Models
OpenAI CLIP vs. Scaled-YOLOv4

OpenAI CLIP vs. Scaled-YOLOv4

Both OpenAI CLIP and Scaled YOLOv4 are commonly used in computer vision projects. Below, we compare and contrast OpenAI CLIP and Scaled YOLOv4.

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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Scaled YOLOv4

Scaled YOLOv4 is an extension of the YOLOv4 research implemented in the YOLOv5 PyTorch framework.
Model Type
Classification
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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YOLO
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
21.4k+
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2k+
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License
MIT
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GPL-3.0
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Training Notebook

Compare OpenAI CLIP and Scaled YOLOv4 with Autodistill

Compare OpenAI CLIP vs. Scaled-YOLOv4

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.