Duplicate from mlboydaisuke/YOLOX-CoreAI

Co-authored-by: Daisuke Majima (MLBoy) <mlboydaisuke@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+yolox-s_float32.aimodel/main.mlirb filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,132 @@
+---
+license: apache-2.0
+pipeline_tag: object-detection
+library_name: coreai
+tags:
+  - core-ai
+  - coreml
+  - object-detection
+  - yolox
+  - apple
+base_model: Megvii-BaseDetection/YOLOX
+base_model_relation: quantized
+---
+
+# YOLOX-S — Core AI
+
+[YOLOX](https://github.com/Megvii-BaseDetection/YOLOX) (Megvii, Apache-2.0) converted to
+Apple **Core AI** (`.aimodel`) — a single-stage **anchor-free** object detector running as
+one static graph on every Apple compute unit (Mac GPU / iPhone GPU / Neural Engine). Part
+of the [Core AI model zoo](https://github.com/john-rocky/coreai-model-zoo)
+([model card](https://github.com/john-rocky/coreai-model-zoo/blob/main/zoo/yolox.md)).
+
+The **dense-detector** counterpart to
+[RF-DETR-CoreAI](https://huggingface.co/mlboydaisuke/RF-DETR-CoreAI): where the DETR family
+needs no NMS, YOLOX is the classic `score = obj · cls` + **per-class NMS** pipeline.
+
+<!-- gen-cards:use-it begin id=yolox-s (managed by scripts/gen-cards — edit cards.json / QuickStart.swift, not this block) -->
+## Use it
+
+⚡ **One line** — run the kit's task op on this model
+(`import CoreAIOps`; no session, no model plumbing, downloads on first use):
+
+```swift
+let boxes = try await CoreAI.detect(inImageAt: url, options: .model("yolox-s"))
+```
+
+Every op, one shape — [Cookbook](https://github.com/john-rocky/coreai-kit/blob/main/docs/COOKBOOK.md).
+
+▶️ **Run it (source)** — the [DetectCamera runner](https://github.com/john-rocky/coreai-kit/tree/main/Examples/DetectCamera)
+(real-time object detection on the zero-copy camera path):
+
+```bash
+git clone https://github.com/john-rocky/coreai-kit
+open coreai-kit/Examples/DetectCamera/DetectCamera.xcodeproj
+# → Run, then pick "YOLOX" in the model picker
+
+# agents / headless (macOS):
+cd coreai-kit/Examples/DetectCamera
+swift run detect-cli --model yolox-s --image Resources/gate_image.jpg
+```
+
+💻 **Build with it** — complete; the glue is kit API, copy-paste runs:
+
+```swift
+import CoreAIKitVision
+
+let detector = try await KitDetector(catalog: "yolox-s")
+let image = try ImageFile.load(imageURL)  // any image file → CGImage + EXIF orientation
+let detections = try await detector.detect(in: image.cgImage)
+// detections: [Detection] — label, score, normalized box (top-left origin)
+```
+
+The take-home is [`Examples/DetectCamera/Sources/QuickStart.swift`](https://github.com/john-rocky/coreai-kit/blob/main/Examples/DetectCamera/Sources/QuickStart.swift)
+— this exact code as one typed function, no UI; the CLI is an argument shell over it, and
+the GUI runs the same detector per camera frame on a zero-copy pixel-buffer fast path.
+YOLOX is a dense detector — `KitDetector` runs the obj·cls threshold + per-class NMS
+host-side; the DETR family needs none. Same `detect(in:)` either way.
+
+**Integration checklist**
+
+- SPM: `https://github.com/john-rocky/coreai-kit` → product **CoreAIKitVision**
+- Info.plist: `NSCameraUsageDescription` — only for the live camera; the snippet needs none
+- Entitlements: none needed
+- First run downloads the model — 0.0 GB (Mac) / 0.0 GB (iPhone) — then it loads from the
+  local cache (Application Support; progress via the `downloadProgress` callback)
+- Measure in Release — Debug is ~3× slower on per-token host work
+<!-- gen-cards:use-it end -->
+
+## Bundle
+
+- `yolox-s_float32.aimodel` — YOLOX-S, 640² input, 8.97M params, **fp32** (the ship dtype;
+  detection has no bandwidth-bound decode loop, so fp16 is no faster on the GPU and only adds
+  near-tie noise). 36 MB. Same bundle on macOS and iOS.
+
+## Graph contract
+
+```
+input  "image"  [1,3,640,640] f32   BGR, 0-255, letterboxed (pad 114, top-left) — YOLOX-native (no /255, no mean/std)
+output "preds"  [1,8400,85]   f32   [cx,cy,w,h, obj, cls_0..cls_79]; box DECODED to 640-px, obj/cls SIGMOID-ed (in-graph)
+```
+
+Host post-process: `score = obj · max_class`, threshold, **per-class NMS** (IoU 0.45), then
+un-letterbox the survivors. Anchors A = 80² + 40² + 20² = 8400 (strides 8/16/32).
+
+## Parity & speed (measured)
+
+- **vs torch fp32:** head cosine **1.000000**, end-to-end detections IoU **1.000** on CPU and GPU.
+- **M4 Max GPU: 4.80 ms / 208 FPS** (median). M4 Max CPU 57 ms.
+- **iPhone 17 Pro** (Release, GPU, live camera): **~22 ms / 35–40 FPS** end-to-end; first-load
+  on-device specialization ~2.6 s (no AOT). The on-device gate reproduces the Mac fp32 oracle
+  **6/6** (cat 0.96/0.96, remote 0.86/0.86, bed 0.71, couch 0.54).
+
+## Use (CoreAIKit)
+
+```swift
+import CoreAIKitVision
+let detector = try await YOLOXDetector(model: .yoloxS)            // downloads this repo
+let detections = try await detector.detect(in: pixelBuffer, scoreThreshold: 0.3)
+```
+
+Live-camera + video reference app: **DetectCamera** in
+[coreai-kit](https://github.com/john-rocky/coreai-kit).
+
+## Convert it yourself
+
+[`conversion/export_yolox.py`](https://github.com/john-rocky/coreai-model-zoo/blob/main/conversion/export_yolox.py)
+— `--variant s --yolox-repo <YOLOX checkout> --weights yolox_s.pth`, gated end-to-end with
+`--verify-image <img> --unit {cpu,gpu}`. The script also maps `nano`/`tiny`/`m`/`l`/`x`.
+
+## License
+
+Apache-2.0 — upstream YOLOX code and COCO-pretrained weights are Apache-2.0.
+
+<!-- funnel:v1 -->
+
+---
+
+**More models in this format:** [Core AI Model Zoo](https://huggingface.co/collections/mlboydaisuke/core-ai-model-zoo-6a7ff330f753e8dcae04671a) — 75 models, each with the recipe that produced it.
+
+**Want a different model on-device?** [Open a request](https://github.com/john-rocky/on-device-requests) — free, open weights only; the export and its measured numbers get published publicly.
+
+<!-- /funnel:v1 -->

config.json

@@ -0,0 +1,7 @@
+{
+  "model_type": "coreai-aimodel",
+  "format": "aimodel",
+  "framework": "Apple Core AI (iOS 27 / macOS 27)",
+  "repository": "https://github.com/john-rocky/coreai-model-zoo",
+  "note": "Converted .aimodel bundles for Apple's Core AI framework. See README.md for the bundle layout and run instructions."
+}

yolox-s_float32.aimodel/main.mlirb

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1533e74f3365b72c087c43ee7dec9f8f8fdacbe42ddb2b5027d60c0083cc6169
+size 36028733

yolox-s_float32.aimodel/metadata.json

@@ -0,0 +1,8 @@
+{
+  "assetVersion" : "2.0",
+  "license" : "Apache-2.0",
+  "description" : "YOLOX-s anchor-free single-stage detector (CSPDarknet + PAFPN + decoupled head). Input: BGR 0-255 letterboxed [1,3,S,S]; output preds [1,A,85] = decoded cxcywh pixels + obj + 80 sigmoid class scores. Host does score=obj*cls threshold + per-class NMS. https:\/\/github.com\/Megvii-BaseDetection\/YOLOX",
+  "producer" : "coreai-core 1.0.0b2",
+  "creationDate" : "20260720T124242Z",
+  "author" : "Megvii (YOLOX); Core AI export: coreai-model-zoo"
+}