Rfdetr Seg Small Fp32
This model was converted to MLX format from RF-DETR (ICLR 2026) using mlx-vlm version 0.4.3.
Model source
- Kind
- Other
- File size
- 129 MB
- Base model
- roboflow/rf-detr
- Version
- vRevision a7a2375
- Updated
- Sep 15, 2026
- Downloads
- 6
- Source
- Hugging Face
Source description
mlx-community/rfdetr-seg-small-fp32
This model was converted to MLX format from RF-DETR (ICLR 2026) using mlx-vlm version 0.4.3.
RF-DETR Seg-Small supports both object detection and instance segmentation on COCO 80 classes.
Use with mlx
pip install -U mlx-vlm
from pathlib import Path
from PIL import Image
from mlx_vlm.utils import load_model
from mlx_vlm.models.rfdetr.processing_rfdetr import RFDETRProcessor
from mlx_vlm.models.rfdetr.generate import RFDETRPredictor
model = load_model(Path("mlx-community/rfdetr-seg-small-fp32"))
processor = RFDETRProcessor.from_pretrained("mlx-community/rfdetr-seg-small-fp32")
predictor = RFDETRPredictor(model, processor, score_threshold=0.3, nms_threshold=0.5)
result = predictor.predict(Image.open("image.jpg"))
# result.boxes - (N, 4) xyxy pixel coordinates
# result.scores - (N,) confidence scores
# result.masks - (N, H, W) binary instance masks
# result.class_names - list of class names
CLI
# Image segmentation
python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32
# Video segmentation
python -m mlx_vlm.models.rfdetr.generate --video input.mp4 --model mlx-community/rfdetr-seg-small-fp32
# Realtime camera
python -m mlx_vlm.models.rfdetr.generate --task realtime --model mlx-community/rfdetr-seg-small-fp32
# Blur background (focus on detections)
python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32 --annotator blur+bg
# Pixelate detections
python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32 --annotator pixelate
Annotator presets
| Preset | Effect |
|---|---|
mask+box | Mask overlay + boxes + labels (default) |
blur | Blur detections |
blur+bg | Blur background |
pixelate | Pixelate detections |
pixelate+bg | Pixelate background |
halo+box | Halo effect + boxes |
box | Boxes + labels only |
Model Details
| Architecture | DINOv2-small backbone + C2f projector + Deformable DETR decoder + Segmentation head |
| Task | Object detection + instance segmentation (COCO 80 classes) |
| Parameters | ~34M |
| Input resolution | 384x384 |
| Dtype | float32 |
| Inference (M4 Max) | ~26ms per frame (~38 FPS) |
Reference
Sources
1 source
Sources
1 sourceVerified Sep 15
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- language: en library_name: mlx pipeline_tag: image-segmentation tags: - mlx - rf-detr - object-detection - instance-segmentation - apple-silicon base_model: roboflow/rf-detr --- # mlx-community/rfdetr-seg-small-fp32 This model was converted to MLX format from [RF-DETR](https://github.com/roboflow/rf-detr) (ICLR 2026) using [mlx-vlm](https://github.com/Blaizzy/mlx-vlm) version **0.4.3**. RF-DETR Seg-Small supports both object detection and instance segmentation on COCO 80 classes. ## Use with mlx ```bash pip install -U mlx-vlm ``` ```python from pathlib import Path from PIL import Image from mlx_vlm.utils import load_model from mlx_vlm.models.rfdetr.processing_rfdetr import RFDETRProcessor from mlx_vlm.models.rfdetr.generate import RFDETRPredictor model = load_model(Path("mlx-community/rfdetr-seg-small-fp32")) processor = RFDETRProcessor.from_pretrained("mlx-community/rfdetr-seg-small-fp32") predictor = RFDETRPredictor(model, processor, score_threshold=0.3, nms_threshold=0.5) result = predictor.predict(Image.open("image.jpg")) # result.boxes - (N, 4) xyxy pixel coordinates # result.scores - (N,) confidence scores # result.masks - (N, H, W) binary instance masks # result.class_names - list of class names ``` ### CLI ```bash # Image segmentation python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32 # Video segmentation python -m mlx_vlm.models.rfdetr.generate --video input.mp4 --model mlx-community/rfdetr-seg-small-fp32 # Realtime camera python -m mlx_vlm.models.rfdetr.generate --task realtime --model mlx-community/rfdetr-seg-small-fp32 # Blur background (focus on detections) python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32 --annotator blur+bg # Pixelate detections python -m mlx_vlm.models.rfdetr.generate --image photo.jpg --model mlx-community/rfdetr-seg-small-fp32 --annotator pixelate ``` ### Annotator presets | Preset | Effect | |--------|--------| | `mask+box` | Mask overlay + boxes + labels (default) | | `blur` | Blur detections | | `blur+bg` | Blur background | | `pixelate` | Pixelate detections | | `pixelate+bg` | Pixelate background | | `halo+box` | Halo effect + boxes | | `box` | Boxes + labels only | ## Model Details | | | |---|---| | Architecture | DINOv2-small backbone + C2f projector + Deformable DETR decoder + Segmentatio...
Source context: 6 downloads · 0 likes · Pipeline image-segmentation · Library mlx · Repo mlx-community/rfdetr-seg-small-fp32
