YuNet face detection LiteRT fp16 (fully-GPU, Pixel 8a corr 0.9999, 4ms, 0.3MB)

.gitattributes

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README.md

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+---
+license: bsd-3-clause
+library_name: LiteRT
+pipeline_tag: object-detection
+tags: [litert, tflite, on-device, android, gpu, face-detection, yunet, libfacedetection, landmarks]
+base_model: ShiqiYu/libfacedetection
+---
+
+# YuNet — LiteRT (on-device face detection, fully-GPU)
+
+[YuNet](https://github.com/ShiqiYu/libfacedetection) (ShiqiYu/libfacedetection), a tiny fast face detector
+(faces + 5 landmarks), converted to **LiteRT** and running **fully on the `CompiledModel` GPU** (ML Drift) on
+Android. **0.076 M params / 0.3 MB fp16.**
+
+![YuNet — face boxes + 5 landmarks on-device LiteRT GPU](samples/sample.png)
+
+## On-device (Pixel 8a, Tensor G3 — verified)
+
+| | |
+|---|---|
+| nodes on GPU | **146 / 146** LITERT_CL (full residency) |
+| inference | **~4 ms** (640×640) |
+| size | **0.3 MB** (fp16) |
+| accuracy | device-vs-PyTorch corr **0.9999** (all 12 outputs) |
+
+```
+image[1,3,640,640] (BGR, 0-255) →[GPU: YuNet]→ 12 outputs: cls/obj/bbox/kps × strides {8,16,32}
+```
+
+## How it converts (litert-torch) — clean, no re-authoring
+
+Pure CNN (depthwise-separable `ConvDPUnit`) + a **nearest-upsample** neck (`F.interpolate(mode="nearest")` →
+`RESIZE_NEAREST_NEIGHBOR`, no transposed conv) + non-padded `MaxPool2d` (no `PADV2`). The head's per-stride
+`permute/reshape/sigmoid` is baked in → 12 decode-ready outputs. Banned ops NONE, ≤4D, tflite-vs-torch corr
+**1.0**, device-vs-torch corr **0.9999**.
+
+## Decode (host-side) & preprocessing
+
+**Preprocessing**: letterbox to 640×640, **BGR, 0-255, no normalization**. Anchor-free priors
+(`px=col·s, py=row·s`, offset 0): score=`cls·obj`, box=center+`exp(wh)·s`, 5 landmarks `kps·s+prior`, then NMS.
+
+## License
+
+[BSD-3-Clause](https://github.com/ShiqiYu/libfacedetection/blob/master/LICENSE). Upstream:
+[ShiqiYu/libfacedetection](https://github.com/ShiqiYu/libfacedetection).

yunet_fp16.tflite

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