Models
OpenAI CLIP vs. EfficientNet

OpenAI CLIP vs. EfficientNet

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

Models

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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.
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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
Classification
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Classification
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Model Features
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Architecture
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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
21.4k+
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License
MIT
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Training Notebook

Compare OpenAI CLIP and EfficientNet with Autodistill

Compare OpenAI CLIP 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.