Models
MobileNet SSD v2 vs. YOLOv4 PyTorch

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.

Models

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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.
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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.
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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YOLO
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Frameworks
TensorFlow 1.5
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
81+
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4.4k+
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License
MIT
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Apache-2.0
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Training Notebook

Compare MobileNet SSD v2 and YOLOv4 PyTorch with Autodistill

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 YOLOv4 PyTorch
Date of Release Jan 13, 2018
Model Type Object Detection Object Detection
Architecture YOLO
GitHub Stars 81 4400

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.

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

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

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