YOLOv4 vs. MobileNet V2 Classification

Both YOLOv4 Darknet and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOv4 Darknet and MobileNet V2 Classification.

Models

YOLOv4 Darknet

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 Darknet.

Learn more about YOLOv4 Darknet

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.

Learn more about MobileNet V2 Classification

Model Type

Object Detection

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Classification

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Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

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Frameworks

Darknet

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Annotation Format

Instance Segmentation

Instance Segmentation

GitHub

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GitHub Stars

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License

YOLO

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Paper

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Training Notebook

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Deploy Model

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Deploy with Roboflow

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Deploy with Roboflow

Compare YOLOv4 Darknet and MobileNet V2 Classification with Autodistill

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YOLOv4 vs. MobileNet V2 Classification

YOLOv4 vs. MobileNet V2 Classification

.

Both

YOLOv4 Darknet

and

MobileNet V2 Classification

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

YOLOv4 Darknet

and

MobileNet V2 Classification

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

YOLOv4 Darknet

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 Darknet.

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 Darknet

Learn more about MobileNet V2 Classification

Compare YOLOv4 Darknet to other models

MobileNet V2 Classification

MobileNet SSD v2

Compare MobileNet V2 Classification to other models

YOLOv8 Instance Segmentation

YOLOv7 Instance Segmentation

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