PierreMarieCurie/rf-detr-onnx
ONNX model with inference, conversion and visualization scripts for RF-DETR (object detection and instance segmentation)
This tool helps you quickly analyze images to automatically identify and outline objects of interest. You provide an image, and it outputs the same image with bounding boxes and outlines drawn around detected items, along with their labels. It's ideal for engineers or researchers working with computer vision tasks who need to deploy robust object detection and instance segmentation models.
Use this if you need to integrate a high-performance object detection or instance segmentation model into your application, especially when working with existing images.
Not ideal if you need real-time video processing or are looking for a no-code solution for image analysis.
Stars
78
Forks
12
Language
Python
License
MIT
Category
Last pushed
Jan 31, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/PierreMarieCurie/rf-detr-onnx"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
broadinstitute/keras-rcnn
Keras package for region-based convolutional neural networks (RCNNs)
alankbi/detecto
Build fully-functioning computer vision models with PyTorch
sovit-123/fasterrcnn-pytorch-training-pipeline
PyTorch Faster R-CNN Object Detection on Custom Dataset
kenshohara/video-classification-3d-cnn-pytorch
Video classification tools using 3D ResNet
lufficc/SSD
High quality, fast, modular reference implementation of SSD in PyTorch