Models
YOLOv4 PyTorch vs. MobileNet SSD v2

YOLOv4 PyTorch vs. MobileNet SSD v2

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

Models

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YOLOv4 PyTorch

YOLOv4 has emerged as the best real time object detection model. YOLOv4 carries forward many of the research contributions of the YOLO family of models along with new modeling and data augmentation techniques. This implementation is in PyTorch.
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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
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
4.4k+
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81+
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License
Apache-2.0
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MIT
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Training Notebook

Compare YOLOv4 PyTorch and MobileNet SSD v2 with Autodistill

Compare YOLOv4 PyTorch 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.