metadata
language: en
tags:
- mlx
- rf-detr
- object-detection
- instance-segmentation
- apple-silicon
base_model: roboflow/rf-detr
library_name: mlx
pipeline_tag: image-segmentation
mlx-community/rfdetr-seg-large-fp32
This model was converted to MLX format from RF-DETR (ICLR 2026) using mlx-vlm version 0.4.3.
RF-DETR Seg-Large produces higher quality instance masks than Seg-Small thanks to higher input resolution (504px vs 384px), more decoder layers (5 vs 4), and more segmentation blocks (5 vs 4).
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-large-fp32"))
processor = RFDETRProcessor.from_pretrained("mlx-community/rfdetr-seg-large-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 --task segment --image photo.jpg --model mlx-community/rfdetr-seg-large-fp32
# Video processing
python -m mlx_vlm.models.rfdetr.generate --task track --video input.mp4 --model mlx-community/rfdetr-seg-large-fp32
# Realtime camera
python -m mlx_vlm.models.rfdetr.generate --task realtime --model mlx-community/rfdetr-seg-large-fp32
# Blur background
python -m mlx_vlm.models.rfdetr.generate --task segment --image photo.jpg --model mlx-community/rfdetr-seg-large-fp32 --annotator blur+bg
Model Details
| Architecture | DINOv2-small backbone + C2f projector + 5-layer Deformable DETR decoder + 5-block Segmentation head |
| Task | Object detection + instance segmentation (COCO 80 classes) |
| Parameters | ~36M |
| Input resolution | 504x504 |
| Mask resolution | 126x126 |
| Dtype | float32 |
| Inference (M4 Max) | |
| Peak memory | ~1.2 GB |
Comparison
| Model | Resolution | Mask quality | Inference | Memory |
|---|---|---|---|---|
| rfdetr-seg-small-fp32 | 384px (96x96 masks) | Good | ~26ms (38 FPS) | 683 MB |
| rfdetr-seg-large-fp32 | 504px (126x126 masks) | Better | ~89ms (11 FPS) | 1.2 GB |