docs: Unsloth-style KerasFormers model card for dfine-medium

README.md

@@ -1,21 +1,82 @@
 ---
 pipeline_tag: object-detection
 license: apache-2.0
+base_model: ustc-community/dfine-medium-coco
 library_name: kerasformers
 tags:
 - keras
 - kerasformers
+- d-fine
 - dfine
-- tf
-- jax
+- detr
+- object-detection
+- arxiv:2410.13842
 - pytorch
+- jax
+- tf
 ---
 
-# dfine-medium (Keras 3)
+## ***See [our collection](https://huggingface.co/collections/kerasformers/d-fine-6a69d56d4bee59c3f582ebf0) for all versions of D-FINE.***
+
+# Run D-FINE with Keras 3: JAX, PyTorch, or TensorFlow
+
+[![GitHub](https://img.shields.io/badge/GitHub-KerasFormers-black?logo=github)](https://github.com/IMvision12/KerasFormers) [![Docs](https://img.shields.io/badge/Docs-D--FINE-blue)](https://imvision12.github.io/KerasFormers/dfine/) [![Collection](https://img.shields.io/badge/HF-D--FINE%20collection-yellow)](https://huggingface.co/collections/kerasformers/d-fine-6a69d56d4bee59c3f582ebf0)
+
+# kerasformers/dfine-medium
+
+Paper: [D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement (arXiv:2410.13842)](https://arxiv.org/abs/2410.13842) · [HF Papers](https://huggingface.co/papers/2410.13842)
+
+D-FINE is a real-time detector built on the RT-DETR recipe: an HGNetV2 backbone, a hybrid encoder, and a deformable decoder with 300 queries. It is NMS-free. Boxes are regressed via Fine-grained Distribution Refinement: each decoder layer predicts a distribution over discrete offset bins and accumulates refinements across layers.
+
+For more details on the model, please go to the upstream [model card](https://huggingface.co/ustc-community/dfine-medium-coco).
+
+Pure-**Keras 3** conversion of [`ustc-community/dfine-medium-coco`](https://huggingface.co/ustc-community/dfine-medium-coco) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
 
-Pure-Keras 3 weights for [kerasformers](https://github.com/IMvision12/KerasFormers), mirrored from the GitHub release. Apache 2.0.
+This is an **object detection** checkpoint (`DFineDetect`) on COCO (HGNetV2-Medium).
+
+## ✨ Quick start
 
 ```python
-from kerasformers.models.dfine import DFineDetect
-model = DFineDetect.from_weights("dfine-medium")
+import os
+os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"
+
+from PIL import Image
+from kerasformers.models.dfine import DFineDetect, DFineImageProcessor
+
+model = DFineDetect.from_weights("kerasformers/dfine-medium")
+processor = DFineImageProcessor()
+
+image = Image.open("your_image.jpg").convert("RGB")
+inputs = processor(image)
+output = model(inputs["pixel_values"], training=False)
+results = processor.post_process_object_detection(
+    output, threshold=0.5, target_sizes=[(image.height, image.width)]
+)[0]
+for score, name, box in zip(
+    results["scores"], results["label_names"], results["boxes"]
+):
+    print(f"{name}: {float(score):.3f} {box}")
 ```
+
+Load any D-FINE variant the same way with `from_weights("kerasformers/<variant>")`:
+
+| Variant | Hub | Backbone |
+|---|---|---|
+| `dfine-nano` | [`kerasformers/dfine-nano`](https://huggingface.co/kerasformers/dfine-nano) | HGNetV2-Nano |
+| `dfine-small` | [`kerasformers/dfine-small`](https://huggingface.co/kerasformers/dfine-small) | HGNetV2-Small |
+| `dfine-medium` | [`kerasformers/dfine-medium`](https://huggingface.co/kerasformers/dfine-medium) | HGNetV2-Medium |
+| `dfine-large` | [`kerasformers/dfine-large`](https://huggingface.co/kerasformers/dfine-large) | HGNetV2-Large |
+| `dfine-xlarge` | [`kerasformers/dfine-xlarge`](https://huggingface.co/kerasformers/dfine-xlarge) | HGNetV2-XLarge |
+
+## Tips
+
+- Set `KERAS_BACKEND` **before** importing Keras / kerasformers.
+- `DFineImageProcessor` keeps `do_normalize=False` by default (rescaled `[0, 1]` input, matching upstream).
+- See [D-FINE docs](https://imvision12.github.io/KerasFormers/dfine/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
+- Community / upstream safetensors still work via the `hf:` prefix, e.g. `DFineDetect.from_weights("hf:ustc-community/dfine-medium-coco")`.
+
+## Special Thanks
+
+A huge thank you to the D-FINE authors (USTC community) for creating and releasing these models.
+
+License: Apache 2.0.