Models
EfficientNet vs. YOLOv4 PyTorch

EfficientNet vs. YOLOv4 PyTorch

Both EfficientNet and YOLOv4 PyTorch are commonly used in computer vision projects. Below, we compare and contrast EfficientNet and YOLOv4 PyTorch.

Models

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EfficientNet

EfficientNet is from a family of image classification models from GoogleAI that train comparatively quickly on small amounts of data, making the most of limited datasets.
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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
Classification
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
CNN
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YOLO
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Frameworks
Keras
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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4.4k+
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License
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Apache-2.0
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Training Notebook

Compare EfficientNet and YOLOv4 PyTorch with Autodistill

Compare EfficientNet vs. YOLOv4 PyTorch

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.