Models
EfficientNet vs. OpenAI CLIP

EfficientNet vs. OpenAI CLIP

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

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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OpenAI CLIP

CLIP (Contrastive Language-Image Pre-Training) is an impressive multimodal zero-shot image classifier that achieves impressive results in a wide range of domains with no fine-tuning. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.
Model Type
Classification
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Classification
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Model Features
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Item 2 Info
Architecture
CNN
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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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21.4k+
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License
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MIT
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Training Notebook

Compare EfficientNet and OpenAI CLIP with Autodistill

Compare EfficientNet vs. OpenAI CLIP

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.