Models

MobileNet SSD v2 vs. YOLOv4 PyTorch

Both

MobileNet SSD v2

and

YOLOv4 PyTorch

are commonly used in computer vision projects. Below, we compare and contrast

MobileNet SSD v2

and

YOLOv4 PyTorch

.

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.

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.

  MobileNet SSD v2 YOLOv4 PyTorch
Date of Release Jan 13, 2018
Community Status
Model Type Object Detection Object Detection
Architecture YOLO
FPS
Framework Used TensorFlow 1.5 PyTorch
Learn more about MobileNet SSD v2Learn more about YOLOv4 PyTorch

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