Models
Scaled-YOLOv4 vs. MobileNet V2 Classification

Scaled-YOLOv4 vs. MobileNet V2 Classification

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

Models

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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
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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.
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
2k+
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License
GPL-3.0
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Training Notebook

Compare Scaled YOLOv4 and MobileNet V2 Classification with Autodistill

Compare Scaled-YOLOv4 vs. MobileNet V2 Classification

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.