Models
YOLOv8 Instance Segmentation vs. OpenAI CLIP

YOLOv8 Instance Segmentation vs. OpenAI CLIP

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

Models

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YOLOv8 Instance Segmentation

The state-of-the-art YOLOv8 model comes with support for instance segmentation tasks.
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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
Instance Segmentation
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Classification
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Model Features
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Item 2 Info
Architecture
YOLO
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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 Instance Segmentation and OpenAI CLIP with Autodistill

Compare YOLOv8 Instance Segmentation 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.