Models
OpenAI CLIP vs. YOLOv4 Tiny

OpenAI CLIP vs. YOLOv4 Tiny

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

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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YOLOv4 Tiny

The tiny and fast version of YOLOv4 - good for training and deployment on limited compute resources, and getting a feel for your dataset
Model Type
Classification
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Object Detection
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Model Features
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Item 2 Info
Architecture
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ResNet-D, YOLO
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Frameworks
PyTorch
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Darknet
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
21.4k+
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License
MIT
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YOLO
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Training Notebook

Compare OpenAI CLIP and YOLOv4 Tiny with Autodistill

Compare OpenAI CLIP vs. YOLOv4 Tiny

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.