Models
YOLOS vs. MobileNet SSD v2

YOLOS vs. MobileNet SSD v2

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

Models

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YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.
Learn more about YOLOS
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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.
Learn more about MobileNet SSD v2
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
Transformer, 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
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View Repo
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View Repo
GitHub Stars
812+
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81+
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License
MIT
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MIT
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
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Compare YOLOS and MobileNet SSD v2 with Autodistill

Compare YOLOS 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.