Models
YOLOv8 vs. OpenAI CLIP

YOLOv8 vs. OpenAI CLIP

Both YOLOv8 and OpenAI CLIP are commonly used in computer vision projects. Below, we compare and contrast YOLOv8 and OpenAI CLIP.

Models

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YOLOv8

YOLOv8 is a state-of-the-art object detection and image segmentation model created by Ultralytics, the developers of YOLOv5.
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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
Object Detection
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Classification
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Model Features
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Item 2 Info
Architecture
YOLO, CNN
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
21.1k+
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21.4k+
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License
AGPL-3.0
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MIT
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Training Notebook

Compare YOLOv8 and OpenAI CLIP with Autodistill

Compare YOLOv8 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.