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Rfdetr Seg Small Fp32

This model was converted to MLX format from RF-DETR (ICLR 2026) using mlx-vlm version 0.4.3.

ArtOtherBasismodellroboflow/rf-detrVersionRevision a7a2375

Modellquelle

Art
Other
Dateigröße
129 MB
Basismodell
roboflow/rf-detr
Version
vRevision a7a2375
Aktualisiert
15. Sept. 2026
Downloads
6
Quelle
Hugging Face

Quellenbeschreibung

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

PresetEffect
mask+boxMask overlay + boxes + labels (default)
blurBlur detections
blur+bgBlur background
pixelatePixelate detections
pixelate+bgPixelate background
halo+boxHalo effect + boxes
boxBoxes + labels only

Model Details

ArchitectureDINOv2-small backbone + C2f projector + Deformable DETR decoder + Segmentation head
TaskObject detection + instance segmentation (COCO 80 classes)
Parameters~34M
Input resolution384x384
Dtypefloat32
Inference (M4 Max)~26ms per frame (~38 FPS)

Reference

Quellen

1 Quelle
Hugging FacePrimärVersion a7a2375b4ca7b2ef0427af91b55d8176ca647b35
huggingface.co/mlx-community/rfdetr-seg-small-fp32/tree/a7a2375b4ca7b2ef0427af91b55d8176ca647b35

Verifiziert 15. Sept.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 129 MB · SHA-256 206e0b4d04f7…085a · Hugging Face

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Quellenauszüge

2 Auszüge

--- 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