Models
Scaled-YOLOv4 vs. MobileNet SSD v2

Scaled-YOLOv4 vs. MobileNet SSD v2

Both Scaled YOLOv4 and MobileNet SSD v2 are commonly used in computer vision projects. Below, we compare and contrast Scaled YOLOv4 and MobileNet SSD v2.

Models

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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
Learn more about Scaled YOLOv4
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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
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
2k+
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81+
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License
GPL-3.0
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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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rocket icon
Deploy with Roboflow
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Compare Scaled YOLOv4 and MobileNet SSD v2 with Autodistill

Compare Scaled-YOLOv4 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.