Models
YOLOv10 vs. YOLOR

YOLOv10 vs. YOLOR

Both YOLOv10 and YOLOR are commonly used in computer vision projects. Below, we compare and contrast YOLOv10 and YOLOR.

Models

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YOLOv10

YOLOv10 is a real-time object detection model introduced in the paper "YOLOv10: Real-Time End-to-End Object Detection".
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YOLOR

YOLOR (You Only Learn One Representation) is an object detection model that uses both implicit and explicit knowledge to make predictions.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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CNN, YOLO
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7800
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2k+
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License
GNU Affero General Public
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GPL-3.0
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Training Notebook

Compare YOLOv10 and YOLOR with Autodistill

Compare YOLOv10 vs. YOLOR

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.