Models
YOLOv3 PyTorch vs. MobileNet V2 Classification

YOLOv3 PyTorch vs. MobileNet V2 Classification

Both YOLOv3 PyTorch and MobileNet V2 Classification are commonly used in computer vision projects. Below, we compare and contrast YOLOv3 PyTorch and MobileNet V2 Classification.

Models

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YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.
Learn more about YOLOv3 PyTorch
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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
PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
7.2k+
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License
GPL-3.0
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Training Notebook

Compare YOLOv3 PyTorch and MobileNet V2 Classification with Autodistill

Models

YOLOv3 PyTorch vs. MobileNet V2 Classification

.

Both

YOLOv3 PyTorch

and

MobileNet V2 Classification

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

YOLOv3 PyTorch

and

MobileNet V2 Classification
  YOLOv3 PyTorch MobileNet V2 Classification
Date of Release Apr 08, 2018
Model Type Object Detection Classification
Architecture YOLO
GitHub Stars 7200

YOLOv3 PyTorch

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. PyTorch version.

How to AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow 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 AugmentHow to LabelHow to Plot PredictionsHow to Filter PredictionsHow to Create a Confusion Matrix

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