YOLOv4 PyTorch vs. MobileNet V2 Classification: Compared and Contrasted

Models

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YOLOv4 PyTorch vs. MobileNet V2 Classification

Both

YOLOv4 PyTorch

and

MobileNet V2 Classification

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

YOLOv4 PyTorch

and

MobileNet V2 Classification

	YOLOv4 PyTorch	MobileNet V2 Classification
Date of Release
Model Type	Object Detection	Classification
Architecture	YOLO
GitHub Stars	4200

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.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

MobileNet V2 Classification

MobileNet is a GoogleAI model well-suited for on-device, real-time classification (distinct from MobileNetSSD, Single Shot Detector). This implementation leverages transfer learning from ImageNet to your dataset.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix

Learn more about YOLOv4 PyTorch

Learn more about MobileNet V2 Classification