Models
EfficientNet vs. YOLOS

EfficientNet vs. YOLOS

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

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.
Learn more about EfficientNet
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YOLOS

YOLOS looks at patches of an image to to form "patch tokens", which are used in place of the traditional wordpiece tokens in NLP.
Learn more about YOLOS
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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Transformer, YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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Keras
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PyTorch
GitHub
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View Repo
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View Repo
GitHub Stars
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812+
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License
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MIT
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
Compare Alternatives
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Compare EfficientNet and YOLOS with Autodistill

Compare EfficientNet vs. YOLOS

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.