Models
4M vs. YOLOv5

4M vs. YOLOv5

Both 4M and YOLOv5 are commonly used in computer vision projects. Below, we compare and contrast 4M and YOLOv5.

Models

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4M

The 4M model is a versatile multimodal Transformer model developed by EPFL and Apple, capable of handling a handful of vision and language tasks.
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YOLOv5

A very fast and easy to use PyTorch model that achieves state of the art (or near state of the art) results.
Model Type
Multimodal Model
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
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CNN, YOLO
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Frameworks
PyTorch
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub Stars
1.1k
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46k+
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License
Apache 2.0
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AGPL-3.0
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Training Notebook

Compare 4M and YOLOv5 with Autodistill

Compare 4M vs. YOLOv5

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.