Models
YOLOv4 PyTorch vs. EfficientNet

YOLOv4 PyTorch vs. EfficientNet

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

Models

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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.
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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.
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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CNN
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Frameworks
PyTorch
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Keras
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
4.4k+
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License
Apache-2.0
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Training Notebook

Compare YOLOv4 PyTorch and EfficientNet with Autodistill

Compare YOLOv4 PyTorch vs. EfficientNet

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.