Models
YOLOR vs. MobileNet SSD v2

YOLOR vs. MobileNet SSD v2

Both YOLOR and MobileNet SSD v2 are commonly used in computer vision projects. Below, we compare and contrast YOLOR and MobileNet SSD v2.

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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MobileNet SSD v2

This architecture provides good realtime results on limited compute. It's designed to run in realtime (30 frames per second) even on mobile devices.
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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Frameworks
PyTorch
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TensorFlow 1.5
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
2k+
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81+
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License
GPL-3.0
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MIT
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Training Notebook

Compare YOLOR and MobileNet SSD v2 with Autodistill

Compare YOLOR vs. MobileNet SSD v2

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.