `yolov4-tiny.weights` (AlexeyAB upstream)        | 24,251,276 B | `cf9fbfd0f6d4869b35762f56100f50ed05268084078805f0e7989efe5bb8ca87` |
+| `yolov4-tiny-416_float.onnx`                     | 24,230,209 B | `eea691d460fd3eb5c1a250b4e5f822784cd44e11aaa77a24299b0952b9f4fc9f` |
+| `yolov4-tiny-416_int8_qop.onnx`                  |  6,113,440 B | `c30c8f0a33b3a0edc13a2ca21726a288228e1448b3c38940f9da0c7d8cee4760` |
+
+---
+
+## Author of the INT8 derivative
+
+**Pablo Mendoza** — HuggingFace [`@thefalley`](https://huggingface.co/thefalley)
+
+Companion repositories:
+
+| Repository | Purpose |
+|---|---|
+| [`Thefalley/yolov4-leaky-416-int8-qop`](https://huggingface.co/Thefalley/yolov4-leaky-416-int8-qop) | Larger sibling: full YOLOv4-Leaky-416 INT8 (61.66 MiB) for higher mAP |
+| `Thefalley/dpu-firmware` (GitHub, ***) | Bare-metal C firmware + RTL for the custom DPU on ZedBoard XC7Z020 |
+
+## Contact
+
+If you are a rights holder and believe this attribution is inaccurate or
+incomplete, please open an issue on this repository and it will be
+corrected promptly.