Models
RF-DETR vs. YOLOv4 PyTorch

RF-DETR vs. YOLOv4 PyTorch

Both RF-DETR and YOLOv4 PyTorch are commonly used in computer vision projects. Below, we compare and contrast RF-DETR and YOLOv4 PyTorch.

Models

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RF-DETR

RF-DETR is a SOTA, real-time object detection model architecture developed by Roboflow and released under the Apache 2.0 license.
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YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
Transformers
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YOLO
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Frameworks
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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4.4k+
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License
Apache 2.0
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Apache-2.0
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Training Notebook

Compare RF-DETR and YOLOv4 PyTorch with Autodistill

Compare RF-DETR vs. YOLOv4 PyTorch

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.