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README.md

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+---
+license: apache-2.0
+tags:
+  - onnx
+  - object-detection
+  - rf-detr
+  - pet-detection
+library_name: onnx
+pipeline_tag: object-detection
+---
+
+# RF-DETR Small (ONNX) — pet detection for Gallery
+
+ONNX export of [RF-DETR](https://github.com/roboflow/rf-detr) Small by Roboflow, used by
+[Gallery](https://github.com/open-noodle/gallery) for pet detection.
+
+Unmodified COCO-pretrained weights. No fine-tuning.
+
+## Files
+
+| Path                   | Description                      |
+| ---------------------- | -------------------------------- |
+| `detection/model.onnx` | RF-DETR Small, opset 17, batch 1 |
+
+## Inference contract
+
+Getting any of this wrong degrades output silently rather than erroring.
+
+**Input** — `input`, shape `[1, 3, 512, 512]`, float32:
+
+1. Decode to **RGB** (not BGR)
+2. Resize to 512×512 — plain square resize, **not** letterboxed
+3. Scale to `[0, 1]`
+4. Normalise with ImageNet statistics: mean `[0.485, 0.456, 0.406]`, std `[0.229, 0.224, 0.225]`
+5. Transpose HWC → CHW, add batch dimension
+
+**Output** — two tensors:
+
+| Name     | Shape          | Meaning                                        |
+| -------- | -------------- | ---------------------------------------------- |
+| `dets`   | `[1, 300, 4]`  | Boxes as cx, cy, w, h — normalised to `[0, 1]` |
+| `labels` | `[1, 300, 91]` | Class logits, **pre-sigmoid**                  |
+
+Apply sigmoid to `labels`, then threshold. Classes use the **91-class COCO id space**
+(90 categories plus background), not the contiguous 80-class space YOLO uses — so
+`bird=16, cat=17, dog=18, horse=19, sheep=20, cow=21`.
+
+The 300 queries are already deduplicated. **No NMS step is required.**
+
+## License
+
+Apache-2.0, inherited from RF-DETR. See the
+[upstream repository](https://github.com/roboflow/rf-detr) for full terms.

detection/model.onnx

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