Models
YOLOv4 Tiny vs. OpenAI CLIP

YOLOv4 Tiny vs. OpenAI CLIP

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

Models

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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
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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
Item 1 Info
Item 2 Info
Architecture
ResNet-D, YOLO
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Frameworks
Darknet
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
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21.4k+
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License
YOLO
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MIT
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Training Notebook

Compare YOLOv4 Tiny and OpenAI CLIP with Autodistill

Compare YOLOv4 Tiny 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.