Models
YOLOR vs. MT-YOLOv6

YOLOR vs. MT-YOLOv6

Both YOLOR and MT-YOLOv6 are commonly used in computer vision projects. Below, we compare and contrast YOLOR and MT-YOLOv6.

Models

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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.
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MT-YOLOv6

MT-YOLOv6 is a YOLO based model released in 2022.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
CNN, 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
2k+
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5.5k+
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License
GPL-3.0
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GPL-3.0
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Training Notebook

Compare YOLOR and MT-YOLOv6 with Autodistill

Compare YOLOR vs. MT-YOLOv6

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.